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View details ↗A ConvNeXt 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): 197.8 - GMACs: 34.4 - Activations (M): 43.1 - Image size: train = 224 x 224, test = 288 x 288 - **Papers:** - A ConvNet for the 2020s: https://arxiv.org/abs/2201.03545 - **Original:** https://github.com/facebookresearch/ConvNeXt - **Dataset:** ImageNet-1k - **Pretrain Dataset:** ImageNet-22k Explore the dataset and runtime metrics of this model in timm model results.
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View details ↗A ConvNeXt 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): 197.8 - GMACs: 101.1 - Activations (M): 126.7 - Image size: 384 x 384 - **Papers:** - A ConvNet for the 2020s: https://arxiv.org/abs/2201.03545 - **Original:** https://github.com/facebookresearch/ConvNeXt - **Dataset:** ImageNet-1k - **Pretrain Dataset:** ImageNet-22k Explore the dataset and runtime metrics of this model in timm model results.
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View details ↗A ConvNeXt image classification model. CLIP image tower weights pretrained in OpenCLIP on LAION and fine-tuned on ImageNet-12k followed by ImageNet-1k in `timm` bby Ross Wightman. Please see related OpenCLIP model cards for more details on pretrain: * https://huggingface.co/laion/CLIP-convnext_xxlarge-laion2B-s34B-b82K-augreg-soup * https://huggingface.co/laion/CLIP-convnext_large_d.laion2B-s26B-b102K-augreg * https://huggingface.co/laion/CLIP-convnext_base_w-laion2B-s13B-b82K-augreg * https://huggingface.co/laion/CLIP-convnext_base_w_320-laion_aesthetic-s13B-b82K
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View details ↗A ConvNeXt image classification model. CLIP image tower weights pretrained in OpenCLIP on LAION and fine-tuned on ImageNet-12k followed by ImageNet-1k in `timm` bby Ross Wightman. Please see related OpenCLIP model cards for more details on pretrain: * https://huggingface.co/laion/CLIP-convnext_xxlarge-laion2B-s34B-b82K-augreg-soup * https://huggingface.co/laion/CLIP-convnext_large_d.laion2B-s26B-b102K-augreg * https://huggingface.co/laion/CLIP-convnext_base_w-laion2B-s13B-b82K-augreg * https://huggingface.co/laion/CLIP-convnext_base_w_320-laion_aesthetic-s13B-b82K - **Model Type:** Image classification / feature backbone - **Model Stats:** - Params (M): 200.1 - GMACs: 101.1 - Activations (M): 126.7 - Image size: 384 x 384 - **Papers:** - LAION-5B: An open large-scale dataset for training next generation image-text models: https://arxiv.org/abs/2210.08402 - A ConvNet for the 2020s: https://arxiv.org/abs/2201.03545 - Learning Transferable Visual Models From Natural Language Supervision: https://arxiv.org/abs/2103.00020 - **Original:** https://github.com/mlfoundations/open_clip - **Pretrain Dataset:** LAION-2B - **Dataset:** ImageNet-1k
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View details ↗A ConvNeXt image classification model. Pretrained in `timm` on ImageNet-12k (a 11821 class subset of full ImageNet-22k) and fine-tuned on ImageNet-1k by Ross Wightman. ImageNet-12k training done on TPUs thanks to support of the TRC program. Fine-tuning performed on 8x GPU Lambda Labs cloud instances.
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View details ↗A ConvNeXt image classification model. Trained in `timm` on ImageNet-1k by Ross Wightman. - **Model Type:** Image classification / feature backbone - **Model Stats:** - Params (M): 9.0 - GMACs: 1.4 - Activations (M): 6.1 - Image size: train = 224 x 224, test = 288 x 288 - **Papers:** - A ConvNet for the 2020s: https://arxiv.org/abs/2201.03545 - **Original:** https://github.com/huggingface/pytorch-image-models - **Dataset:** ImageNet-1k Explore the dataset and runtime metrics of this model in timm model results.
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View details ↗A ConvNeXt image classification model. Pretrained on ImageNet-22k by paper authors. - **Model Type:** Image classification / feature backbone - **Model Stats:** - Params (M): 66.3 - GMACs: 8.7 - Activations (M): 21.6 - Image size: 224 x 224 - **Papers:** - A ConvNet for the 2020s: https://arxiv.org/abs/2201.03545 - **Original:** https://github.com/facebookresearch/ConvNeXt - **Dataset:** ImageNet-22k Explore the dataset and runtime metrics of this model in timm model results.
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View details ↗A ConvNeXt 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): 50.2 - GMACs: 8.7 - Activations (M): 21.6 - Image size: train = 224 x 224, test = 288 x 288 - **Papers:** - A ConvNet for the 2020s: https://arxiv.org/abs/2201.03545 - **Original:** https://github.com/facebookresearch/ConvNeXt - **Dataset:** ImageNet-1k - **Pretrain Dataset:** ImageNet-22k Explore the dataset and runtime metrics of this model in timm model results.
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View details ↗A ConvNeXt 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): 50.2 - GMACs: 25.6 - Activations (M): 63.4 - Image size: 384 x 384 - **Papers:** - A ConvNet for the 2020s: https://arxiv.org/abs/2201.03545 - **Original:** https://github.com/facebookresearch/ConvNeXt - **Dataset:** ImageNet-1k - **Pretrain Dataset:** ImageNet-22k Explore the dataset and runtime metrics of this model in timm model results.
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View details ↗A ConvNeXt image classification model. Pretrained in `timm` on ImageNet-12k (a 11821 class subset of full ImageNet-22k) and fine-tuned on ImageNet-1k by Ross Wightman. ImageNet-12k training done on TPUs thanks to support of the TRC program. Fine-tuning performed on 8x GPU Lambda Labs cloud instances.
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View details ↗A ConvNeXt image classification model. Pretrained in `timm` on ImageNet-12k (a 11821 class subset of full ImageNet-22k) and fine-tuned on ImageNet-1k by Ross Wightman.
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View details ↗A ConvNeXt image classification model. Pretrained on ImageNet-1k by paper authors. - **Model Type:** Image classification / feature backbone - **Model Stats:** - Params (M): 28.6 - GMACs: 4.5 - Activations (M): 13.4 - Image size: train = 224 x 224, test = 288 x 288 - **Papers:** - A ConvNet for the 2020s: https://arxiv.org/abs/2201.03545 - **Original:** https://github.com/facebookresearch/ConvNeXt - **Dataset:** ImageNet-1k Explore the dataset and runtime metrics of this model in timm model results.
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View details ↗A ConvNeXt image classification model. Pretrained on ImageNet-22k by paper authors. - **Model Type:** Image classification / feature backbone - **Model Stats:** - Params (M): 44.6 - GMACs: 4.5 - Activations (M): 13.5 - Image size: 224 x 224 - **Papers:** - A ConvNet for the 2020s: https://arxiv.org/abs/2201.03545 - **Original:** https://github.com/facebookresearch/ConvNeXt - **Dataset:** ImageNet-22k Explore the dataset and runtime metrics of this model in timm model results.
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