| | |
| | | task=Tasks.auto_speech_recognition, |
| | | model=args.model, |
| | | output_dir=args.output_dir, |
| | | batch_size=args.batch_size, |
| | | param_dict={"decoding_model": args.decoding_mode, "hotword": args.hotword_txt} |
| | | ) |
| | | inference_pipeline(audio_in=args.audio_in) |
| | | inference_pipeline(audio_in=args.audio_in, batch_size_token=args.batch_size_token) |
| | | |
| | | if __name__ == "__main__": |
| | | parser = argparse.ArgumentParser() |
| | |
| | | parser.add_argument('--output_dir', type=str, default="./results/") |
| | | parser.add_argument('--decoding_mode', type=str, default="normal") |
| | | parser.add_argument('--hotword_txt', type=str, default=None) |
| | | parser.add_argument('--batch_size', type=int, default=64) |
| | | parser.add_argument('--batch_size_token', type=int, default=5000) |
| | | parser.add_argument('--gpuid', type=str, default="0") |
| | | args = parser.parse_args() |
| | | modelscope_infer(args) |