diff --git a/autotranscript/diarisation.py b/autotranscript/diarisation.py
index ea36b93..1c2e4fb 100644
--- a/autotranscript/diarisation.py
+++ b/autotranscript/diarisation.py
@@ -4,14 +4,16 @@ from torch import Tensor
 import os
 from typing import TypeVar, Union
 import json
-
+from .misc import PYANNOTE_DEFAULT_PATH
 Annotation = TypeVar('Annotation') 
 
-PYANNOTE_DEFAULT_PATH = os.path.join(os.path.dirname(os.path.dirname(__file__)), 
-                                     "models", "pyannote", 
-                                     "speaker_diarization", "config.yaml")
-
 class Diariser:
+    """
+    Diarisation class
+    This class is used to diarize an audio file using a pretrained model
+    from pyannote.audio.
+    :param model: model to use for diarization
+    """
     def __init__(self, model,*args,**kwargs) -> None:
 
         self.model = model
@@ -137,10 +139,11 @@ class Diariser:
         -------
         Pipeline Object
         """
-
+        
         if local:
             diarization_model =  Pipeline.from_pretrained(model,*args, **kwargs)
         else:
+            print("Loading model from HuggingFace")
             if token == "":
                 token = cls._get_token()
             diarization_model =  Pipeline.from_pretrained(model, use_auth_token = token,
diff --git a/autotranscript/misc.py b/autotranscript/misc.py
index 065e45d..716852e 100644
--- a/autotranscript/misc.py
+++ b/autotranscript/misc.py
@@ -4,83 +4,22 @@ from whisper import Whisper, load_model
 import os
 import glob
 from warnings import warn
+import yaml
 
-WHISPER_DEFAULT_PATH = os.path.join(os.path.dirname(os.path.dirname(__file__)),
+WHISPER_DEFAULT_PATH = os.path.join(os.path.dirname(__file__),
                                      "models", "whisper")
 
-PYANNOTE_DEFAULT_PATH = os.path.join(os.path.dirname(os.path.dirname(__file__)), 
+PYANNOTE_DEFAULT_PATH = os.path.join(os.path.dirname(__file__), 
                                      "models", "pyannote", 
                                      "speaker_diarization", "config.yaml")
 
-def load_whisper_model(model: str ="medium", local : bool = False, download_root: str = WHISPER_DEFAULT_PATH) -> Whisper:
+
+def config_diarization_yaml(file):
     """
-    Load modules from whisper
-
-    Parameters
-    ----------
-    whisper : str
-        whisper model
-        available models:
-
-            - 'tiny.en'
-            - 'tiny'
-            - 'base.en'
-            - 'base'
-            - 'small.en'
-            - 'small'
-            - 'medium.en'
-            - 'medium'
-            - 'large-v1'
-            - 'large-v2'
-            - 'large' 
-
-    local : bool
-        If true, load from local cache
-
-    download_root : str
-        Path to download the model
-
-        default: /models/whisper
+    Configure diarization pipeline from yaml file to use the model offline
+    and avoid manuel file manipulation.
     
-    Returns
-    -------
-    Whisper Object
+    :param file: yaml file
+    :type file: yaml
     """
-    warn("load_whisper_model is deprecated. Use Transcriptor.load_model() instead.", DeprecationWarning)
-    if local:
-        available_models = [os.path.basename(x) for x in glob.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.")
-
-    return load_model(model, download_root=download_root)
-
-def load_pyannote_model(model: str = PYANNOTE_DEFAULT_PATH, 
-                        token: str = "",
-                        local : bool = True,
-                        *args, **kwargs) -> Pipeline:
-    """
-    Load modules from pyannote
-
-    Parameters
-    ----------
-    model : str
-        pyannote model 
-        default: /models/pyannote/speaker_diarization/config.yaml
-    token : str
-        HUGGINGFACE_TOKEN
-    local : bool
-        If true, load from local cache
-    
-    Returns
-    -------
-    Pipeline Object
-    """
-    warn("load_pyannote_model is deprecated. Use Diarisation.load_model() instead.", DeprecationWarning)
-    if local:
-        return Pipeline.from_pretrained(model,*args, **kwargs)
-    else:
-        return Pipeline.from_pretrained(model, use_auth_token = token, *args, **kwargs)
+    
\ No newline at end of file
diff --git a/autotranscript/transcriber.py b/autotranscript/transcriber.py
index 39c0842..82156cf 100644
--- a/autotranscript/transcriber.py
+++ b/autotranscript/transcriber.py
@@ -2,24 +2,12 @@ import os
 from whisper import Whisper, load_model
 from typing import TypeVar , Union
 from glob import glob
-
+from .misc import WHISPER_DEFAULT_PATH
 whisper = TypeVar('whisper') 
 Tensor = TypeVar('Tensor')
 nparray = TypeVar('nparray')
 
-def get_whisper_default_path() -> str:
-    """
-    Get default path for whisper models
 
-    Returns
-    -------
-    str
-        path
-    """
-    _path = os.path.dirname(os.path.dirname(__file__))
-    return os.path.join(_path, "models", "whisper")
-
-WHISPER_DEFAULT_PATH = get_whisper_default_path()
 
 class Transcriber:
     def __init__(self, model: whisper ) -> None:
@@ -68,7 +56,7 @@ class Transcriber:
     def load_model(cls,
                     model: str = "medium", 
                     local : bool = True,
-                    download_root: str = WHISPER_DEFAULT_PATH ,
+                    download_root: str = WHISPER_DEFAULT_PATH,
                     *args, **kwargs) -> 'Transcriber':
         """
         Load whisper module