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@@ -33,6 +33,23 @@ It achieves the following results on the evaluation set:
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  - Loss: 0.0369
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  - Accuracy: 0.9883
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  ## Model description
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  More information needed
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  - Loss: 0.0369
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  - Accuracy: 0.9883
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+ ## how to use
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+ ```python
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+ from transformers import ViTFeatureExtractor, ViTModel
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+ from PIL import Image
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+ import requests
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+
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+ url = 'http://images.cocodataset.org/val2017/000000039769.jpg'
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+ image = Image.open(requests.get(url, stream=True).raw)
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+
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+ feature_extractor = ViTFeatureExtractor.from_pretrained('google/vit-base-patch16-224-in21k')
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+ model = ViTModel.from_pretrained('akahana/vit-base-cats-vs-dogs')
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+ inputs = feature_extractor(images=image, return_tensors="pt")
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+
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+ outputs = model(**inputs)
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+ last_hidden_states = outputs.last_hidden_state
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+ ```
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+
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  ## Model description
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  More information needed