def METHOD_NAME(self):
    model = Model.from_pretrained(self.model_id)
    self.tokenizer = BertTokenizer(
        os.path.join(model.model_dir, ModelFile.VOCAB_FILE))
    db = Database(
        tokenizer=self.tokenizer,
        table_file_path=[
            os.path.join(model.model_dir, 'databases', fname)
            for fname in os.listdir(
                os.path.join(model.model_dir, 'databases'))
        ],
        syn_dict_file_path=os.path.join(model.model_dir, 'synonym.txt'),
        is_use_sqlite=True)
    preprocessor = TableQuestionAnsweringPreprocessor(
        model_dir=model.model_dir, db=db)
    pipelines = [
        pipeline(
            Tasks.table_question_answering,
            model=model,
            preprocessor=preprocessor,
            db=db)
    ]
    tableqa_tracking_and_print_results_without_history(pipelines)