#!/usr/bin/env python3
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import argparse
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from modelscope.pipelines import pipeline
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from modelscope.utils.constant import Tasks
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if __name__ == '__main__':
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parser = argparse.ArgumentParser(
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description="download model configs",
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formatter_class=argparse.ArgumentDefaultsHelpFormatter,
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)
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parser.add_argument("--model_name",
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type=str,
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default="speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch",
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help="model name in modelscope")
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args = parser.parse_args()
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inference_pipeline = pipeline(
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task=Tasks.auto_speech_recognition,
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model='damo/{}'.format(args.model_name),
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model_revision='v1.0.0')
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