Robotics

Update model card with robotics metadata and project links

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by nielsr HF Staff - opened
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  1. README.md +36 -6
README.md CHANGED
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- license: apache-2.0
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  # PhysBrain-VLA
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  PhysBrain 1.0 β€” Physical Intelligence for Embodied General AI
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- [Open Source Plan](#open-source-plan) β€’ [Overview](#overview) β€’ [Key Technologies](#key-technologies) β€’ [Getting Started](#getting-started)
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  ---
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  Together, these three technologies form the PhysBrain 1.0 system: **PhysBrain** (base model) Γ— **TwinBrainVLA** (architecture) Γ— **LangForce** (training strategy) β€” achieving SOTA across multiple embodied intelligence benchmarks with exceptional data efficiency.
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  ## Citation
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  If you find PhysBrain useful in your research, please consider citing our work:
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  @misc{physbrain10technicalreport,
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  title={PhysBrain 1.0 Technical Report},
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- author={Shijie Lian and Bin Yu and Xiaopeng Lin and Changti Wu and Hang Yuan and Xiaolin Hu and Zhaolong Shen and Yuzhuo Miao and Haishan Liu and Yuxuan Tian and Yukun Shi and Cong Huang and Kai Chen},
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  year={2026},
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  eprint={2605.15298},
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  archivePrefix={arXiv},
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  ## License
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- This project is released under the [Apache 2.0 License](LICENSE).
 
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+ license: apache-2.0
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+ pipeline_tag: robotics
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+
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  # PhysBrain-VLA
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  PhysBrain 1.0 β€” Physical Intelligence for Embodied General AI
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+ [Paper](https://huggingface.co/papers/2605.15298) β€’ [Project Page](https://phys-brain.github.io/) β€’ [GitHub](https://github.com/Phys-Brain/PhysBrain-VLA)
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  ---
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  Together, these three technologies form the PhysBrain 1.0 system: **PhysBrain** (base model) Γ— **TwinBrainVLA** (architecture) Γ— **LangForce** (training strategy) β€” achieving SOTA across multiple embodied intelligence benchmarks with exceptional data efficiency.
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+ ## Open Source Plan
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+ All PhysBrain 1.0 VLA model checkpoints are now available. You can find the full collection at [πŸ€— Hugging Face](https://huggingface.co/collections/Phys-Brain/physbrain-10-vla).
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+ The current release status is as follows:
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+ | Component | Status |
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+ | ------------------------------------------------------ | ------------ |
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+ | PhysBrain 1.0 VLA (RoboCasa Fine-Tuned) | βœ… Available |
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+ | PhysBrain 1.0 VLA (LIBERO Fine-Tuned) | βœ… Available |
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+ | PhysBrain 1.0 VLA (SIMPLER WidowX Robot Fine-Tuned) | βœ… Available |
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+ | PhysBrain 1.0 VLA (SIMPLER Google Robot Fine-Tuned) | βœ… Available |
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+ | Inference Code | βœ… Available |
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+ ## Getting Started
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+ PhysBrain-VLA is built on top of the **starVLA** scaffold. To use it, follow these two steps:
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+ 1. **Copy the framework file** into your starVLA codebase:
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+ ```powershell
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+ cp physbrain_vla/PhysBrainVLA.py <path-to-starVLA>/starVLA/model/framework/
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+ ```
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+ 2. **Load and deploy** the model following the standard starVLA checkpoint loading workflow.
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+ For detailed starVLA setup and inference instructions, please refer to the starVLA repository.
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  ## Citation
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  If you find PhysBrain useful in your research, please consider citing our work:
 
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  @misc{physbrain10technicalreport,
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  title={PhysBrain 1.0 Technical Report},
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+ author={Shijie Lian and Bin Yu and Xiaopeng Lin and Changti Wu Author and Hang Yuan and Xiaolin Hu and Zhaolong Shen and Yuzhuo Miao and Haishan Liu and Yuxuan Tian and Yukun Shi and Cong Huang and Kai Chen},
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  year={2026},
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  eprint={2605.15298},
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  archivePrefix={arXiv},
 
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  ## License
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+ This project is released under the [Apache 2.0 License](LICENSE).