Create app.py

app.py

@@ -0,0 +1,17 @@
+from fastapi import FastAPI, UploadFile
+from transformers import pipeline
+from PIL import Image
+import io
+import uvicorn
+
+app = FastAPI()
+pipe = pipeline("image-classification", model="google/vit-base-patch16-224")
+
+@app.post("/predict")
+async def predict(file: UploadFile):
+    img = Image.open(io.BytesIO(await file.read()))
+    preds = pipe(img)
+    return preds
+
+if __name__ == "__main__":
+    uvicorn.run(app, host="0.0.0.0", port=7860)