import numpy as np | |
from transformers import QuestionAnsweringPipeline | |
class DemoQAPipeline(QuestionAnsweringPipeline): | |
def postprocess(self, model_outputs): | |
# Format: {'score': 1.3321573119791374e-13, 'start': 70, 'end': 90, 'answer': 'Hopkins was featured'} | |
answers = super().postprocess(model_outputs) | |
return {'guess': answers['answer'], 'confidence': answers['score']} | |