Enable direct use of model from huggingface

app.py

@@ -49,7 +49,7 @@ def create_pipeline_inputs(self):
 
         with gr.Row():
             dd_model = gr.Dropdown(choices=self.whisper_inf.available_models, value=whisper_params["model_size"],
-                                   label=_("Model"))
+                                   label=_("Model"), allow_custom_value=True)
             dd_lang = gr.Dropdown(choices=self.whisper_inf.available_langs + [AUTOMATIC_DETECTION],
                                   value=AUTOMATIC_DETECTION if whisper_params["lang"] == AUTOMATIC_DETECTION.unwrap()
                                   else whisper_params["lang"], label=_("Language"))

modules/whisper/faster_whisper_inference.py

@@ -1,5 +1,6 @@
 import os
 import time
+import huggingface_hub
 import numpy as np
 import torch
 from typing import BinaryIO, Union, Tuple, List
@@ -118,15 +119,28 @@ def update_model(self,
         Parameters
         ----------
         model_size: str
-            Size of whisper model
+            Size of whisper model. If you enter the huggingface repo id, it will try to download the model
+            automatically from huggingface.
         compute_type: str
             Compute type for transcription.
             see more info : https://opennmt.net/CTranslate2/quantization.html
         progress: gr.Progress
             Indicator to show progress directly in gradio.
         """
         progress(0, desc="Initializing Model..")
-        self.current_model_size = self.model_paths[model_size]
+
+        model_size_dirname = model_size.replace("/", "--") if "/" in model_size else model_size
+        if model_size not in self.model_paths and model_size_dirname not in self.model_paths:
+            print(f"Model is not detected. Trying to download \"{model_size}\" from huggingface to "
+                  f"\"{os.path.join(self.model_dir, model_size_dirname)} ...")
+            huggingface_hub.snapshot_download(
+                model_size,
+                local_dir=os.path.join(self.model_dir, model_size_dirname),
+            )
+            self.model_paths = self.get_model_paths()
+            gr.Info(f"Model is downloaded with the name \"{model_size_dirname}\"")
+
+        self.current_model_size = self.model_paths[model_size_dirname]
 
         local_files_only = False
         hf_prefix = "models--Systran--faster-whisper-"