adding code

app.py

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+from transformers import ViTConfig, ViTForImageClassification
+
+# option 1: load with randomly initialized weights (train from scratch)
+
+config = ViTConfig(num_hidden_layers=12, hidden_size=768)
+model = ViTForImageClassification(config)
+
+print(config)
+
+from transformers import ViTFeatureExtractor
+
+feature_extractor = ViTFeatureExtractor()
+
+# or, to load one that corresponds to a checkpoint on the hub:
+feature_extractor = ViTFeatureExtractor.from_pretrained("google/vit-base-patch16-224")
+
+from PIL import Image
+import requests
+
+url = 'http://images.cocodataset.org/val2017/000000039769.jpg'
+image = Image.open(requests.get(url, stream=True).raw)
+image.save("cats.png")
+image
+
+