Create app.py

app.py

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+from transformers import AutoImageProcessor, AutoModelForImageClassification
+from PIL import Image
+import torch
+import gradio as gr
+
+image_processor = AutoImageProcessor.from_pretrained("wesleyacheng/dog-breeds-multiclass-image-classification-with-vit")
+model = AutoModelForImageClassification.from_pretrained("wesleyacheng/dog-breeds-multiclass-image-classification-with-vit")
+
+def classify_dog(image):
+    inputs = image_processor(images=image, return_tensors="pt")
+    with torch.no_grad():
+        outputs = model(**inputs)
+    logits = outputs.logits
+    predicted_class_idx = logits.argmax(-1).item()
+    predicted_breed = model.config.id2label[predicted_class_idx]
+    return f"Predicted Dog Breed: {predicted_breed}"
+
+demo = gr.Interface(
+    fn=classify_dog,
+    inputs=gr.Image(type="pil"),
+    outputs="text",
+    title="Dog Breed Classifier",
+    description="Upload an image of a dog and the model will classify its breed (120 breeds supported)."
+)
+
+demo.launch()