Fixed cache default value, moved ValuError t othe right place, added to docstring.

scraibe/diarisation.py

@@ -187,7 +187,7 @@ class Diariser:
     def load_model(cls, 
                     model: str = PYANNOTE_DEFAULT_CONFIG,
                     use_auth_token: str = None,
-                    cache_token: bool = True,
+                    cache_token: bool = False,
                     cache_dir: Union[Path, str] = PYANNOTE_DEFAULT_PATH,
                     hparams_file: Union[str, Path] = None,
                     device: str = None,
@@ -196,11 +196,12 @@ class Diariser:
         
         """
         Loads a pretrained model from pyannote.audio, 
-        either from a local cache or online repository.
+        either from a local cache or some online repository.
 
         Args:
             model: Path or identifier for the pyannote model.
-                default: /models/pyannote/speaker_diarization/config.yaml
+                default: '/home/[user]/.cache/torch/models/pyannote/config.yaml'
+                or one of 'jaikinator/scraibe', 'pyannote/speaker-diarization-3.1'
             token: Optional HUGGINGFACE_TOKEN for authenticated access.
             cache_token: Whether to cache the token locally for future use.
             cache_dir: Directory for caching models.
@@ -261,8 +262,8 @@ class Diariser:
                 model = _model
                 if cache_token and use_auth_token is not None:
                     cls._save_token(use_auth_token)
-                
+
-                if not os.path.exists(model) and use_auth_token is None:
+                if use_auth_token is None:
                     use_auth_token = cls._get_token()
         else:
             raise FileNotFoundError(f'No local model or directory found at {model}.')
@@ -271,18 +272,17 @@ class Diariser:
                                           use_auth_token=use_auth_token,
                                           cache_dir=cache_dir,
                                           hparams_file=hparams_file,)
-        
-        # try to move the model to the device
-        if device is None:
-            device = "cuda" if is_available() else "cpu"
-        
-        _model = _model.to(torch_device(device)) # torch_device is renamed from torch.device to avoid name conflict
-            
         if _model is None:
             raise ValueError('Unable to load model either from local cache' \
                 'or from huggingface.co models. Please check your token' \
                 'or your local model path')
-        
+
+        # try to move the model to the device
+        if device is None:
+            device = "cuda" if is_available() else "cpu"
+
+        _model = _model.to(torch_device(device)) # torch_device is renamed from torch.device to avoid name conflict
+
         return cls(_model)
 
     @staticmethod