README.md

metadata

library_name: pimm
datasets:
  - DeepLearnPhysics/PILArNet-M
tags:
  - particle-physics
  - lartpc
  - point-cloud

PoLAr-MAE — pretrained (self-supervised)

Full PoLAr-MAE masked-autoencoder pretrained on LArTPC (PILArNet) point clouds (masked point reconstruction + energy infilling): ViT-S encoder, MAE decoder, reconstruction heads. Use the encoder as a backbone / warm-start.

• pimm type: PoLAr-MAE · arch vit_small

Loading

import pimm
model = pimm.from_pretrained("hf://deeplearnphysics/polar-mae-pretrain")

Provenance

Repackaged from the original PoLAr-MAE release checkpoints into the pimm export format. Inherits the source repo license.