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A SPNasNet image classification model. Trained on ImageNet-1k in `timm` using recipe template described below. Recipe details: * A simple RmsProp based recipe without RandAugment. Using RandomErasing, mixup, dropout, standard random-resize-crop augmentation. * RMSProp (TF 1.0 behaviour) optimizer, EMA weight averaging * Step (exponential decay w/ staircase) LR schedule with warmup
starnet_s1.in1k
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starnet_s2.in1k
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starnet_s4.in1k
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A Swin Transformer image classification model. Pretrained on ImageNet-22k and fine-tuned on ImageNet-1k by paper authors. - **Model Type:** Image classification / feature backbone - **Model Stats:** - Params (M): 87.9 - GMACs: 47.2 - Activations (M): 134.8 - Image size: 384 x 384 - **Papers:** - Swin Transformer: Hierarchical Vision Transformer using Shifted Windows: https://arxiv.org/abs/2103.14030 - **Original:** https://github.com/microsoft/Swin-Transformer - **Dataset:** ImageNet-1k - **Pretrain Dataset:** ImageNet-22k Explore the dataset and runtime metrics of this model in timm model results.
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A Swin Transformer image classification model. Pretrained on ImageNet-22k and fine-tuned on ImageNet-1k by paper authors. - **Model Type:** Image classification / feature backbone - **Model Stats:** - Params (M): 87.8 - GMACs: 15.5 - Activations (M): 36.6 - Image size: 224 x 224 - **Papers:** - Swin Transformer: Hierarchical Vision Transformer using Shifted Windows: https://arxiv.org/abs/2103.14030 - **Original:** https://github.com/microsoft/Swin-Transformer - **Dataset:** ImageNet-1k - **Pretrain Dataset:** ImageNet-22k Explore the dataset and runtime metrics of this model in timm model results.
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A Swin Transformer image classification model. Pretrained on ImageNet-22k and fine-tuned on ImageNet-1k by paper authors. - **Model Type:** Image classification / feature backbone - **Model Stats:** - Params (M): 196.7 - GMACs: 104.1 - Activations (M): 202.2 - Image size: 384 x 384 - **Papers:** - Swin Transformer: Hierarchical Vision Transformer using Shifted Windows: https://arxiv.org/abs/2103.14030 - **Original:** https://github.com/microsoft/Swin-Transformer - **Dataset:** ImageNet-1k - **Pretrain Dataset:** ImageNet-22k Explore the dataset and runtime metrics of this model in timm model results.
基础档案已收录,详细介绍后续补充。可先查看厂商、分类与来源。
A Swin Transformer image classification model. Pretrained on ImageNet-22k and fine-tuned on ImageNet-1k by paper authors.
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基础档案已收录,详细介绍后续补充。可先查看厂商、分类与来源。
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