locuslab/convmixer

Health v2 · maintenance only

Adoption not part of the score

1084 stars · 98 forks observed · 2026-08-28

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

An official PyTorch implementation of ConvMixer, a patch-based convolutional image classification architecture from the ICLR 2022 paper 'Patches Are All You Need?'. It includes model definitions, pretrained ImageNet weights, and training/evaluation scripts built on the timm framework.

Use cases

• train a ConvMixer model on ImageNet
• evaluate pretrained ConvMixer checkpoints on ImageNet validation
• use ConvMixer as a backbone in timm
• reproduce results from the Patches Are All You Need paper
• train ConvMixer on CIFAR-10
• compare patch-based convnets against vision transformers

When to choose

• you want a simple patch-based convolutional architecture for image classification
• you need pretrained ConvMixer weights for ImageNet experiments
• you use timm and want ConvMixer models integrated
• you are researching alternatives to vision transformers

When to avoid

• you need a general-purpose production computer-vision pipeline
• you want actively developed state-of-the-art architectures
• you need non-PyTorch frameworks like TensorFlow or JAX

Facets

library · maturity maintenance

machine-learning deep-learning image-processing deep-learning computer-vision image-processing python convmixer pytorch timm image-classification convolutional-networks research-code pretrained-weights gpu

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markdown · JSON · MCP: product_card(name="locuslab/convmixer")