| --- |
| license: mit |
| library_name: pytorch |
| tags: |
| - robotics |
| - tactile-sensing |
| - multimodal |
| datasets: |
| - TUM-ICS/Hide-and-Seek |
| --- |
| |
| # HAS-Bench Baselines |
|
|
| Pretrained baseline checkpoints for the [Hide-and-Seek tactile dataset](https://huggingface.co/datasets/TUM-ICS/Hide-and-Seek): a dual-head multimodal classifier with an object head and a weight head, trained with the public release pipeline (seed 42). |
|
|
| | File | Modalities | |
| |---|---| |
| | `m123/best_model.pt` | tactile point cloud + raw skin signals + virtual skin wrenches | |
| | `m12345/best_model.pt` | + end-effector pose + wrist F/T | |
|
|
| Each directory also contains the `last_metrics.json` written at the end of training. |
|
|
| ## Usage |
|
|
| ```bash |
| hf download TUM-ICS/HAS-Bench-baselines --local-dir checkpoints |
| ``` |
|
|
| Dataloaders and evaluation scripts: https://github.com/TUM-ICS/Tactile-Hide-and-Seek |
|
|
