def METHOD_NAME(input_features, output_features, data_csv, **kwargs):
    config = {
        "input_features": input_features,
        "output_features": output_features,
        "combiner": {"type": "concat", "output_size": 14},
        TRAINER: {"epochs": 2, BATCH_SIZE: 128},
    }
    model = LudwigModel(config)
    _, _, output_dir = model.train(dataset=data_csv, **kwargs)
    return model, output_dir