Robotics
Transformers
Safetensors
internvl_chat
feature-extraction
vision-language-model
manipulation
custom_code
Instructions to use InternRobotics/VLAC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use InternRobotics/VLAC with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("InternRobotics/VLAC", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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# VLAC: A Vision-Language-Action-Critic Model for Robotic Real-World Reinforcement Learning
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<div align="center">
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[[paper]](https://arxiv.org/abs/2509.15937)
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[[code]](https://github.com/InternRobotics/VLAC)
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[[model]](https://huggingface.co/InternRobotics/VLAC)
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If you find our work helpful, please cite:
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```bibtex
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@article{zhai2025vision,
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title={A vision-language-action-critic model for robotic real-world reinforcement learning},
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# VLAC: A Vision-Language-Action-Critic Model for Robotic Real-World Reinforcement Learning
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<div align="center">
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[[ICML2026]](https://openreview.net/pdf?id=i7mfaYYLDf)
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[[paper]](https://arxiv.org/abs/2509.15937)
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[[code]](https://github.com/InternRobotics/VLAC)
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[[model]](https://huggingface.co/InternRobotics/VLAC)
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If you find our work helpful, please cite:
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```bibtex
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@inproceedings{zhanggeneralist,
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title={A Generalist Pair-wise Progress Critic Model for Vision-Language-Action Robots},
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author={Zhang, Qi and Zhai, Shaopeng and Zhang, Shengzhe and Liu, Litao and Zhang, Tianyi and Huang, Fuxian and Zhou, Ming},
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booktitle={Forty-third International Conference on Machine Learning}
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}
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```
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```bibtex
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@article{zhai2025vision,
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title={A vision-language-action-critic model for robotic real-world reinforcement learning},
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