Download and prepare the dataset as Arrow files that can be loaded as a Dataset using `builder.as_dataset()`:

        ```py
        >>> from datasets import load_dataset_builder
        >>> builder = load_dataset_builder("rotten_tomatoes")
        >>> builder.download_and_prepare()
        ```

        Download and prepare the dataset as sharded Parquet files locally:

        ```py
        >>> from datasets import load_dataset_builder
        >>> builder = load_dataset_builder("rotten_tomatoes")
        >>> builder.download_and_prepare("./output_dir", file_format="parquet")
        ```

        Download and prepare the dataset as sharded Parquet files in a cloud storage: