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PoLAr-MAE-Pretrain
DeepLearnPhysics/PoLAr-MAE-Pretrain
PoLAr-MAE-Pretrain is a machine learning model from DeepLearnPhysics. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for pimm.
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-s…
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At a glance
- Library
- pimm
- Access
- Public
- Created
- Jun 26, 2026
- Updated
- Jun 27, 2026
- SHA
- a85559df
Datasets
Model card
From the Hugging Face model README
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· archvit_small
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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.
- Library
- pimm
- Created
- Jun 26, 2026
- Updated
- Jun 27, 2026