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