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| | | ### Install [modelscope and funasr](https://github.com/alibaba-damo-academy/FunASR#installation) |
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| | | |
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| | | ```shell |
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| | | pip3 install torch torchaudio |
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| | | pip install -U modelscope |
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| | | pip install -U funasr |
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| | | # pip3 install torch torchaudio |
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| | | pip install -U modelscope funasr |
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| | | # For the users in China, you could install with the command: |
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| | | # pip install -U modelscope funasr -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html -i https://mirror.sjtu.edu.cn/pypi/web/simple |
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| | | ``` |
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| | | |
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| | | ### Export [onnx model](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/export) |
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| | | |
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| | | ## Acknowledge |
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| | | 1. This project is maintained by [FunASR community](https://github.com/alibaba-damo-academy/FunASR). |
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| | | 2. We acknowledge [mayong](https://github.com/RapidAI/RapidASR/tree/main/cpp_onnx) for contributing the onnxruntime(cpp api). |
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| | | 3. We borrowed a lot of code from [FastASR](https://github.com/chenkui164/FastASR) for audio frontend and text-postprocess. |
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| | | 2. We acknowledge mayong for contributing the onnxruntime of Paraformer and CT_Transformer, [repo-asr](https://github.com/RapidAI/RapidASR/tree/main/cpp_onnx), [repo-punc](https://github.com/RapidAI/RapidPunc). |
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| | | 3. We acknowledge [ChinaTelecom](https://github.com/zhuzizyf/damo-fsmn-vad-infer-httpserver) for contributing the VAD runtime. |
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| | | 4. We borrowed a lot of code from [FastASR](https://github.com/chenkui164/FastASR) for audio frontend and text-postprocess. |
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