agibot-world
/

GO-1

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 library_name: transformers
-tags: []
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 ## Model Details
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 ---
 library_name: transformers
+datasets:
+- agibot-world/AgiBotWorld-Beta
+- agibot-world/AgiBotWorld-Alpha
 ---
+# GO-1
 <!-- Provide a quick summary of what the model is/does. -->
+GO-1 is our robotic foundation model pretrained on [AgiBot World Dataset](https://huggingface.co/datasets/agibot-world/AgiBotWorld-Beta).
+Please refer to our [project page](https://agibot-world.com/), [github repo](https://github.com/OpenDriveLab/Agibot-World) and [paper](https://arxiv.org/abs/2503.06669) for more details.
 ## Model Details
 <!-- Provide a longer summary of what this model is. -->
+- **Developed by:** Team AgiBot-World
+- **Model type:** Vision-Language-Action model
+- **License:** CC BY-NC-SA 4.0
+- **Vision Language Model:** [InternVL 2.5-2B](https://huggingface.co/OpenGVLab/InternVL2_5-2B)
+- **Pre-training Dataset:** [AgiBot World Dataset](https://huggingface.co/datasets/agibot-world/AgiBotWorld-Beta)
+### Model Sources
 <!-- Provide the basic links for the model. -->
+- **Repository:** https://github.com/OpenDriveLab/Agibot-World
+- **Paper:** https://arxiv.org/abs/2503.06669
+- **Project Page:** https://agibot-world.com/
 ## Uses
+This is the pre-trained GO-1 model. For fine-tuning on simulation benchmarks or your customized dataset, please visit our [github repo](https://github.com/OpenDriveLab/Agibot-World).
+## Citation
 <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+- Please consider citing our work if it helps your research.
+- For the full authorship and detailed contributions, please refer to [contributions](https://github.com/OpenDriveLab/AgiBot-World/blob/main/CONTRIBUTING.md).
+- In alphabetical order by surname:
+```BibTeX
+@article{bu2025agibot,
+  title={Agibot world colosseo: A large-scale manipulation platform for scalable and intelligent embodied systems},
+  author={Bu, Qingwen and Cai, Jisong and Chen, Li and Cui, Xiuqi and Ding, Yan and Feng, Siyuan and Gao, Shenyuan and He, Xindong and Huang, Xu and Jiang, Shu and others},
+  journal={arXiv preprint arXiv:2503.06669},
+  year={2025}
+}
+@inproceedings{bu2025agibot,
+  title={Agibot world colosseo: A large-scale manipulation platform for scalable and intelligent embodied systems},
+  author={Bu, Qingwen and Cai, Jisong and Chen, Li and Cui, Xiuqi and Ding, Yan and Feng, Siyuan and He, Xindong and Huang, Xu and others},
+  booktitle={2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
+  year={2025},
+  organization={IEEE}
+}
+```