def METHOD_NAME(model_path, trainable=False):
    """Load a recommender model from the filesystem.
    Parameters
    ----------
    model_path: str, required
        Path to a file or directory where the model is stored. If a directory is
        provided, the latest model will be loaded.
    trainable: boolean, optional, default: False
        Set it to True if you would like to finetune the model. By default,
        the model parameters are assumed to be fixed after being loaded.
    Returns
    -------
    self : object
    """
    model = Recommender.METHOD_NAME(model_path, trainable)
    if hasattr(model, "pretrained"):  # NeuMF
        model.pretrained = False
    model._build_graph()
    model.saver.restore(model.sess, model.load_from.replace(".pkl", ".cpt"))
    return model