now is completely finished

app.py

@@ -19,7 +19,7 @@ def classifier(image):
     logits = outputs.logits
     probabilities = torch.nn.functional.softmax(logits, dim=-1)
     predicted_class_idxs = probabilities.topk(5, dim=-1)[1].tolist()[0]
-    probabilities = probabilities.tolist()[0][:5]
+    probabilities = sorted(probabilities.tolist()[0],  reverse=True)[:5]
     classes = [model.config.id2label[idx] for idx in predicted_class_idxs]
     df = pd.DataFrame({'food':classes , 'posibility': probabilities})
     return df.to_html(index=False)