Project Title

OpenRLHF — High-Performance, Scalable RLHF Framework for Efficient Distributed Training

Overview

OpenRLHF is an open-source RLHF (Reinforcement Learning from Human Feedback) framework designed for ease of use, scalability, and high performance. Built on Ray, vLLM, ZeRO-3, and HuggingFace Transformers, it simplifies RLHF training and enables efficient distributed scheduling, making it accessible for models up to 70B parameters.

Key Features

Distributed Architecture with Ray for scalable training across multiple GPUs
vLLM Inference Acceleration and AutoTP for high-throughput, memory-efficient sample generation
Memory-Efficient Training with ZeRO-3 and AutoTP, enabling large model training without heavyweight frameworks
Optimized PPO Implementation with advanced tricks for enhanced training stability and reward quality

Use Cases

Researchers and developers needing a scalable framework for training large language models with RLHF
Enterprises looking to implement efficient distributed training for AI models up to 70B parameters
Academia and institutions requiring a high-performance framework for research in reinforcement learning and human feedback

Advantages

Supports Hybrid Engine scheduling for maximizing GPU utilization
Native integration with HuggingFace Transformers for seamless model loading and fine-tuning
Incorporates advanced PPO tricks for improved training stability and reward quality
Open-source and community-driven, allowing for continuous improvement and customization

Limitations / Considerations

The project's license is currently unknown, which may affect its use in certain commercial applications
As with any complex framework, there may be a learning curve for new users to fully leverage its capabilities
The framework's performance may be dependent on the specific hardware and infrastructure used for training

Ray: A framework for distributed computing that OpenRLHF leverages for its distributed architecture.
DeepSpeed: A deep learning optimization library that provides ZeRO-3, used by OpenRLHF for memory-efficient training.
HuggingFace Transformers: A library of pre-trained models that OpenRLHF integrates with for model loading and fine-tuning.

Basic Information

GitHub: https://github.com/OpenRLHF/OpenRLHF
Stars: 8,088
License: Unknown
Last Commit: 2025-10-08

📊 Project Information

Project Name: OpenRLHF
GitHub URL: https://github.com/OpenRLHF/OpenRLHF
Programming Language: Python
⭐ Stars: 8,088
🍴 Forks: 787
📅 Created: 2023-07-30
🔄 Last Updated: 2025-10-08

🏷️ Project Topics

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📚 Documentation

This article is automatically generated by AI based on GitHub project information and README content analysis

OpenRLHF

Project Description