Update app.py

app.py

@@ -141,6 +141,16 @@ def main():
                answer_end_index = int(tf.math.argmax(outputs.end_logits, axis=-1)[0])
                #answer_start_scores = tf.nn.softmax(outputs.start_logits)
                #answer_end_scores = tf.nn.softmax(outputs.end_logits)
+               #######################
+               start_probabilities = tf.nn.softmax(start_logits, dim=-1)[0]
+               end_probabilities = tf.nn.softmax(end_logits, dim=-1)[0]
+               scores = start_probabilities[:, None] * end_probabilities[None, :]
+               scores = tf.experimental.numpy.triu(scores)
+               max_index = scores.argmax().item()
+               start_index = max_index // scores.shape[1]
+               end_index = max_index % scores.shape[1]
+               st.write(scores[start_index, end_index])
+               #######################
                predict_answer_tokens = inputs.input_ids[0, answer_start_index : answer_end_index + 1] 
                answer=tokenizer.decode(predict_answer_tokens) 
 
@@ -152,7 +162,7 @@ def main():
                    #score = answer_start_scores*answer_end_scores
                    #st.write(f'Aqui {answer_start_scores}' )
                    #st.write(answer_end_scores)
-                   st.write(outputs)
+
                    cantidad_respuestas = cantidad_respuestas + 1
                    df_answer.loc[i, "answer"] = answer
                    lista_noticias_respuestas.append(df_answer.loc[i].to_frame().T)