From the course: AWS Certified Machine Learning Engineer - Associate (MLA-C02) Cert Prep

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Inference parameters in action

Inference parameters in action

From the course: AWS Certified Machine Learning Engineer - Associate (MLA-C02) Cert Prep

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Inference parameters in action

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Inference Parameters in Action, a hands-on tutorial. What happens when you crank up the temperature on a language model to maximum, or when you set top-k to just 5 tokens? I'm going to show you the side-by-side comparisons that demonstrate how tiny adjustments to these parameters can dramatically change the personality, creativity, and reliability of your AI models. In this hands-on tutorial, we're going to experiment with inference parameters and observe their effects in real-time. I'll be demonstrating with practical examples how temperature, TopK and TopP sampling affect model outputs for different use cases. By the end of this video, you'll have a visual understanding of how to configure these parameters to achieve exactly the type of responses you need from your language models. Let's dive in and start experimenting. Now we're here in Amazon Bedrock, and you can see that you have the option here to open a playground. Click that. Let's go for the chat option, and you have the area…

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