I contributed this collection containing 6 different ConvMixer models that were pre-trained on the ImageNet-1K dataset available for fine-tuning as well as image classification. Further, the models are also accompanied with a tutorial to help you get started in <5 minutes.
ConvMixer is a simple model that uses only standard convolutions to achieve the mixing steps. Despite its simplicity, ConvMixer outperforms ViT and MLP-Mixer. ConvMixer relies directly on patches as input, separates the mixing of spatial and channel dimensions and maintains equal size and resolution throughout the network.
https://tfhub.dev/rishit-dagli/collections/convmixer 8
The associated GitHub repo could be found here:

  
      

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GitHub - Rishit-dagli/ConvMixer-torch2tf: This repository hosts code for... 7


  This repository hosts code for converting the original ConvMixer models (PyTorch) to TensorFlow. - GitHub - Rishit-dagli/ConvMixer-torch2tf: This repository hosts code for converting the original C...

  

  
    
    
  

  


You might want to take a look at a ConvMixer implementation by @Sayak_Paul here 2 and by @sayannath235 here 3.