| 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 | |