Update app.py

app.py

@@ -134,16 +134,16 @@ def main():
                outputs = qa_model(input_ids=inputs['input_ids'], attention_mask=inputs['attention_mask'])
                answer_start_index = int(tf.math.argmax(outputs.start_logits, axis=-1)[0])
                answer_end_index = int(tf.math.argmax(outputs.end_logits, axis=-1)[0])
-               answer_start_scores = outputs.start_logits
-               answer_end_scores = outputs.end_logits
+               answer_start_scores = tf.nn.softmax(outputs.start_logits)
+               answer_end_scores = tf.nn.softmax(outputs.end_logits)
                predict_answer_tokens = inputs.input_ids[0, answer_start_index : answer_end_index + 1] 
                answer=tokenizer.decode(predict_answer_tokens) 
 
                if (len(answer)>0):
                    
                    # Extract 5 greatest values fo start and end scores with indeces
-                   #answer_start_scores= tf.math.top_k(answer_start_scores, k=5)
-                   #answer_end_scores= tf.math.top_k(answer_end_scores, k=5)
+                   answer_start_scores= tf.math.reduce_sum(answer_start_scores)
+                   answer_end_scores= tf.math.reduce_sum(answer_end_scores)
                    score = answer_start_scores[0]*answer_end_scores[0]
                    st.write(f'Aqui {answer}' )
                    st.write(score)