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Ross Wightman 5 years ago committed by GitHub
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@ -32,7 +32,7 @@ I've included a few of my favourite models, but this is not an exhaustive collec
* DPN (from [me](https://github.com/rwightman/pytorch-dpn-pretrained), weights hosted by Cadene) * DPN (from [me](https://github.com/rwightman/pytorch-dpn-pretrained), weights hosted by Cadene)
* DPN-68, DPN-68b, DPN-92, DPN-98, DPN-131, DPN-107 * DPN-68, DPN-68b, DPN-92, DPN-98, DPN-131, DPN-107
* Generic EfficientNet (from my standalone [GenMobileNet](https://github.com/rwightman/genmobilenet-pytorch)) - A generic model that implements many of the efficient models that utilize similar DepthwiseSeparable and InvertedResidual blocks * Generic EfficientNet (from my standalone [GenMobileNet](https://github.com/rwightman/genmobilenet-pytorch)) - A generic model that implements many of the efficient models that utilize similar DepthwiseSeparable and InvertedResidual blocks
* EfficientNet (B0-B5) (https://arxiv.org/abs/1905.11946) -- validated, compat with TF weights * EfficientNet (B0-B7) (https://arxiv.org/abs/1905.11946) -- validated, compat with TF weights
* MixNet (https://arxiv.org/abs/1907.09595) -- validated, compat with TF weights * MixNet (https://arxiv.org/abs/1907.09595) -- validated, compat with TF weights
* MNASNet B1, A1 (Squeeze-Excite), and Small (https://arxiv.org/abs/1807.11626) * MNASNet B1, A1 (Squeeze-Excite), and Small (https://arxiv.org/abs/1807.11626)
* MobileNet-V1 (https://arxiv.org/abs/1704.04861) * MobileNet-V1 (https://arxiv.org/abs/1704.04861)

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