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| license: mit |
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| <div align="center"> |
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| <p align="center"> |
| <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" /> |
| </p> |
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| <h3 align="center"> Grounding Vision–Language–Action Models in Scientific Laboratories </h3> |
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| <p align="center"> |
| <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> |
| </p> |
| </div> |
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| --- |
|
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| ## Model Description |
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| **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. |
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| ## How to Use |
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| ### Download |
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| ```bash |
| huggingface-cli download zjunlp/LabVLA --local-dir LabVLA |
| ``` |
|
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| ### Deployment |
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| Serve the model over the OpenPI msgpack WebSocket protocol: |
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| ```bash |
| git clone https://github.com/zjunlp/LabVLA.git |
| cd LabVLA |
| bash deployment/deploy.sh |
| ``` |
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| For training, data preparation, and more details, please refer to our [GitHub repository](https://github.com/zjunlp/LabVLA). |
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