| library_name: pimm | |
| tags: | |
| - particle-physics | |
| - lartpc | |
| - point-cloud | |
| # Panda — semantic segmentation | |
| 5-class LArTPC semantic segmentation: PTv3 encoder–decoder + linear per-point head. | |
| - **pimm type:** `DefaultSegmentorV2` · 5 classes | |
| ## Loading | |
| ```python | |
| import pimm | |
| model = pimm.from_pretrained("hf://deeplearnphysics/panda-semantic") | |
| ``` | |
| Architecture + hyper-parameters travel in `config.json`, so no config file is | |
| needed. Weights are bitwise-identical to the original checkpoint. | |
| ## Provenance | |
| Repackaged from the original [`panda`](https://github.com/DeepLearnPhysics/panda) checkpoints into the [`pimm`](https://github.com/youngsm/particle-imaging-models) export format. Inherits the source repo's license. | |