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Improve model card

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Hi! I'm Niels from the Hugging Face community science team. I've updated the model card to improve its visibility and documentation:
- Added the `robotics` pipeline tag to the metadata.
- Included links to the official GitHub repository, project page, and the research paper.
- Organized the content into clear sections for installation, usage, and citations.

This should help other researchers find and use your work more effectively!

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  1. README.md +22 -9
README.md CHANGED
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  ---
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  license: bsd-2-clause
 
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  ---
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- # Action Chunking with Transformers (ACT)
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- The model was trained with the [MujocoUR5eCable dataset](https://huggingface.co/datasets/RoboManipBaselines/MujocoUR5eCable).
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- ## Install
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- See [GitHub](https://github.com/isri-aist/RoboManipBaselines/blob/master/doc/install.md#ACT) for installation.
 
 
 
 
 
 
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  ## Policy rollout
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- Run a trained policy:
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  ```console
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- # Go to the top directory of this repository
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  $ cd robo_manip_baselines
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  $ python ./bin/Rollout.py Act MujocoUR5eCable --checkpoint ./checkpoint/Act/<checkpoint_name>/policy_last.ckpt
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  ```
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  ## Technical Details
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- For more information on the technical details, please see the following paper:
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  ```bib
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  @INPROCEEDINGS{ACT_RSS23,
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  author = {Tony Z. Zhao and Vikash Kumar and Sergey Levine and Chelsea Finn},
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  }
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  ```
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- ## RoboManipBaselines Paper
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- https://huggingface.co/papers/2509.17057
 
 
 
 
 
 
 
 
 
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  ---
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  license: bsd-2-clause
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+ pipeline_tag: robotics
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  ---
 
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+ # Action Chunking with Transformers (ACT) - MujocoUR5eCable
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+ This model is a part of the **RoboManipBaselines** framework. It implements the [Action Chunking with Transformers (ACT)](https://tonyzhaozh.github.io/act/) architecture and was trained on the [MujocoUR5eCable dataset](https://huggingface.co/datasets/RoboManipBaselines/MujocoUR5eCable).
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+ - **Paper:** [RoboManipBaselines: A Unified Framework for Imitation Learning in Robotic Manipulation across Real and Simulation Environments](https://huggingface.co/papers/2509.17057)
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+ - **Project Page:** [RoboManipBaselines Project Page](https://isri-aist.github.io/RoboManipBaselines-ProjectPage/)
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+ - **Repository:** [GitHub - isri-aist/RoboManipBaselines](https://github.com/isri-aist/RoboManipBaselines)
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+
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+ ## Installation
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+ See [GitHub](https://github.com/isri-aist/RoboManipBaselines/blob/master/doc/install.md#ACT) for installation instructions.
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  ## Policy rollout
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+ To run the trained policy, use the following command from the top directory of the repository:
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  ```console
 
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  $ cd robo_manip_baselines
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  $ python ./bin/Rollout.py Act MujocoUR5eCable --checkpoint ./checkpoint/Act/<checkpoint_name>/policy_last.ckpt
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  ```
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  ## Technical Details
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+ For more information on the technical details of the ACT architecture, please see the following paper:
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  ```bib
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  @INPROCEEDINGS{ACT_RSS23,
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  author = {Tony Z. Zhao and Vikash Kumar and Sergey Levine and Chelsea Finn},
 
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  }
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  ```
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+ ## Citation
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+ If you use RoboManipBaselines in your work, please cite the framework paper:
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+ ```bibtex
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+ @article{RoboManipBaselines_Murooka_2025,
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+ title={RoboManipBaselines: A Unified Framework for Imitation Learning in Robotic Manipulation across Real and Simulation Environments},
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+ author={Murooka, Masaki and Motoda, Tomohiro and Nakajo, Ryoichi and Oh, Hanbit and Makihara, Koshi and Shirai, Keisuke and Ogata, Tetsuya and Domae, Yukiyasu},
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+ journal={arXiv preprint arXiv:2509.17057},
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+ year={2025}
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+ }
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+ ```