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uv-verl-rl-training

Run large-scale RL training for LLMs with verl and GRPO.

1|Updated Feb 6, 2026
Search Tags:#reinforcement learning#LLM training#distributed training#PPO#GRPO#verl
One-click install
npx skills add https://github.com/uv-xiao/pkbllm --skill uv-verl-rl-training
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: uv-verl-rl-training
Source: https://github.com/uv-xiao/pkbllm/tree/main/knowledge/ML/training/verl
Command: npx skills add https://github.com/uv-xiao/pkbllm --skill uv-verl-rl-training

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides a robust and scalable framework for training Large Language Models (LLMs) using Reinforcement Learning (RL), addressing the complexities of distributed training and various RL algorithms.

Core Features & Use Cases

  • Reinforcement Learning: Supports advanced RL algorithms like GRPO, PPO, and others for LLM post-training.
  • Scalable Infrastructure: Designed for large-scale training with flexible backend support (FSDP, Megatron-LM, vLLM).
  • Use Case: Train a chatbot to follow complex instructions more accurately by using GRPO on a dataset of user prompts and desired responses, leveraging a distributed GPU cluster.

Quick Start

Launch GRPO training for math reasoning using the verl skill.

Frequently Asked Questions about uv-verl-rl-training

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I scale reinforcement learning training for large language models using PPO or GRPO?▼

Scale LLM reinforcement learning training using the verl library, which supports advanced algorithms like PPO and GRPO. It integrates with distributed backends like FSDP, Megatron-LM, and vLLM to handle large-scale post-training infrastructure efficiently.

Can I use vLLM and Megatron-LM together for distributed LLM training?▼

Yes, distributed LLM training supports flexible backend integrations with both vLLM and Megatron-LM. You can leverage these frameworks alongside FSDP to manage large-scale GPU clusters during reinforcement learning post-training.

What is the best way to start GRPO training for math reasoning on a GPU cluster?▼

Start GRPO training for math reasoning by launching the verl skill. It provides production-ready infrastructure to train chatbots or models on datasets of user prompts and desired responses using a distributed GPU cluster.

Does this reinforcement learning framework support algorithms other than PPO?▼

Yes, the reinforcement learning framework supports multiple advanced algorithms beyond PPO, including GRPO and RLOO. These algorithms facilitate accurate LLM post-training for complex instruction following.

Do I need a distributed GPU cluster to perform LLM post-training with verl?▼

Large-scale LLM post-training requires a distributed GPU cluster to effectively utilize backend integrations like FSDP, Megatron-LM, and vLLM. This scalable infrastructure addresses the complexities of large model reinforcement learning.

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