def METHOD_NAME(
    model_name: str,
    pretrained: bool,
    **kwargs,
):
    model, pl_model = FACE_DETECTION_BACKBONES.get(model_name)(pretrained=pretrained, **kwargs)
    # following steps are required since `get_model` needs to return `torch.nn.Module`
    # moving some required parameters from `fastface.FaceDetector` to `torch.nn.Module`
    # set input_transform params
    model.register_buffer("normalizer", getattr(pl_model, "normalizer"))
    model.register_buffer("mean", getattr(pl_model, "mean"))
    model.register_buffer("std", getattr(pl_model, "std"))
    # copy pasting `_postprocess` function from `fastface.FaceDetector` to `torch.nn.Module`
    # set output_transform function
    # this is called from FaceDetector lightning module form fastface itself
    # https://github.com/borhanMorphy/fastface/blob/master/fastface/module.py#L200
    setattr(model, "_postprocess", getattr(pl_model, "_postprocess"))
    return model