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A HGNet-V2 (High Performance GPU Net) image classification model. Trained by model authors on mined ImageNet-22k and ImageNet-1k using SSLD distillation and further fine-tuned on ImageNet-1k. Please see details at https://github.com/PaddlePaddle/PaddleClas/blob/develop/docs/zh_CN/models/ImageNet1k/PP-HGNetV2.md

Image classification
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A HGNet-V2 (High Performance GPU Net) image classification model. Trained by model authors on mined ImageNet-22k and ImageNet-1k using SSLD distillation. Please see details at https://github.com/PaddlePaddle/PaddleClas/blob/develop/docs/zh_CN/models/ImageNet1k/PP-HGNetV2.md

Image classification
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A HGNet-V2 (High Performance GPU Net) image classification model. Trained by model authors on mined ImageNet-22k and ImageNet-1k using SSLD distillation and further fine-tuned on ImageNet-1k. Please see details at https://github.com/PaddlePaddle/PaddleClas/blob/develop/docs/zh_CN/models/ImageNet1k/PP-HGNetV2.md

Image classification
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- **Model Type:** Image classification / feature backbone - **Model Stats:** - Params (M): 21.3 - GMACs: 4.3 - Activations (M): 16.3 - 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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