Model card for maxvit nano rw 256.sw in1k A timm specific MaxViT image classification model. Trained in timm on ImageNet 1k by Ross Wightman. ImageNet 1k training done on TPUs thanks to support of the TRC program. Model Variants in maxxvit.py MaxxViT covers a number of related model architectures that share a common structure including: CoAtNet Combining MBConv (depthwise separable) convolutional blocks in early stages with self attention transformer blocks in later stages. MaxViT Uniform blocks across all stages, each containing a MBConv (depthwise separable) convolution block followed by two self attention blocks with different partitioning schemes (window followed by grid). CoAtNeXt A timm specific arch that uses ConvNeXt blocks in place of MBConv blocks in CoAtNet. All normalization layers are LayerNorm (no BatchNorm). MaxxViT A timm specific arch that uses ConvNeXt blocks in place of MBConv blocks in MaxViT. All normalization layers are LayerNorm (no BatchNorm). MaxxViT V2 A MaxxViT variation that removes the window block attention leaving only ConvNeXt blocks and grid attention w/ more width to compensate. Aside from the major variants listed above, there are more subtle chan…
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