verl: Volcano Engine Reinforcement Learning for LLMs verl is a RL training library initiated by ByteDance Seed team and maintained by the verl community verl: Volcano Engine Reinforcement Learning for LLMs verl is a flexible, efficient and production-ready RL training library for large language models (LLMs)
Welcome to verl’s documentation! — verl documentation Welcome to verl’s documentation! verl is a flexible, efficient and production-ready RL training framework designed for large language models (LLMs) post-training It is an open source implementation of the HybridFlow paper
verl · PyPI verl: Volcano Engine Reinforcement Learning for LLMs verl is a flexible, efficient and production-ready RL training library for large language models (LLMs) verl is the open-source version of HybridFlow: A Flexible and Efficient RLHF Framework paper
Welcome to veRL HybridFlow’s documentation! veRL is free software; you can redistribute it and or modify it under the terms of the Apache License 2 0 We welcome contributions Join us on GitHub
What Is verl: Volcano Engine Reinforcement Learning for LLMs? Q1: What exactly is verl? A: Verl is an open-source reinforcement learning training library tailored for large language models, offering support for algorithms like PPO, GRPO, and ReMax It’s designed to integrate seamlessly with popular LLM frameworks
Installation — verl documentation Install verl For installing the latest version of verl, the best way is to clone and install it from source Then you can modify our code to customize your own post-training jobs
Reinforcement Learning from Human Feedback on AMD GPUs with verl and . . . In this blog post, we provide an overview of Volcano Engine Reinforcement Learning for LLMs (verl) and discuss its benefits in large-scale reinforcement learning from human feedback (RLHF) We also detail the modifications made to the codebase to optimize verl’s performance on AMD Instinct GPUs