def METHOD_NAME(self) -> bool:
    """
    The model can be initialized via
    1. downloading pre-trained weights for SemanticKITTI.
    2. passing a path to an existing checkpoint file.
    This has not been done in the __init__() function since logging is available only once the node is registered.
    """
    if self.checkpoint in ['semantickitti']:
        file_path = EfficientLpsLearner.download(str(self._tmp_folder),
                                                 trained_on=self.checkpoint)
        self.checkpoint = file_path
    if self._learner.load(self.checkpoint):
        self.get_logger().info('Successfully loaded the checkpoint.')
        return True
    else:
        self.get_logger().error('Failed to load the checkpoint.')
        return False