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---
license: apache-2.0
language:
- zh
metrics:
- accuracy
- cer
pipeline_tag: automatic-speech-recognition
tags:
- Paraformer
- FunASR
- ASR
---
## Introduce
This repo cloned from https://huggingface.co/funasr/Paraformer-large
## Install funasr_onnx
```shell
pip install -U funasr_onnx
# For the users in China, you could install with the command:
# pip install -U funasr_onnx -i https://mirror.sjtu.edu.cn/pypi/web/simple
```
## Download the model
```shell
git clone https://huggingface.co/hoangus0303/paraformer-large-clone-from-funasr
```
## Inference with runtime
### Speech Recognition
#### Paraformer
```python
from funasr_onnx import Paraformer
model_dir = "./paraformer-large"
model = Paraformer(model_dir, batch_size=1, quantize=True)
wav_path = ['./funasr/paraformer-large/asr_example.wav']
result = model(wav_path)
print(result)
```
- `model_dir`: the model path, which contains `model.onnx`, `config.yaml`, `am.mvn`
- `batch_size`: `1` (Default), the batch size duration inference
- `device_id`: `-1` (Default), infer on CPU. If you want to infer with GPU, set it to gpu_id (Please make sure that you have install the onnxruntime-gpu)
- `quantize`: `False` (Default), load the model of `model.onnx` in `model_dir`. If set `True`, load the model of `model_quant.onnx` in `model_dir`
- `intra_op_num_threads`: `4` (Default), sets the number of threads used for intraop parallelism on CPU
Input: wav formt file, support formats: `str, np.ndarray, List[str]`
Output: `List[str]`: recognition result