Create app.py

app.py

@@ -0,0 +1,17 @@
+# app.py
+import gradio as gr
+from transformers import pipeline
+
+clf = pipeline("image-classification", model="nateraw/food")  # example model
+
+def predict(img):
+    preds = clf(img)  # list of {label, score}
+    # return top 3 in format expected by gr.Label
+    return {p["label"]: float(p["score"]) for p in preds[:3]}
+
+demo = gr.Interface(fn=predict,
+                    inputs=gr.Image(type="pil"),
+                    outputs=gr.Label(num_top_classes=3),
+                    title="🍽️ Food detector")
+if __name__ == "__main__":
+    demo.launch()