How to use the pooch.Unzip function in pooch

def fetch_bedmap2():
    downloader = pooch.HTTPDownloader(progressbar=True)
    filenames = bedmap2.fetch(
        'bedmap2_tiff.zip', processor=pooch.Unzip(), downloader=downloader
    )
    return [f for f in filenames if os.path.splitext(f)[1] == '.tif']

if zone not in ZONES:
            raise ValueError(
                "Passed zone '{}' is not a valid GRAV-D zone.".format(zone)
            )
        blocks = tuple(b for b in ZONES[zone])
    if block is not None:
        if block not in BLOCKS:
            raise ValueError(
                "Passed block '{}' is not a valid GRAV-D block.".format(block)
            )
        blocks = (block,)
    fnames = list(
        fname
        for b in blocks
        for fname in REGISTRY.fetch(
            "NGS_GRAVD_Block_{}_BETA1.zip".format(b), processor=Unzip()
        )
    )
    if not load:
        return fnames
    frames = [_load_block_file(b, fnames) for b in blocks]
    if len(frames) > 1:
        frame = pd.concat(frames, ignore_index=True)
    else:
        frame = frames[0]
    return frame

**kwargs
        Extra parameters passed to the :func:`xarray.open_rasterio` function.

    Returns
    -------
    grid : :class:`xarray.Dataset`
        The loaded Bedmap2 datasets.

    """
    if isinstance(datasets, str):
        datasets = [datasets]
    if not set(datasets).issubset(DATASETS.keys()):
        raise ValueError(
            "Invalid datasets: {}".format(set(datasets).difference(DATASETS.keys()))
        )
    fnames = REGISTRY.fetch("bedmap2_tiff.zip", processor=Unzip())
    if not load:
        return [get_fname(dataset, fnames) for dataset in datasets]
    arrays = []
    for dataset in datasets:
        array = xr.open_rasterio(get_fname(dataset, fnames), chunks=chunks, **kwargs)
        # Replace no data values with nans
        array = array.where(array != array.nodatavals)
        # Remove "band" dimension and coordinate
        array = array.squeeze("band", drop=True)
        array.name = dataset
        array.x.attrs["units"] = "meters"
        array.y.attrs["units"] = "meters"
        array.attrs["long_name"] = DATASETS[dataset]["name"]
        if "units" in DATASETS[dataset]:
            array.attrs["units"] = DATASETS[dataset]["units"]
        arrays.append(array)