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Single-file implementation to advance vision-language-action (VLA) models with reinforcement learning.
| Date | Stars |
|---|---|
| 2026-07-31 | 447 |
| 2026-08-03 | 447 |
| 2026-08-04 | 447 |
| 2026-08-05 | 448 |
| 2026-08-06 | 448 |
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# VLA-RL: Towards Masterful and General Robotic Manipulation with Scalable Reinforcement Learning
<div align="center">
[](https://congruous-farmhouse-8db.notion.site/VLA-RL-Toward-Masterful-and-General-Robotic-Manipulation-with-Scalable-Reinforcement-Learning-1953a2cd706280ecaad4e93a5bd2b8e3?pvs=4)
</div>
## 🌟 Highlights
- 🎯 **General Manipulation**: Improving OpenVLA-7B with outcome-based multi-task reinforcement learing.
- ⚡️ **Cutting-edge Architecture**: Built with Ray+vLLM+LoRA+FSDP, our codebase delivers both scalability and flexibility.
- 📝 **Clean Implementation**: Following [cleanrl](https://github.com/vwxyzjn/cleanrl)'s philosophy, we provide a single-file implementation for easy reading and modification.
- 🚧 **Active Development**: Work in Progress, let's build it together.
## 📝 TODO
- [ ] Support SERL-style Real-world RL
- [ ] Support More Environments (e.g., Roboverse)
- [ ] Support More VLAs (e.g., MiniVLA)
## 🛠️ Installation
See [INSTALL.md](docs/INSTALL.md) for installation instructions.
See [ERROR_CATCH.md](docs/ERROR_CATCH.md) for error catching.
## 🚀 Quick Start
Before launching distributed training, please edit the script with the appropriate dataset and model paths first.
### 📈 Training
```bash
# bash scripts/train_rl_vllm_ray_fsdp.sh <gpus> <task_ids>
# e.g.,
bash scripts/train_rl_vllm_ray_fsdp.sh 0,1 0,1,2,3,4,5,6,7,8,9
```
### 🧪 Evaluation
```bash
# parallel evaluation with vectorized environment
bash scripts/eval_vllm_ray.sh 0,1
```
## 🏷️ License
This repository is released under the Apache-2.0 license.
## 🙏 Acknowledgement
Our code is built upon [open-instruct](https://github.com/allenai/open-instruct), [OpenRLHF](https://github.com/OpenRLHF/OpenRLHF), [verl](https://github.com/volcengine/verl) and [openvla](https://github.com/openvla/openvla). We thank all these authors for their nicely open sourced code and their great contributions to the community.
## 🥰 Citation
If you find this repository helpful, please consider citing:
```
@misc{lu2025vlarl,
title={VLA-RL: Towards Masterful and General Robotic Manipulation with Scalable Reinforcement Learning},
author={Guanxing Lu, Chubin Zhang, Haonan Jiang, Yuheng Zhou, Zifeng Gao, Yansong Tang and Ziwei Wang},
year={2025},
howpublished={\url{https://congruous-farmhouse-8db.notion.site/VLA-RL-Towards-Masterful-and-General-Robotic-Manipulation-with-Scalable-Reinforcement-Learning-1953a2cd706280ecaad4e93a5bd2b8e3?pvs=4}},
note={Notion Blog}
}
```
Excerpt of 2,604 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:dfea19be2d3f0d0c, llm:description: 'Single-file implementation to advance vision-language-action (VLA) models with reinforcement learning.' language: Python
matched fp:dfea19be2d3f0d0c, llm:description: 'Single-file implementation to advance vision-language-action (VLA) models with reinforcement learning.' language: Python
matched fp:dfea19be2d3f0d0c, llm:description: 'Single-file implementation to advance vision-language-action (VLA) models with reinforcement learning.' language: Python
matched fp:dfea19be2d3f0d0c, llm:description: 'Single-file implementation to advance vision-language-action (VLA) models with reinforcement learning.' language: Python