Update app.py

app.py

@@ -153,7 +153,9 @@ def main():
                answer = tokenizer.convert_tokens_to_string(tokenizer.convert_ids_to_tokens(input_ids[answer_start:answer_end]))
 
                all_results.loc[i] = answer, max(outputs.start_logits.numpy()[0]), 0, 0
-               result=all_results.sort_values(by=['score'], ascending=False, inplace=True).head(1)
+
+               st.write(all_results)
+               #result=all_results.sort_values(by=['score'], ascending=False, inplace=True).head(1)
                
                #outputs = qa_model(input_ids=inputs['input_ids'], attention_mask=inputs['attention_mask'])
                
@@ -178,11 +180,11 @@ def main():
                #predict_answer_tokens = inputs.input_ids[0, answer_start_index : answer_end_index + 1] 
                #answer=tokenizer.decode(predict_answer_tokens) 
                
-               if (len(result['answer'])>0):    
-                   cantidad_respuestas = cantidad_respuestas + 1
-                   df_answer.loc[i, "answer"] = result.loc['answer']
-                   df_answer.loc[i, "score"]= result.loc['score']
-                   lista_noticias_respuestas.append(df_answer.loc[i].to_frame().T)
+               #if (len(result['answer'])>0):    
+                #   cantidad_respuestas = cantidad_respuestas + 1
+                 #  df_answer.loc[i, "answer"] = result.loc['answer']
+                  # df_answer.loc[i, "score"]= result.loc['score']
+                   #lista_noticias_respuestas.append(df_answer.loc[i].to_frame().T)
                 
                # Barra de progreso
                if (usar_barra_progreso==1):