Evaluating Qwen Coder 7b

In this chapter, you will explore how to fine-tune and evaluate the Qwen Coder 7B model by adjusting its temperature setting. You'll learn about creating a custom Docker image for your AI model and testing it with different configurations. We’ll dive into two scenarios: one where the temperature is set very low (0.01) and another where it’s set to a higher value (1).

You will see how these settings affect data generation, query results, and overall performance. The chapter includes detailed tables comparing the outcomes of each scenario, helping you understand which setting works best for your specific use case.

By reading this chapter, you'll gain insights into optimizing AI models for better accuracy and naturalness in responses. So, if you're curious about how to tweak your model settings for optimal results, keep reading!