def download_tsv_files_and_extract(local_cache_path: str = ".") -> None:
    """Download and extract the dataset files in tsv format from NYU Jiant 
        downloads both original and tsv formatted data. 

    Args:
        local_cache_path (str [optional]) -- Directory to cache files to. Defaults to current working directory (default: {"."})
    
    Returns:
        None -- Nothing is returned
    """
    try:
        folder_name = "MNLI"
        file_name = f"{folder_name}.zip"
        maybe_download(URL_JIANT_MNLI_TSV, file_name, local_cache_path)
        if not os.path.exists(os.path.join(local_cache_path, folder_name)):
            extract_zip(os.path.join(local_cache_path, file_name), local_cache_path)

        # Clean up zip download
        if os.path.exists(os.path.join(local_cache_path, file_name)):
            os.remove(os.path.join(local_cache_path, file_name))
    except IOError as e:
        raise (e)
    print("Downloaded file to: ", os.path.join(local_cache_path, folder_name))
Download and extract the dataset files in tsv format from NYU Jiant 
        downloads both original and tsv formatted data. 

    Args:
        local_cache_path (str [optional]) -- Directory to cache files to. Defaults to current working directory (default: {"."})
    
    Returns:
        None -- Nothing is returned
    
utils_nlp/dataset/multinli.py