def METHOD_NAME(cls, **kwargs):
    """Instantiate the model.
    Args:
        kwargs: Input args.
                model_dir: The model dir used to load the checkpoint and the label information.
                num_labels: An optional arg to tell the model how many classes to initialize.
                                Method will call utils.parse_label_mapping if num_labels is not input.
                label2id: An optional label2id mapping, which will cover the label2id in configuration (if exists).
    Returns:
        The loaded model, which is initialized by transformers.PreTrainedModel.from_pretrained
    """
    model_dir = kwargs.pop('model_dir', None)
    cfg = kwargs.pop('cfg', None)
    model_args = parse_labels_in_order(model_dir, cfg, **kwargs)
    if model_dir is None:
        config = VecoConfig(**model_args)
        model = cls(config)
    else:
        model = super(Model, cls).from_pretrained(
            pretrained_model_name_or_path=model_dir, **model_args)
    return model