diff --git a/autotranscript/transcriber.py b/autotranscript/transcriber.py
index 82156cf..0cd42bf 100644
--- a/autotranscript/transcriber.py
+++ b/autotranscript/transcriber.py
@@ -1,6 +1,7 @@
 import os
 from whisper import Whisper, load_model
-from typing import TypeVar , Union
+from typing import TypeVar , Union , Optional
+import torch
 from glob import glob
 from .misc import WHISPER_DEFAULT_PATH
 whisper = TypeVar('whisper') 
@@ -17,7 +18,7 @@ class Transcriber:
         """
         self.model = model
 
-    def transcribe(self, audio : Union[str, Tensor, nparray]  ,
+    def transcribe(self, audio : Union[str, Tensor, nparray] ,
                    *args, **kwargs) -> str:
         """
         transcribe audio file
@@ -55,9 +56,10 @@ class Transcriber:
     @classmethod
     def load_model(cls,
                     model: str = "medium", 
-                    local : bool = True,
                     download_root: str = WHISPER_DEFAULT_PATH,
-                    *args, **kwargs) -> 'Transcriber':
+                    device: Optional[Union[str, torch.device]] = None,
+                    in_memory: bool = False,
+                    ) -> 'Transcriber':
         """
         Load whisper module
 
@@ -92,20 +94,9 @@ class Transcriber:
         Whisper Object
         """
 
-        if local:
-            
-            available_models = [os.path.basename(x) for x in 
-                                glob(os.path.join(download_root, "*"))]
-            
-            for i, module in enumerate(available_models):
-                available_models[i] = module.split(".")[0]
-            
-            if model not in available_models:
-                raise RuntimeError("Model not found. Consider downloading the "/
-                                   "model first. By deactivating the local flag, " /
-                                    "the model will be downloaded automatically.")
 
-        _model = load_model(model, download_root=download_root, *args, **kwargs)
+        _model = load_model(model, download_root=download_root,
+                            device=device, in_memory=in_memory)
 
         return cls(_model)