enable fine-tuned faster-whisper model

modules/faster_whisper_inference.py

@@ -1,5 +1,4 @@
 import os
-
 import time
 import numpy as np
 from typing import BinaryIO, Union, Tuple, List
@@ -24,16 +23,17 @@ os.environ['KMP_DUPLICATE_LIB_OK'] = 'True'
 class FasterWhisperInference(BaseInterface):
     def __init__(self):
         super().__init__()
+        self.model_dir = os.path.join("models", "Whisper", "faster-whisper")
         self.current_model_size = None
         self.model = None
-        self.available_models = whisper.available_models()
+        self.model_paths = self.get_model_paths()
+        self.available_models = self.model_paths.keys()
         self.available_langs = sorted(list(whisper.tokenizer.LANGUAGES.values()))
         self.translatable_models = ["large", "large-v1", "large-v2", "large-v3"]
         self.device = "cuda" if torch.cuda.is_available() else "cpu"
         self.available_compute_types = ctranslate2.get_supported_compute_types(
             "cuda") if self.device == "cuda" else ctranslate2.get_supported_compute_types("cpu")
         self.current_compute_type = "float16" if self.device == "cuda" else "float32"
-        self.model_dir = os.path.join("models", "Whisper", "faster-whisper")
 
     def transcribe_file(self,
                         files: list,
@@ -317,15 +317,40 @@ class FasterWhisperInference(BaseInterface):
             Indicator to show progress directly in gradio.
         """
         progress(0, desc="Initializing Model..")
-        self.current_model_size = model_size
+        self.current_model_size = self.model_paths[model_size]
         self.current_compute_type = compute_type
         self.model = faster_whisper.WhisperModel(
             device=self.device,
-            model_size_or_path=model_size,
+            model_size_or_path=self.current_model_size,
             download_root=self.model_dir,
             compute_type=self.current_compute_type
         )
 
+    def get_model_paths(self):
+        """
+        Get available models from models path including fine-tuned model.
+
+        Returns
+        ----------
+        Name list of models
+        """
+        model_paths = {model:model for model in whisper.available_models()}
+        faster_whisper_prefix = "models--Systran--faster-whisper-"
+
+        existing_models = os.listdir(self.model_dir)
+        wrong_dirs = [".locks"]
+        existing_models = list(set(existing_models) - set(wrong_dirs))
+
+        webui_dir = os.getcwd()
+
+        for model_name in existing_models:
+            if faster_whisper_prefix in model_name:
+                model_name = model_name[len(faster_whisper_prefix):]
+
+            if model_name not in whisper.available_models():
+                model_paths[model_name] = os.path.join(webui_dir, self.model_dir, model_name)
+        return model_paths
+
     @staticmethod
     def generate_and_write_file(file_name: str,
                                 transcribed_segments: list,