v0.0.4 (#29)

* Replace 'Self' type (requires python>=3.11); Add optional revision to hf_hub_download

* Bump version

vocos/__init__.py

@@ -1,4 +1,4 @@
 from vocos.pretrained import Vocos
 
 
-__version__ = "0.0.3"
+__version__ = "0.0.4"

vocos/pretrained.py

@@ -1,6 +1,6 @@
 from __future__ import annotations
 
-from typing import Any, Dict, Self, Tuple, Union
+from typing import Any, Dict, Tuple, Union, Optional
 
 import torch
 import yaml
@@ -47,7 +47,7 @@ def __init__(
         self.head = head
 
     @classmethod
-    def from_hparams(cls, config_path: str) -> Self:
+    def from_hparams(cls, config_path: str) -> Vocos:
         """
         Class method to create a new Vocos model instance from hyperparameters stored in a yaml configuration file.
         """
@@ -60,12 +60,12 @@ def from_hparams(cls, config_path: str) -> Self:
         return model
 
     @classmethod
-    def from_pretrained(cls, repo_id: str) -> Self:
+    def from_pretrained(cls, repo_id: 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.
         """
-        config_path = hf_hub_download(repo_id=repo_id, filename="config.yaml")
-        model_path = hf_hub_download(repo_id=repo_id, filename="pytorch_model.bin")
+        config_path = hf_hub_download(repo_id=repo_id, filename="config.yaml", revision=revision)
+        model_path = hf_hub_download(repo_id=repo_id, filename="pytorch_model.bin", revision=revision)
         model = cls.from_hparams(config_path)
         state_dict = torch.load(model_path, map_location="cpu")
         if isinstance(model.feature_extractor, EncodecFeatures):