Evaluating Llama 3.2 3B

In this chapter, you will dive into evaluating a custom AI model built from the Llama 3.2 3B framework. We'll explore how adjusting parameters like temperature can impact the model's performance and reliability when generating responses to specific queries.

You’ll learn about setting up your own custom model with Docker and understand why tweaking settings such as context size is crucial for better results. The chapter also covers testing different scenarios, including data generation and query response accuracy, under varying conditions.

By the end of this section, you'll have a clearer picture of how to fine-tune AI models to meet specific needs and improve their usability in real-world applications.