maybe a fix

app.py

@@ -40,18 +40,18 @@ def predict (Sentence, Word, LLM, Norm, Layer):
     pred_list = pred.detach().numpy().tolist()
 
     df = pd.DataFrame({'feature':labels, 'value':pred_list})
-    df = df.sort_values('value', ascending=False)
     df = df[df['value'] > 0]
-    
-    output = [df['feature'][i]+'\t\t\t\t\t\t\t'+str(df['value'][i]) for i in range(df.shape[0])]
-    return "All Positive Predicted Values:\n"+"\n".join(output)
+    df_sorted = df.sort_values(by='value', ascending=False)
+
+    output = [df_sorted['feature'][i]+'\t\t\t\t\t\t\t'+str(df_sorted['value'][i]) for i in range(df_sorted.shape[0])]
+    print("All Positive Predicted Values:\n"+"\n".join(output))
 
 demo = gr.Interface(
     fn=predict,
     inputs=[
         "text", 
         "text", 
-        gr.Radio(["BERT", "ALBERT"]),
+        gr.Radio(["BERT", "ALBERT", "roBERTa"]),
         gr.Radio(["Binder", "McRae", "Buchanan"]),
         gr.Slider(0,12, step=1)
     ],