Instructions to use zaleni/WSA-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use zaleni/WSA-Base with LeRobot:
- Notebooks
- Google Colab
- Kaggle
| pipeline_tag: robotics | |
| license: apache-2.0 | |
| # WSA: A 3D-Centric World-Spatial-Action Model for Generalizable Robot Control | |
| This repository contains the weights for **WSA-Base**, a 3D-centric World-Spatial-Action embodied foundation model for generalizable robot control. | |
| - **Paper:** [WSA$_1$: a 3D-Centric World-Spatial-Action Model for Generalizable Robot Control](https://huggingface.co/papers/2607.03941) | |
| - **Project Page:** [https://zaleni.github.io/WSA1/](https://zaleni.github.io/WSA1/) | |
| - **Repository:** [https://github.com/zaleni/WSA](https://github.com/zaleni/WSA) | |
| ## Overview | |
| WSA (World-Spatial-Action) is an embodied foundation model that unifies instruction-aligned 2D visual planning, action-conditioned 3D world modeling, and 3D-aware action generation into a shared latent space. WSA-Base utilizes a Qwen3-VL-2B backbone and is pre-trained on diverse datasets to enable data-efficient, generalizable robot manipulation. | |
| For details on how to set up the environment, run inference, or perform downstream fine-tuning, please refer to the [official GitHub repository](https://github.com/zaleni/WSA). |