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license: mit
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<img src="https://raw.githubusercontent.com/zjunlp/LabVLA/main/assets/logo/labvla-symbol.png" width="88" alt="LabVLA symbol" /><img src="https://raw.githubusercontent.com/zjunlp/LabVLA/main/assets/logo/labvla-wordmark.png" height="56" alt="LabVLA" />
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<h3 align="center"> Grounding Vision–Language–Action Models in Scientific Laboratories </h3>
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<a href="https://huggingface.co/papers/2606.13578">📰HF Paper</a> •
<a href="https://zjunlp.github.io/LabVLA/">🔥Project Page</a> •
<a href="https://github.com/zjunlp/LabVLA">💻GitHub Repo</a> •
<a href="https://huggingface.co/zjunlp/LabVLA">🤗Model</a>
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## Model Description
**LabVLA** is the first vision–language–action (VLA) model designed for scientific laboratory environments. It combines a **Qwen3-VL-4B-Instruct** vision–language backbone with a **DiT flow-matching action expert**, trained with the π0.5 recipe to enable real-time robot control in lab settings.
## How to Use
### Download
```bash
huggingface-cli download zjunlp/LabVLA --local-dir LabVLA
```
### Deployment
Serve the model over the OpenPI msgpack WebSocket protocol:
```bash
git clone https://github.com/zjunlp/LabVLA.git
cd LabVLA
bash deployment/deploy.sh
```
For training, data preparation, and more details, please refer to our [GitHub repository](https://github.com/zjunlp/LabVLA).
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