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README.md
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ConvNeXt V2 is a pure convolutional model (ConvNet) that introduces a fully convolutional masked autoencoder framework (FCMAE) and a new Global Response Normalization (GRN) layer to ConvNeXt. ConvNeXt V2 significantly improves the performance of pure ConvNets on various recognition benchmarks.
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![model image](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/
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## Intended uses & limitations
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You can use the raw model for image classification. See the [model hub](https://huggingface.co/models?search=
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fine-tuned versions on a task that interests you.
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### How to use
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ConvNeXt V2 is a pure convolutional model (ConvNet) that introduces a fully convolutional masked autoencoder framework (FCMAE) and a new Global Response Normalization (GRN) layer to ConvNeXt. ConvNeXt V2 significantly improves the performance of pure ConvNets on various recognition benchmarks.
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![model image](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/convnextv2_architecture.png)
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## Intended uses & limitations
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You can use the raw model for image classification. See the [model hub](https://huggingface.co/models?search=convnextv2) to look for
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fine-tuned versions on a task that interests you.
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### How to use
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