| | |
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| | | res = model.export(quantize=False) |
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| | | ``` |
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| | | |
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| | | ### Text ONNX |
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| | | ```python |
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| | | # pip3 install -U funasr-onnx |
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| | | from funasr_onnx import Paraformer |
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| | | model_dir = "damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch" |
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| | | model = Paraformer(model_dir, batch_size=1, quantize=True) |
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| | | |
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| | | wav_path = ['~/.cache/modelscope/hub/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/example/asr_example.wav'] |
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| | | |
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| | | result = model(wav_path) |
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| | | print(result) |
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| | | ``` |
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| | | |
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| | | More examples ref to [demo](runtime/python/onnxruntime) |
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| | | |
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| | | ## Deployment Service |
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| | | FunASR supports deploying pre-trained or further fine-tuned models for service. Currently, it supports the following types of service deployment: |
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| | | - File transcription service, Mandarin, CPU version, done |
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