c

app.py

@@ -33,18 +33,18 @@ def classify_sound(file_path):
         for idx, prob in zip(top5.indices, top5.values)
     ]
 
-    full_probs = {
-        model.config.id2label[i]: round(prob.item(), 4)
-        for i, prob in enumerate(probs)
-    }
-
-    return {
-        "Top 5 Predictions": dict(top5_labels),
-        "Sampling Rate": sr,
-        "Waveform Shape": str(original_shape),
-        "All Probabilities": full_probs
+    top20 = torch.topk(probs, k=20)
+    top20_probs = {
+        model.config.id2label[idx.item()]: round(prob.item(), 4)
+        for idx, prob in zip(top20.indices, top20.values)
     }
 
+    return (
+        dict(top5_labels),             
+        str(sr),                      
+        str(original_shape),         
+        top20_probs                 
+    )
 
 demo = gr.Interface(
     fn=classify_sound,