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Add model_dir to arguments #202

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merged 2 commits into from
Sep 30, 2022
Merged

Add model_dir to arguments #202

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9247fb9
Add model_dir to arguments
jibinmathew69 Sep 30, 2022
5de8acc
minor formatting change
jongwook Sep 30, 2022
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Add model_dir to arguments
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@jibinmathew69
jibinmathew69 committed Sep 30, 2022
commit 9247fb9e983731320e84187b876e198d748850cc
5 changes: 4 additions & 1 deletion whisper/transcribe.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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="overide default model directory with new directory")
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")
Expand All @@ -272,8 +273,10 @@ def cli():
parser.add_argument("--logprob_threshold", type=optional_float, default=-1.0, help="if the average log probability is lower than this value, treat the decoding as failed")
parser.add_argument("--no_speech_threshold", type=optional_float, default=0.6, help="if the probability of the <|nospeech|> token is higher than this value AND the decoding has failed due to `logprob_threshold`, consider the segment as silence")


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)
Expand All @@ -290,7 +293,7 @@ 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)
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