def METHOD_NAME(config_file: str,
                      checkpoint_file: str,
                      output_folder: str,
                      model_name: str,
                      model_version: str = '1.0',
                      force: bool = False):
    """Converts MMPose model (config + checkpoint) to TorchServe `.mar`.
    Args:
        config_file:
            In MMPose config format.
            The contents vary for each task repository.
        checkpoint_file:
            In MMPose checkpoint format.
            The contents vary for each task repository.
        output_folder:
            Folder where `{model_name}.mar` will be created.
            The file created will be in TorchServe archive format.
        model_name:
            If not None, used for naming the `{model_name}.mar` file
            that will be created under `output_folder`.
            If None, `{Path(checkpoint_file).stem}` will be used.
        model_version:
            Model's version.
        force:
            If True, if there is an existing `{model_name}.mar`
            file under `output_folder` it will be overwritten.
    """
    mmcv.mkdir_or_exist(output_folder)
    config = mmcv.Config.fromfile(config_file)
    with TemporaryDirectory() as tmpdir:
        model_file = osp.join(tmpdir, 'config.py')
        config.dump(model_file)
        handler_path = osp.join(osp.dirname(__file__), 'mmpose_handler.py')
        model_name = model_name or osp.splitext(
            osp.basename(checkpoint_file))[0]
        # use mmcv CheckpointLoader if checkpoint is not from a local file
        if not osp.isfile(checkpoint_file):
            ckpt = CheckpointLoader.load_checkpoint(checkpoint_file)
            checkpoint_file = osp.join(tmpdir, 'checkpoint.pth')
            with open(checkpoint_file, 'wb') as f:
                torch.save(ckpt, f)
        args = Namespace(
            **{
                'model_file': model_file,
                'serialized_file': checkpoint_file,
                'handler': handler_path,
                'model_name': model_name,
                'version': model_version,
                'export_path': output_folder,
                'force': force,
                'requirements_file': None,
                'extra_files': None,
                'runtime': 'python',
                'archive_format': 'default'
            })
        manifest = ModelExportUtils.generate_manifest_json(args)
        package_model(args, manifest)