cosmos-policy
nielsr HF Staff commited on
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1 Parent(s): c50ead9

Add robotics pipeline tag and license metadata

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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 metadata on the Hub:
- Added `pipeline_tag: robotics` so users can find this model when filtering by task.
- Added `license: other` to represent the custom NVIDIA One-Way Noncommercial License mentioned in the documentation.
- Added the BibTeX citation for the Cosmos Policy paper.

These changes help researchers and developers discover and cite your work more easily!

Files changed (1) hide show
  1. README.md +14 -4
README.md CHANGED
@@ -1,9 +1,12 @@
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  ---
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- datasets:
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- - nvidia/ALOHA-Cosmos-Policy
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  base_model:
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  - nvidia/Cosmos-Predict2-2B-Video2World
 
 
 
 
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  ---
 
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  # **Cosmos-Policy-ALOHA-Predict2-2B**
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  [**Cosmos Policy**](https://huggingface.co/collections/nvidia/cosmos-policy) | [**Code**](http://github.com/NVlabs/cosmos-policy) | [**White Paper**](https://arxiv.org/abs/2601.16163) | [**Website**](https://research.nvidia.com/labs/dir/cosmos-policy/)
@@ -258,11 +261,18 @@ Please report security vulnerabilities or NVIDIA AI Concerns [here](https://www.
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  - **Base Model**: [Cosmos-Predict2-2B-Video2World](https://huggingface.co/nvidia/Cosmos-Predict2-2B-Video2World)
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  - **Training Dataset**: [ALOHA-Cosmos-Policy](https://huggingface.co/datasets/nvidia/ALOHA-Cosmos-Policy)
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  - **Planning Model Checkpoint**: [Cosmos-Policy-ALOHA-Planning-Model-Predict2-2B](https://huggingface.co/nvidia/Cosmos-Policy-ALOHA-Planning-Model-Predict2-2B)
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- - **Paper**: https://arxiv.org/abs/2601.16163
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  - **Original ALOHA**: [Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware](https://arxiv.org/abs/2304.13705)
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  ## Citation
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  If you use this model, please cite the Cosmos Policy paper:
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- (Cosmos Policy BibTeX citation coming soon!)
 
 
 
 
 
 
 
 
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  ---
 
 
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  base_model:
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  - nvidia/Cosmos-Predict2-2B-Video2World
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+ datasets:
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+ - nvidia/ALOHA-Cosmos-Policy
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+ license: other
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+ pipeline_tag: robotics
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  ---
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+
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  # **Cosmos-Policy-ALOHA-Predict2-2B**
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  [**Cosmos Policy**](https://huggingface.co/collections/nvidia/cosmos-policy) | [**Code**](http://github.com/NVlabs/cosmos-policy) | [**White Paper**](https://arxiv.org/abs/2601.16163) | [**Website**](https://research.nvidia.com/labs/dir/cosmos-policy/)
 
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  - **Base Model**: [Cosmos-Predict2-2B-Video2World](https://huggingface.co/nvidia/Cosmos-Predict2-2B-Video2World)
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  - **Training Dataset**: [ALOHA-Cosmos-Policy](https://huggingface.co/datasets/nvidia/ALOHA-Cosmos-Policy)
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  - **Planning Model Checkpoint**: [Cosmos-Policy-ALOHA-Planning-Model-Predict2-2B](https://huggingface.co/nvidia/Cosmos-Policy-ALOHA-Planning-Model-Predict2-2B)
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+ - **Paper**: [Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning](https://arxiv.org/abs/2601.16163)
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  - **Original ALOHA**: [Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware](https://arxiv.org/abs/2304.13705)
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  ## Citation
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  If you use this model, please cite the Cosmos Policy paper:
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+ ```bibtex
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+ @article{kim2026cosmos,
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+ title={Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning},
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+ author={Kim, Moo Jin and Gao, Yihuai and Lin, Tsung-Yi and Lin, Yen-Chen and Ge, Yunhao and Lam, Grace and Liang, Percy and Song, Shuran and Liu, Ming-Yu and Finn, Chelsea and Gu, Jinwei},
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+ journal={arXiv preprint arXiv:2601.16163},
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+ year={2026}
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+ }
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+ ```