src/transformers/pipelines/table_question_answering.py/TableQuestionAnsweringPipeline/__init__
class TableQuestionAnsweringPipeline:    def __init__(self, args_parser=TableQuestionAnsweringArgumentHandler(), *args, **kwargs):
        super().__init__(*args, **kwargs)
        self._args_parser = args_parser

        self.check_model_type(
            dict(
                TF_MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING.items()
                + TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING.items()
            )
            if self.framework == "tf"
            else dict(
                MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING.items() + MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING.items()
            )
        )

        self.aggregate = bool(getattr(self.model.config, "aggregation_labels", None)) and bool(
            getattr(self.model.config, "num_aggregation_labels", None)
        )
        self.type = "tapas" if hasattr(self.model.config, "aggregation_labels") else None