bearpaw/pytorch-classification

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1738 stars · 555 forks observed · 2026-08-28

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

A PyTorch library providing a unified interface for training image classification models on CIFAR-10/100 and ImageNet. It includes implementations of popular architectures like ResNet, PreResNet, Wide ResNet, ResNeXt, and DenseNet, with pretrained models and training logs.

Use cases

• train a resnet on cifar-10
• benchmark wide residual networks on cifar-100
• train densenet on imagenet
• get pretrained classification models for pytorch
• compare image classification architectures
• reproduce resnext training results

When to choose

• you need a unified codebase to train and compare many CNN architectures on CIFAR or ImageNet
• you want reference accuracy numbers and pretrained checkpoints for classic vision models

When to avoid

• you need modern vision transformers or the latest architectures
• you want a maintained production inference library rather than research training code

Facets

library · maturity maintenance

machine-learning deep-learning machine-learning computer-vision image-processing python pytorch image-classification resnet densenet cifar10 cifar100 imagenet pretrained-models gpu

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