Instructions to use TreeePlanter/vls_calvin_dp_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use TreeePlanter/vls_calvin_dp_base with LeRobot:
- Notebooks
- Google Colab
- Kaggle
Upload README.md with huggingface_hub
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README.md
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# vls_calvin_dp_base
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# vls_calvin_dp_base
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A Diffusion Policy checkpoint trained on the CALVIN benchmark, released as the
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frozen base policy used in **VLS: Steering Pretrained Robot Policies via
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Vision-Language Models**.
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VLS is a training-free, inference-time framework that steers the sampling
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process of a frozen generative robot policy (such as this checkpoint) using
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trajectory-differentiable rewards synthesized by a vision-language model — no
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fine-tuning or weight updates required.
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- Paper: <https://arxiv.org/abs/2602.03973>
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- Project page: <https://vision-language-steering.github.io/webpage/>
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- Trained with [LeRobot](https://github.com/huggingface/lerobot).
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