natolambert/rlhf-book

This project serves as an open-source textbook and accompanying code repository, meticulously documenting Reinforcement Learning from Human Feedback (RLHF) and advanced post-training techniques for language models. It aims to consolidate fragmented knowledge, provide canonical references for established methods, and shed light on emerging industry practices like 'Character Training.' By offering both theoretical explanations and practical code implementations, it acts as a foundational resource for researchers, developers, and students seeking to master the complexities of aligning large language models with human preferences in a rapidly evolving AI landscape.