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@@ -24,11 +24,11 @@ Disclaimer: The team releasing ConvNeXT V2 did not write a model card for this m
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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/convnext_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=convnext) 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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  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