Add robotics pipeline tag and license metadata
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by
nielsr
HF Staff
- opened
README.md
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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/)
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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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---
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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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# **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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```
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