facebookresearch/mae

Health v2 · maintenance only

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Adoption not part of the score

8370 stars · 1348 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A PyTorch/GPU re-implementation of the Masked Autoencoders (MAE) paper for self-supervised vision learning. It includes pre-training code, fine-tuning code, pre-trained ViT checkpoints, and a visualization demo.

Use cases

• pretrain vision transformers with masked autoencoding
• fine-tune MAE checkpoints on ImageNet classification
• reproduce the MAE paper results in PyTorch
• visualize masked image reconstruction
• use self-supervised pretraining for downstream vision tasks

When to choose

• you want to pretrain or fine-tune ViT models with MAE in PyTorch
• you need official pre-trained MAE checkpoints
• you are studying or reproducing self-supervised vision research

When to avoid

• you need a maintained production library with regular updates
• you want a general-purpose computer vision toolkit rather than MAE specifically
• you cannot use PyTorch or GPU resources

Facets

library · maturity maintenance

machine-learning deep-learning image-processing computer-vision deep-learning machine-learning python pytorch self-supervised-learning masked-autoencoder vision-transformer pretrained-models research-code gpu linux

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