Verl Rl Training
技能 活跃Provides guidance for training LLMs with reinforcement learning using verl (Volcano Engine RL). Use when implementing RLHF, GRPO, PPO, or other RL algorithms for LLM post-training at scale with flexible infrastructure backends.
To enable users to implement advanced LLM post-training techniques like RLHF, GRPO, and PPO at scale using the verl library.
功能
- Guidance for RLHF, GRPO, PPO, and other RL algorithms
- Support for large-scale LLM post-training
- Flexible infrastructure backend configurations
- Detailed installation and quick start examples
- Comprehensive configuration reference
使用场景
- Implementing RLHF for LLM fine-tuning
- Training LLMs with GRPO for reasoning tasks
- Scaling PPO training for large language models
- Leveraging flexible backends like FSDP, Megatron-LM, and vLLM
非目标
- Megatron-native training (recommends other tools)
- PyTorch-native abstractions with Monarch (recommends other tools)
- Simple SFT/DPO (recommends other tools)
工作流
- Prepare Dataset
- Define Reward Function
- Create Training Config
- Launch Training
- Monitor and Validate
实践
- Reinforcement Learning
- LLM Post-Training
- Distributed Systems
先决条件
- GPU cluster with 8+ GPUs (H100 recommended for math tasks)
- Dataset in parquet format with 'prompt' and 'reward_model' columns
- Base model from HuggingFace Hub
- Install Megatron-LM bridge (for Megatron workflow)
Trust
- warning:Issues AttentionIn the last 90 days, 17 issues were opened and 4 were closed, indicating a low closure rate and potentially slow maintainer response.
安装
npx skills add davila7/claude-code-templates通过 npx 运行 Vercel skills CLI(skills.sh)— 需要本地安装 Node.js,以及至少一个兼容 skills 的智能体(Claude Code、Cursor、Codex 等)。前提是仓库遵循 agentskills.io 格式。
质量评分
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