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| | | ### Steps: |
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| | | 1. Download the whole directory |
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| | | ```shell |
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| | | git clone https://github.com/alibaba/FunASR.git && cd FunASR |
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| | | cd funasr/runtime/python/onnxruntime/paraformer/rapid_paraformer |
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| | | ``` |
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| | | 2. Install the related packages. |
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| | | ```bash |
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| | | pip install -r requirements.txt |
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| | | ``` |
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| | | 3. Export the model. |
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| | | |
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| | | `Tips`: torch 1.11.0 is required. |
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| | | 1. Export the model. |
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| | | - Command: (`Tips`: torch 1.11.0 is required.) |
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| | | |
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| | | ```shell |
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| | | python -m funasr.export.export_model [model_name] [export_dir] [true] |
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| | | ``` |
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| | | `model_name`: the model is to export. |
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| | | |
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| | | `export_dir`: the dir where the onnx is export. |
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| | | |
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| | | More details ref to ([export docs](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/export)) |
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| | | - `e.g.`, Export model from modelscope |
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| | | ```shell |
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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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| | | python -m funasr.export.export_model [model_name] [export_dir] [true] |
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| | | ``` |
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| | | - `e.g.`, Export model from local path, the model'name must be `model.pb`. |
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| | | ```shell |
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| | | python -m funasr.export.export_model '/mnt/workspace/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch' "./export" true |
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| | | ``` |
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| | | `model_name`: the model is to export. |
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| | | |
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| | | 5. Run the demo. |
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| | | `export_dir`: the dir where the onnx is export. |
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| | | |
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| | | More details ref to ([export docs](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/export)) |
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| | | |
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| | | - `e.g.`, Export model from modelscope |
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| | | ```shell |
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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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| | | ``` |
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| | | - `e.g.`, Export model from local path, the model'name must be `model.pb`. |
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| | | ```shell |
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| | | python -m funasr.export.export_model '/mnt/workspace/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch' "./export" true |
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| | | ``` |
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| | | |
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| | | 2. Install the `rapid_paraformer`. |
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| | | - Build the rapid_paraformer `whl` |
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| | | ```shell |
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| | | git clone https://github.com/alibaba/FunASR.git && cd FunASR |
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| | | cd funasr/runtime/python/onnxruntime |
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| | | python setup.py bdist_wheel |
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| | | ``` |
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| | | - Install the build `whl` |
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| | | ```bash |
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| | | pip install dist/rapid_paraformer-0.0.1-py3-none-any.whl |
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| | | ``` |
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| | | 3. Run the demo. |
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| | | - Model_dir: the model path, which contains `model.onnx`, `config.yaml`, `am.mvn`. |
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| | | - Input: wav formt file, support formats: `str, np.ndarray, List[str]` |
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| | | - Output: `List[str]`: recognition result. |
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| | | - Example: |
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| | | ```python |
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| | | from paraformer_onnx import Paraformer |
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| | | from rapid_paraformer import Paraformer |
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| | | model_dir = "/nfs/zhifu.gzf/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch" |
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| | | model = Paraformer(model_dir, batch_size=1) |
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