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 implement an end-to-end Direct Preference Optimization workflow to align a large language model with human preferences without using a reward model. We combine TRL’s DPOTrainer ...

This guide assumes that the project is being built on Linux* but equivalent steps can be performed on any other operating system. cmake path/to/repo/root && cmake --build . To run the tests, proceed ...

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.