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After meeting the [prerequisites](/official/projects/waste_identification_ml/circularnet-docs/content/before-you-begin), follow these steps to clone the project from the [GitHub repository](https://github.com/tensorflow/models/tree/master/official/projects/waste_identification_ml) and install all the required packages.
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After meeting the [prerequisites](before-you-begin.md),
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follow these steps to clone the project from the [GitHub repository](https://github.com/tensorflow/models/tree/master/official/projects/waste_identification_ml) and install all the required packages.
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Run the following commands on the **SSH-in-browser** window of your VM instance
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in Google Cloud or the terminal of your edge device:
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sudo apt-get install git
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```
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**Note:** If the `Do you want to continue?` message is displayed, enter `Y` and press **Enter** to continue.<br><br>
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1. Clone the [GitHub repository](https://github.com/tensorflow/models/tree/master/official/projects/waste_identification_ml):
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1. Clone the tensorflow models, which contains Circularnet
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(waste_identification_ml) [Repo link](https://github.com/tensorflow/models)
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```
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git clone --depth 1 https://github.com/tensorflow/models.git
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```
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**Note:** If the scripts from this guide are unavailable on GitHub, the
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CircularNet team provides zip files for you to download locally. In that
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case, cloning from GitHub is unnecessary; you only have to unzip the
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files.<br><br>
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1. Open the `client` folder in the `prediction_pipeline` directory:
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1. Open the `client` folder within the `waste_identification_ml` project
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directory:
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```
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cd models/official/projects/waste_identification_ml/Triton_TF_Cloud_Deployment/client/
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```
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1. Run the `requirements.sh` script to install all the required packages and libraries:
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1. Run `requirements.sh` to install all the required packages and libraries:
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```
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sh requirements.sh
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```
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**Note:** If the `Do you want to continue?` message is displayed, enter `Y` and press **Enter** to continue.<br><br>
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1. Return to the root directory:
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```
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cd\
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```
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Then, press **Enter**.
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Next, start the triton inference server that will serve inference requests. [Start server](start-server.md)

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