Tags: #rlhf

An easy-to-use, scalable, and high-performance open-source framework for Reinforcement Learning from Human Feedback (RLHF) based on Ray and vLLM.

An efficient toolkit for fine-tuning ChatGLM-6B models using PEFT methods, enabling customization and deployment of large language models.

A comprehensive open-source textbook and code repository dedicated to Reinforcement Learning from Human Feedback (RLHF) and post-training language models.

Provides robust recipes and training code to align language models with human and AI preferences, enhancing helpfulness and safety.

A continually updated, curated list of essential resources for Reinforcement Learning with Human Feedback (RLHF), encompassing research papers, codebases, datasets, and related materials.

A modular framework for aligning any-modality large models with human intentions and values using diverse fine-tuning and reinforcement learning methods.

A modular open-source framework for training constrained value-aligned Large Language Models (LLMs) using Safe Reinforcement Learning from Human Feedback (RLHF).

A human preference reward model for evaluating and improving text-to-image generation models.

A comprehensive collection of recipes and code for training various reward models crucial for Reinforcement Learning from Human Feedback (RLHF) in large language models.

An open-source framework providing code, models, and insights for stable Reinforcement Learning from Human Feedback (RLHF) training in Large Language Models, focusing on the PPO algorithm and reward modeling.