def METHOD_NAME():
    download_dir = "./"
    train_df, tune_df = shopee_dataset(download_dir=download_dir)
    predictor = MultiModalPredictor(label="label")
    hyperparameters = [
        "model.names=[timm_image]",
        "model.timm_image.checkpoint_name=ghostnet_100",
        "env.num_workers=0",
        "env.num_workers_evaluation=0",
        "optimization.top_k_average_method=best",
        "optimization.val_check_interval=1.0",
    ]
    predictor.fit(
        train_data=train_df,
        tuning_data=tune_df,
        hyperparameters=hyperparameters,
        time_limit=2,
    )