jeonsworld/ViT-pytorch

Health v2 · maintenance only

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2162 stars · 397 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A PyTorch reimplementation of Google's Vision Transformer (ViT) for image classification, based on the paper 'An Image is Worth 16x16 Words'. It includes scripts to convert official checkpoints, fine-tune on datasets like CIFAR-10/100, and train with mixed precision.

Use cases

• fine-tune a vision transformer on cifar-10
• load pretrained ViT weights in pytorch
• train an image classifier with transformers
• convert google vit npz checkpoints to pytorch
• experiment with patch-based transformer models for images

When to choose

• you want a faithful PyTorch port of the original ViT with official pretrained weights
• you need a simple training script for image classification with transformers

When to avoid

• you need production-grade, actively maintained vision model tooling
• you want a broad model zoo beyond ViT variants

Facets

library · maturity maintenance

machine-learning deep-learning image-processing deep-learning computer-vision image-processing machine-learning python vision-transformer pytorch image-classification pretrained-models transformer gpu

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