Robotics
Transformers
Safetensors
English
qwen2_5_vl
image-text-to-text
RDT
rdt
RDT 2
Vision-Language-Action
Bimanual
Manipulation
Zero-shot
UMI
text-generation-inference
Instructions to use robotics-diffusion-transformer/RDT2-VQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use robotics-diffusion-transformer/RDT2-VQ with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("robotics-diffusion-transformer/RDT2-VQ") model = AutoModelForMultimodalLM.from_pretrained("robotics-diffusion-transformer/RDT2-VQ", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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## Citation
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```bibtex
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@
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year={2025}
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```
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## Citation
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```bibtex
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@article{liu2026rdt2,
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title={RDT2: Exploring the Scaling Limit of UMI Data Towards Zero-Shot Cross-Embodiment Generalization},
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author={Liu, Songming and Li, Bangguo and Ma, Kai and Wu, Lingxuan and Tan, Hengkai and Ouyang, Xiao and Su, Hang and Zhu, Jun},
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journal={arXiv preprint arXiv:2602.03310},
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year={2026}
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}
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```
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