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README.md
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@@ -25,7 +25,7 @@ Disclaimer: The team releasing RegNet did not write a model card for this model
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## Model description
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The authors trained [RegNets](https://huggingface.co/?models=regnet) models in a self-supervised fashion on
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![model image](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/regnet_architecture.png)
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>>> dataset = load_dataset("huggingface/cats-image")
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>>> image = dataset["test"]["image"][0]
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>>> feature_extractor = AutoFeatureExtractor.from_pretrained("
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>>> model = RegNetForImageClassification.from_pretrained("
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>>> inputs = feature_extractor(image, return_tensors="pt")
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'tabby, tabby cat'
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```
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For more code examples, we refer to the [documentation](https://huggingface.co/docs/transformers/master/en/model_doc/regnet).
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## Model description
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The authors trained [RegNets](https://huggingface.co/?models=regnet) models in a self-supervised fashion on a billion uncurated Instagram images. This model is later fine-tuned on ImageNet.
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![model image](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/regnet_architecture.png)
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>>> dataset = load_dataset("huggingface/cats-image")
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>>> image = dataset["test"]["image"][0]
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>>> feature_extractor = AutoFeatureExtractor.from_pretrained("facebook/regnet-y-320-seer-in1k")
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>>> model = RegNetForImageClassification.from_pretrained("facebook/regnet-y-320-seer-in1k")
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>>> inputs = feature_extractor(image, return_tensors="pt")
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'tabby, tabby cat'
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```
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For more code examples, we refer to the [documentation](https://huggingface.co/docs/transformers/master/en/model_doc/regnet).
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