Openrlhf Training
Skill Verified ActiveHigh-performance RLHF framework with Ray+vLLM acceleration. Use for PPO, GRPO, RLOO, DPO training of large models (7B-70B+). Built on Ray, vLLM, ZeRO-3. 2× faster than DeepSpeedChat with distributed architecture and GPU resource sharing.
To enable efficient and high-performance Reinforcement Learning from Human Feedback (RLHF) training for large language models using a distributed architecture with advanced acceleration techniques.
Features
- High-performance RLHF training framework
- Support for PPO, GRPO, RLOO, DPO algorithms
- Ray + vLLM acceleration for large models (7B-70B+)
- Distributed architecture with multi-node GPU cluster support
- Hybrid Engine for GPU resource sharing
Use Cases
- Training large language models with RLHF
- Fine-tuning models on custom reward functions
- Leveraging distributed computing for faster training
- Accelerating inference during RLHF rollout phases
Non-Goals
- Single-node or basic model fine-tuning
- Environments without GPU acceleration capabilities
- Inference-only model serving outside of the training loop
Installation
npx skills add davila7/claude-code-templatesRuns the Vercel skills CLI (skills.sh) via npx — needs Node.js locally and at least one installed skills-compatible agent (Claude Code, Cursor, Codex, …). Assumes the repo follows the agentskills.io format.
Quality Score
VerifiedTrust Signals
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