chrissewell/whisperX
1
0
Fork 0
mirror of https://github.com/m-bain/whisperX.git synced 2025-07-01 18:17:27 -04:00
Code Issues Packages Projects Releases Wiki Activity

Merge pull request #1024 from philmcmahon/local-files-only-param

Browse Source 
Add models_cache_only param
This commit is contained in:
Max Bain
2025-01-27 14:26:19 +00:00
committed by GitHub
parent 36d2622e27 7b3c9ce629
commit 44e8bf5bb6
1 changed files with 3 additions and 1 deletions
Download Patch File Download Diff File Expand all files Collapse all files

4
whisperx/transcribe.py
View File

@ -26,6 +26,7 @@ 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", help="name of the Whisper model to use")
parser.add_argument("--model_cache_only", type=str2bool, default=False, help="If True, will not attempt to download models, instead using cached models from --model_dir")
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("--device_index", default=0, type=int, help="device index to use for FasterWhisper inference")
@ -90,6 +91,7 @@ def cli():
model_name: str = args.pop("model")
batch_size: int = args.pop("batch_size")
model_dir: str = args.pop("model_dir")
model_cache_only: bool = args.pop("model_cache_only")
output_dir: str = args.pop("output_dir")
output_format: str = args.pop("output_format")
device: str = args.pop("device")
@ -177,7 +179,7 @@ def cli():
results = []
tmp_results = []
# model = load_model(model_name, device=device, download_root=model_dir)
model = load_model(model_name, device=device, device_index=device_index, download_root=model_dir, compute_type=compute_type, language=args['language'], asr_options=asr_options, vad_method=vad_method, vad_options={"chunk_size":chunk_size, "vad_onset": vad_onset, "vad_offset": vad_offset}, task=task, threads=faster_whisper_threads)
model = load_model(model_name, device=device, device_index=device_index, download_root=model_dir, compute_type=compute_type, language=args['language'], asr_options=asr_options, vad_method=vad_method, vad_options={"chunk_size":chunk_size, "vad_onset": vad_onset, "vad_offset": vad_offset}, task=task, local_files_only=model_cache_only, threads=faster_whisper_threads)
for audio_path in args.pop("audio"):
audio = load_audio(audio_path)