def METHOD_NAME(model: Module, checkpoint_path: Path, device=_DEFAULT_DEVICE) -> Module:
    """Load weights from HuBERTPretrainModel checkpoint into hubert_pretrain_base model.
    Args:
        model (Module): The hubert_pretrain_base model.
        checkpoint_path (Path): The model checkpoint.
        device (torch.device, optional): The device of the model. (Default: ``torch.device("cpu")``)
    Returns:
        (Module): The pretrained model.
    """
    state_dict = torch.load(checkpoint_path, map_location=device)
    state_dict = {k.replace("model.", ""): v for k, v in state_dict["state_dict"].items()}
    model.load_state_dict(state_dict)
    return model