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- **Model Type:** Image classification / feature backbone - **Model Stats:** - Params (M): 41.2 - GMACs: 9.0 - Activations (M): 22.0 - Image size: 224 x 224 - **Papers:** - Deep High-Resolution Representation Learning for Visual Recognition: https://arxiv.org/abs/1908.07919 - **Original:** https://github.com/HRNet/HRNet-Image-Classification - **Dataset:** ImageNet-1k Explore the dataset and runtime metrics of this model in timm model results.

Image classification
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A Inception-ResNet-v2 image classification model. Trained on ImageNet-1k paper authors. Ported from Tensorflow via Cadene's pretrained-models.pytorch. - **Model Type:** Image classification / feature backbone - **Model Stats:** - Params (M): 55.8 - GMACs: 13.2 - Activations (M): 25.1 - Image size: 299 x 299 - **Papers:** - https://arxiv.org/abs/1602.07261: https://arxiv.org/abs/1602.07261 - **Original:** - https://github.com/tensorflow/models - https://github.com/Cadene/pretrained-models.pytorch - **Dataset:** ImageNet-1k Explore the dataset and runtime metrics of this model in timm model results.

Image classification
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A Inception-v3 image classification model. Trained on ImageNet-1k, torchvision weights. - **Model Type:** Image classification / feature backbone - **Model Stats:** - Params (M): 23.8 - GMACs: 5.7 - Activations (M): 9.0 - Image size: 299 x 299 - **Papers:** - Rethinking the Inception Architecture for Computer Vision: https://arxiv.org/abs/1512.00567 - **Original:** https://github.com/pytorch/vision - **Dataset:** ImageNet-1k Explore the dataset and runtime metrics of this model in timm model results.

Image classification
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A Inception-v4 image classification model. Trained on ImageNet-1k paper authors. Ported from Tensorflow via Cadene's pretrained-models.pytorch. - **Model Type:** Image classification / feature backbone - **Model Stats:** - Params (M): 42.7 - GMACs: 12.3 - Activations (M): 15.1 - Image size: 299 x 299 - **Papers:** - https://arxiv.org/abs/1602.07261: https://arxiv.org/abs/1602.07261 - **Original:** - https://github.com/tensorflow/models - https://github.com/Cadene/pretrained-models.pytorch - **Dataset:** ImageNet-1k Explore the dataset and runtime metrics of this model in timm model results.

Image classification
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A LCNet image classification model. Trained on ImageNet-1k in `timm` using recipe template described below. Recipe details: * RandAugment `RA2` recipe. Inspired by and evolved from EfficientNet RandAugment recipes. Published as `B` recipe in ResNet Strikes Back. * RMSProp (TF 1.0 behaviour) optimizer, EMA weight averaging * Step (exponential decay w/ staircase) LR schedule with warmup

Image classification
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