Update app.py

app.py

@@ -15,7 +15,7 @@ def summarize(inputs):
     # with a max_length of 200, the model has a chance to encapsule lots of information
     preds = model.generate(**inputs,max_length=200,min_length=100)
     # we decode the predictions to store them
-    decoded_predictions = tokenizer.batch_decode(predictions, skip_special_tokens=True)
+    decoded_predictions = tokenizer.batch_decode(preds, skip_special_tokens=True)
   # each batches predictions are appended to the list   
   return decoded_predictions