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, dtype="auto") - Notebooks
- Google Colab
- Kaggle
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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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<img src="https://github.com/InternRobotics/VLAC/tree/main/data/title_banner-2.gif" alt="VLAC banner" width="800"></img>
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</div> -->
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## VLAC-2B
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VLAC is a general-purpose pair-wise critic and manipulation model which designed for real world robot reinforcement learning and data refinement.
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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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[[model-8b]](https://huggingface.co/InternRobotics/VLAC-8b)
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</div>
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<img src="https://github.com/InternRobotics/VLAC/tree/main/data/title_banner-2.gif" alt="VLAC banner" width="800"></img>
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</div> -->
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## VLAC-8B is available now:
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[[model-8b]](https://huggingface.co/InternRobotics/VLAC-8b)
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## VLAC-2B
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VLAC is a general-purpose pair-wise critic and manipulation model which designed for real world robot reinforcement learning and data refinement.
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