这是一个从零开始构建的强化学习人类反馈（RLHF）学习代码库，实现了 PPO、GRPO、GSPO 以及相关的策略优化算法，并提供了清晰、可复现的训练流程。由于文档是由latex文件转译过来，如果md文件渲染异常，请用VScode的md插件打开

This repository contains lecture notes, practical materials, and implementations for the course: "Reinforcement Learning: from Bandits to RLHF" The course is designed to provide a deep and systematic understanding of RL, combining: solid mathematical foundations intuitive explanations practical implementations modern research insights

Official Code for our paper: "Language Models Learn to Mislead Humans via RLHF""

🤖 Enhance reinforcement learning stability and efficiency with advanced algorithms like TRPO, PPO, DPO, GRPO, DAPO, and GSPO for optimized policy training.

This repository contains the implementation of a Reinforcement Learning with Human Feedback (RLHF) system using custom datasets. The project utilizes the trlX library for training a preference model that integrates human feedback directly into the optimization of language models.

You will learn about RLHF from this repository 🤖.

🚀 Master AI fine-tuning on consumer hardware! Learn LoRA, DoRA, QDoRA, PiSSA & RLHF through engaging stories & hands-on tutorials. Optimized for AMD GPUs (ROCm). From 15-min demos to production deployment. Features LLaMA-Factory zero-code interface & constitutional AI. 🇺🇸🇹🇷 Available in English & Turkish.

The RLHF (Reinforcement Learning from Human Feedback) repository provides an implementation of reinforcement learning (RL) enhanced by human feedback. It enables agents to improve their learning and performance when traditional reward signals are insufficient or hard to define.

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Learning RLHF

🎮 Interactive browser-based labs for "Complete Reinforcement Learning Journey: From Basics to RLHF" — visualize algorithms, tweak parameters, and watch agents learn in real-time.

Developing a Reinforcement Learning model to learn to play Pokemon Platinum, integrating this into the code through a desktop emulator such as DeSmuME. Will then utilise RLHF (Reinforcement Learning with Human Feedback) for model training.

microDPO: A minimalist, pure PyTorch implementation of Direct Preference Optimization. Inspired by nanoGPT, it strips away massive RLHF libraries to reveal the elegant math behind AI alignment. Demystify how LLMs learn human preferences with a single, highly readable file. Train a tiny aligned model on your laptop in minutes.

OmniForge is a platform a brand's knowledge base (PDFs, Brand Guidelines) is ingested and an AI Agent then uses RAG to understand the brand voice. system generates marketing copy and matching social media assets (Diffusion). for "perfection," the system uses LoRA for consistent style and RLHF to learn from human marketing experts' feedback.

Additional experiments to the paper "Language Models Learn to Mislead Humans via RLHF""

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Learning setting up RL environments and post-training flows.

https://www.youtube.com/watch?v=JgvyzIkgxF0&ab_channel=ArxivInsights

可以用来简单 debug 查看中间过程的 rlhf 学习框架

RLHF学习记录

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A learning material list of RLHF (Updating)

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Created with CodeSandbox

Using Reinforcement Learning with Human Feedback (RLHF) for optimizing cybersecurity educational learning paths.

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Reinforcement Learning from Human Feedback Exploration using Nvidia's HelpSteer3 Database