Update app.py

app.py

@@ -19,21 +19,21 @@ def fill_the_mask(text):
         #First sort the list of dictionaries according to the score
         model_out = sorted(model_out, key=lambda x: x['score'],reverse=True)
     
-        #Create a list to store the model output
-        out_list = []
+        #Create a dictionary to store the model output
+        out_dict = {}
     
         #Iterate over the list of dictionaries and get the required ouput
         for sub_dict in model_out:
-            out_list.append(sub_dict["sequence"])
+            out_dict[sub_dict["sequence"]] = round(sub_dict["score"], 3)
             
-        return out_list
+        return out_dict
 
 #Create a Gradio user interface
 my_interface = gr.Interface(title="Masked Language Model APP\n(by Umair Akram)", 
              description="This App uses a fine-tuned DistilBERT-Base-Uncased Masked Language Model to predict the missed word in a sentence.\nEnter your text and put \"[MASK]\" at the word which you want to predict, as shown in the following example: Can we [MASK] to Paris?",
              fn=fill_the_mask, 
              inputs="text",
-             outputs="text")    
+             outputs="label")    
 
 #Define the main function
 if __name__ == "__main__":