could the Vocos.from_pretrained code supoort to load from local?

[lilyzlt]

Firstly, thanks for your effort~
and when I use Vocos.from_pretrained("charactr/vocos-encodec-24khz"),I found it will Request huggingface everytime even I already download it, could this part code update from only download to support local dir as well?
update this code bellow:

to :
def from_pretrained(cls, repo_or_dir: str, revision: Optional[str] = None) -> Vocos:
"""
Class method to create a new Vocos model instance from a pre-trained model stored in the Hugging Face model hub
or from a local directory.
Args:
repo_or_dir (str): Either the repository ID on Hugging Face hub or the path to a local directory containing the model files.
revision (Optional[str], optional): The specific model version to use (if loading from Hugging Face hub).

    Returns:
        Vocos: An instance of the Vocos model loaded with pretrained weights.
    """
    if os.path.isdir(repo_or_dir):
        # Load from local directory
        config_path = os.path.join(repo_or_dir, "config.yaml")
        model_path = os.path.join(repo_or_dir, "pytorch_model.bin")
    else:
        # Load from Hugging Face model hub
        config_path = hf_hub_download(repo_id=repo_or_dir, filename="config.yaml", revision=revision)
        model_path = hf_hub_download(repo_id=repo_or_dir, filename="pytorch_model.bin", revision=revision)

    # Load the model configuration and state dictionary
    model = cls.from_hparams(config_path)
    state_dict = torch.load(model_path, map_location="cpu")

    # Handle special cases for feature extractor if necessary
    if isinstance(model.feature_extractor, EncodecFeatures):
        encodec_parameters = {
            "feature_extractor.encodec." + key: value
            for key, value in model.feature_extractor.encodec.state_dict().items()
        }
        state_dict.update(encodec_parameters)

    # Load the state dictionary into the model
    model.load_state_dict(state_dict)
    model.eval()
    return model

thanks a lot~