#grpo (14 Repositories)
Ranked open-source repositories tagged with #grpo, scored by pull request acceptance likelihood and maintainer engagement velocity.
37.5%
42.0h
14 repositories tagged #grpo
verl-project/verl-omni
Multimodal RL training framework for diffusion & omni models
walkinglabs/hands-on-modern-rl
🚀 An open-source, hands-on curriculum bridging the gap from basic RL concepts to LLM alignment, RLVR, and advanced Agentic systems.
modelscope/ms-swift
Use PEFT or Full-parameter to CPT/SFT/DPO/GRPO 600+ LLMs (Qwen3.8, DeepSeek-V4, GLM-5.1, InternLM3, Llama4, ...) and 300+ MLLMs (Qwen3-VL, Qwen3-Omni, InternVL3.5, Ovis2.5, GLM5.3, Gemma4, Llava, Phi4, ...) (AAAI 2025).
hud-evals/hud-python
RL environments + evals for AI agents. Define once, train anything.
oumi-ai/oumi
Easily fine-tune (SFT/RL), evaluate, and deploy Qwen, Gemma, or any open agentic LLM/VLM!
redai-studio/Relax
An Asynchronous Reinforcement Learning Engine for Omni-Modal Post-Training at Scale
OpenPipe/ART
Agent Reinforcement Trainer: train multi-step agents for real-world tasks using GRPO. Give your agents on-the-job training. Reinforcement learning for Qwen3.6, GPT-OSS, Llama, and more!
inclusionAI/AReno
An easy-to-use, fast toolkit to scale up RL post-training on a single node.
Haozhe-Xing/agent_learning
A systematic AI Agent development tutorial covering LLM agents, RAG, tool use, memory systems, multi-agent systems, LangChain, LangGraph, MCP, and agentic RL.｜从零开始学 AI Agent 开发 | 系统、全面、实战导向的 Agent 开发教程 | 每日自动追踪 arXiv 最新论文 | Learn AI Agent Development from Scratch
whitecircle/halo
Halo is an open-source framework built by White Circle for training large language and multimodal models
adithya-s-k/FineEnvs
FineEnvs — RL Environments 101: building and scaling RL environments in the age of LLMs
jiangxinke/Harness-RL
Agentic RAG R1 Framework via Reinforcement Learning
Gen-Verse/Open-AgentRL
RLAnything (ICML 2026) & AutoTool (ICML 2026), DemyAgent: Open-Source RL for LLMs and Agentic Scenarios
datawhalechina/diy-llm
Covers pre-training data, Tokenizer, Transformer, MoE,distributed training, Scaling Laws, inference & alignment .6 progressive code assignments for full-stack LLM learning | 涵盖预训练数据、分词器、Transformer、MoE、分布式训练、缩放定律、推理与对齐，6 项渐进代码作业，掌握 LLM 全栈知识