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@@ -1,6 +1,7 @@
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# Libtorch-python
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## Export the model
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+
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### Install [modelscope and funasr](https://github.com/alibaba-damo-academy/FunASR#installation)
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```shell
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@@ -18,14 +19,16 @@ pip install onnx onnxruntime # Optional, for onnx quantization
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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 torch --quantize True
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```
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-## Install the `funasr_torch`.
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-
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+## Install the `funasr_torch`
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+
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install from pip
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+
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```shell
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pip install -U funasr_torch
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# For the users in China, you could install with the command:
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# pip install -U funasr_torch -i https://mirror.sjtu.edu.cn/pypi/web/simple
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```
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+
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or install from source code
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```shell
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@@ -36,11 +39,13 @@ pip install -e ./
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# pip install -e ./ -i https://mirror.sjtu.edu.cn/pypi/web/simple
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```
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-## Run the demo.
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+## Run the demo
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+
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- Model_dir: the model path, which contains `model.torchscripts`, `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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+
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```python
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from funasr_torch import Paraformer
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@@ -55,7 +60,7 @@ pip install -e ./
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## Performance benchmark
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-Please ref to [benchmark](https://github.com/alibaba-damo-academy/FunASR/blob/main/funasr/runtime/python/benchmark_libtorch.md)
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+Please ref to [benchmark](https://github.com/alibaba-damo-academy/FunASR/blob/main/runtime/docs/benchmark_libtorch.md)
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## Speed
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@@ -70,4 +75,5 @@ Test [wav, 5.53s, 100 times avg.](https://isv-data.oss-cn-hangzhou.aliyuncs.com/
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| Onnx | 0.038 |
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## Acknowledge
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+
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This project is maintained by [FunASR community](https://github.com/alibaba-damo-academy/FunASR).
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