@classmethod
def _load_model(cls, entity_tag_specs: List[EntityTagSpec], label_data: RasaModelData, config: Dict[(Text, Any)], data_example: Dict[(Text, Dict[(Text, List[FeatureArray])])], model_path: Path, finetune_mode: bool=False) -> 'RasaModel':
    file_name = cls.__name__
    tf_model_file = (model_path / f'{file_name}.tf_model')
    label_key = (LABEL_KEY if config[INTENT_CLASSIFICATION] else None)
    label_sub_key = (LABEL_SUB_KEY if config[INTENT_CLASSIFICATION] else None)
    model_data_example = RasaModelData(label_key=label_key, label_sub_key=label_sub_key, data=data_example)
    model = cls._load_model_class(tf_model_file, model_data_example, label_data, entity_tag_specs, config, finetune_mode=finetune_mode)
    return model
@classmethod
def _load_model(cls, entity_tag_specs: List[EntityTagSpec], label_data: RasaModelData, config: Dict[(Text, Any)], data_example: Dict[(Text, Dict[(Text, List[FeatureArray])])], model_path: Path, finetune_mode: bool=False) -> 'RasaModel':
    file_name = cls.__name__
    tf_model_file = (model_path / f'{file_name}.tf_model')
    label_key = (LABEL_KEY if config[INTENT_CLASSIFICATION] else None)
    label_sub_key = (LABEL_SUB_KEY if config[INTENT_CLASSIFICATION] else None)
    model_data_example = RasaModelData(label_key=label_key, label_sub_key=label_sub_key, data=data_example)
    model = cls._load_model_class(tf_model_file, model_data_example, label_data, entity_tag_specs, config, finetune_mode=finetune_mode)
    return model