OpenRLHF
An Easy-to-use, Scalable and High-performance Agentic RL Framework based on Ray (PPO & DAPO & REINFORCE++ & VLM & TIS & vLLM & Ray & Async RL)
Build and scale reinforcement learning systems that learn from human feedback with an easy-to-use framework.
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Free · no card · unsubscribe anytimeAn Easy-to-use, Scalable and High-performance Agentic RL Framework based on Ray (PPO & DAPO & REINFORCE++ & VLM & TIS & vLLM & Ray & Async RL)
OpenRLHF has 10k stars on GitHub. It has been forked 1k times. OpenRLHF is written mainly in Python. It has been in active development since 2023. OpenRLHF is available under the Apache-2.0 license. Its main topics are large-language-models, proximal-policy-optimization, raylib, reinforcement-learning.
What is OpenRLHF?
An Easy-to-use, Scalable and High-performance Agentic RL Framework based on Ray (PPO & DAPO & REINFORCE++ & VLM & TIS & vLLM & Ray & Async RL)
Is OpenRLHF open source?
OpenRLHF is an open-source project. It is released under the Apache-2.0 license.
Is OpenRLHF free?
Yes. OpenRLHF is free and open source — you can use, modify and self-host it.
What license does OpenRLHF use?
OpenRLHF is available under the Apache-2.0 license.
What language is OpenRLHF written in?
OpenRLHF is written mainly in Python.
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