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
File size: 795 Bytes
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library_name: lerobot
license: apache-2.0
model_name: vls_calvin_dp_base
pipeline_tag: robotics
tags:
- diffusion
- lerobot
- robotics
---
# vls_calvin_dp_base
A Diffusion Policy checkpoint trained on the CALVIN benchmark, released as the
frozen base policy used in **VLS: Steering Pretrained Robot Policies via
Vision-Language Models**.
VLS is a training-free, inference-time framework that steers the sampling
process of a frozen generative robot policy (such as this checkpoint) using
trajectory-differentiable rewards synthesized by a vision-language model — no
fine-tuning or weight updates required.
- Paper: <https://arxiv.org/abs/2602.03973>
- Project page: <https://vision-language-steering.github.io/webpage/>
- Trained with [LeRobot](https://github.com/huggingface/lerobot). |