Moreover, we discuss strategies for metadata selection and human evaluation to ensure the quality and effectiveness of ITDs. By integrating these elements, this tutorial provides a structured ...

In this tutorial, we show how we treat prompts as first-class, versioned artifacts and apply rigorous regression testing to large language model behavior using MLflow. We design an evaluation pipeline ...

This project provides a minimal, easy-to-understand codebase for fine-tuning Large Language Models. Our core philosophy is to explain complex optimization techniques with the simplest possible code.