Add model_dir to arguments (#202)

* Add model_dir to arguments

* minor formatting change

Co-authored-by: Jong Wook Kim <jongwook@openai.com>

whisper/transcribe.py

@@ -249,6 +249,7 @@ def cli():
     parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
     parser.add_argument("audio", nargs="+", type=str, help="audio file(s) to transcribe")
     parser.add_argument("--model", default="small", choices=available_models(), help="name of the Whisper model to use")
+    parser.add_argument("--model_dir", type=str, default=None, help="the path to save model files; uses ~/.cache/whisper by default")
     parser.add_argument("--device", default="cuda" if torch.cuda.is_available() else "cpu", help="device to use for PyTorch inference")
     parser.add_argument("--output_dir", "-o", type=str, default=".", help="directory to save the outputs")
     parser.add_argument("--verbose", type=str2bool, default=True, help="whether to print out the progress and debug messages")
@@ -274,6 +275,7 @@ def cli():
 
     args = parser.parse_args().__dict__
     model_name: str = args.pop("model")
+    model_dir: str = args.pop("model_dir")
     output_dir: str = args.pop("output_dir")
     device: str = args.pop("device")
     os.makedirs(output_dir, exist_ok=True)
@@ -290,7 +292,7 @@ def cli():
         temperature = [temperature]
 
     from . import load_model
-    model = load_model(model_name, device=device)
+    model = load_model(model_name, device=device, download_root=model_dir)
 
     for audio_path in args.pop("audio"):
         result = transcribe(model, audio_path, temperature=temperature, **args)