From 0ee33ed14b24bf13ea70197c4b0cc6770e0d1639 Mon Sep 17 00:00:00 2001
From: 彭震东 <zhendong.peng@qq.com>
Date: 星期一, 18 三月 2024 21:56:20 +0800
Subject: [PATCH] fix typo (#1510)

---
 README.md |   17 ++++++++++++++++-
 1 files changed, 16 insertions(+), 1 deletions(-)

diff --git a/README.md b/README.md
index d159050..a4511b9 100644
--- a/README.md
+++ b/README.md
@@ -112,7 +112,7 @@
 from funasr import AutoModel
 # paraformer-zh is a multi-functional asr model
 # use vad, punc, spk or not as you need
-model = AutoModel(model="paraformer-zh",  vad_model="fsmn-vad",  punc_model="ct-punc-c", 
+model = AutoModel(model="paraformer-zh",  vad_model="fsmn-vad",  punc_model="ct-punc", 
                   # spk_model="cam++", 
                   )
 res = model.generate(input=f"{model.model_path}/example/asr_example.wav", 
@@ -227,6 +227,21 @@
 res = model.export(quantize=False)
 ```
 
+### Test ONNX
+```python
+# pip3 install -U funasr-onnx
+from funasr_onnx import Paraformer
+model_dir = "damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch"
+model = Paraformer(model_dir, batch_size=1, quantize=True)
+
+wav_path = ['~/.cache/modelscope/hub/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/example/asr_example.wav']
+
+result = model(wav_path)
+print(result)
+```
+
+More examples ref to [demo](runtime/python/onnxruntime)
+
 ## Deployment Service
 FunASR supports deploying pre-trained or further fine-tuned models for service. Currently, it supports the following types of service deployment:
 - File transcription service, Mandarin, CPU version, done

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