src/transformers/pipelines/conversational.py/ConversationalPipeline/postprocess
class ConversationalPipeline:    def postprocess(self, model_outputs, clean_up_tokenization_spaces=True):
        output_ids = model_outputs["output_ids"]
        answer = self.tokenizer.decode(
            output_ids[0],
            skip_special_tokens=True,
            clean_up_tokenization_spaces=clean_up_tokenization_spaces,
        )
        conversation = model_outputs["conversation"]
        conversation.mark_processed()
        conversation.append_response(answer)
        return conversation