src/transformers/pipelines/text2text_generation.py/Text2TextGenerationPipeline/postprocess
class Text2TextGenerationPipeline:    def postprocess(self, model_outputs, return_type=ReturnType.TEXT, clean_up_tokenization_spaces=False):
        records = []
        for output_ids in model_outputs["output_ids"][0]:
            if return_type == ReturnType.TENSORS:
                record = {f"{self.return_name}_token_ids": output_ids}
            elif return_type == ReturnType.TEXT:
                record = {
                    f"{self.return_name}_text": self.tokenizer.decode(
                        output_ids,
                        skip_special_tokens=True,
                        clean_up_tokenization_spaces=clean_up_tokenization_spaces,
                    )
                }
            records.append(record)
        return records