natolambert/rlhf-book

A deep dive into RLHF and it’s applications from scratch.

Implementation of RLHF (Reinforcement Learning with Human Feedback) on top of the PaLM architecture. Basically ChatGPT but with PaLM

Comprehensive toolkit for Reinforcement Learning from Human Feedback (RLHF) training, featuring instruction fine-tuning, reward model training, and support for PPO and DPO algorithms with various configurations for the Transformer 5 models including Qwen 3.0

A continually updated list of literature on Reinforcement Learning from AI Feedback (RLAIF)

An Easy-to-use, Scalable and High-performance Agentic RL Framework based on Ray (PPO & DAPO & REINFORCE++ & VLM & TIS & vLLM & Ray & Async RL)

Democratizing Reinforcement Learning for LLMs

Code for Deep RL from Human Preferences [Christiano et al]. Plus a webapp for collecting human feedback

🚀 An open-source, hands-on curriculum bridging the gap from basic RL concepts to LLM alignment, RLVR, and advanced Agentic systems.

A repo for distributed training of language models with Reinforcement Learning via Human Feedback (RLHF)