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| | | Step 1-2) Optional, Prepare server onnxruntime environment (on server). |
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| | | |
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| | | Install [`rapid_paraformer`](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/runtime/python/onnxruntime). |
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| | | Install [`onnx_paraformer`](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/runtime/python/onnxruntime). |
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| | | |
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| | | - Build the rapid_paraformer `whl` |
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| | | - Build the onnx_paraformer `whl` |
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| | | ``` |
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| | | git clone https://github.com/alibaba/FunASR.git && cd FunASR |
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| | | cd funasr/runtime/python/onnxruntime/rapid_paraformer |
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| | | python setup.py bdist_wheel |
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| | | python setup.py build |
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| | | python setup.py install |
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| | | ``` |
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| | | |
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| | | - Install the build `whl` |
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| | | ``` |
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| | | pip install dist/rapid_paraformer-0.0.1-py3-none-any.whl |
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| | | ``` |
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| | | [//]: # () |
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| | | [//]: # (- Install the build `whl`) |
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| | | |
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| | | [//]: # (```) |
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| | | |
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| | | [//]: # (pip install dist/rapid_paraformer-0.0.1-py3-none-any.whl) |
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| | | |
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| | | [//]: # (```) |
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| | | |
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| | | Export the model, more details ref to [export docs](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/runtime/python/onnxruntime). |
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| | | ``` |
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| | | python -m funasr.export.export_model 'damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch' "./export" true |
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| | | ```shell |
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| | | python -m funasr.export.export_model --model-name damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch --export-dir ./export --type onnx --quantize True |
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| | | ``` |
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| | | |
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| | | Step 2) Optional, generate protobuf file (run on server, the two generated pb files are both used for server and client). |
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