From 77232f88015883c5fcd03170d7c699c87e4dc0fb Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期四, 27 四月 2023 22:51:22 +0800
Subject: [PATCH] Merge branch 'main' of github.com:alibaba-damo-academy/FunASR add

---
 funasr/runtime/onnxruntime/readme.md |    7 ++++---
 README.md                            |    2 +-
 2 files changed, 5 insertions(+), 4 deletions(-)

diff --git a/README.md b/README.md
index 665f425..414eb9b 100644
--- a/README.md
+++ b/README.md
@@ -28,7 +28,7 @@
 
 ## Highlights
 - FunASR supports speech recognition(ASR), Multi-talker ASR, Voice Activity Detection(VAD), Punctuation Restoration, Language Models, Speaker Verification and Speaker diarization.   
-- We have released large number of academic and industrial pretrained models on [ModelScope](https://www.modelscope.cn/models?page=1&tasks=auto-speech-recognition)
+- We have released large number of academic and industrial pretrained models on [ModelScope](https://www.modelscope.cn/models?page=1&tasks=auto-speech-recognition), ref to [Model Zoo](https://alibaba-damo-academy.github.io/FunASR/en/modelscope_models.html)
 - The pretrained model [Paraformer-large](https://www.modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary) obtains the best performance on many tasks in [SpeechIO leaderboard](https://github.com/SpeechColab/Leaderboard)
 - FunASR supplies a easy-to-use pipeline to finetune pretrained models from [ModelScope](https://www.modelscope.cn/models?page=1&tasks=auto-speech-recognition)
 - Compared to [Espnet](https://github.com/espnet/espnet) framework, the training speed of large-scale datasets in FunASR is much faster owning to the optimized dataloader.
diff --git a/funasr/runtime/onnxruntime/readme.md b/funasr/runtime/onnxruntime/readme.md
index 7a96261..436c7df 100644
--- a/funasr/runtime/onnxruntime/readme.md
+++ b/funasr/runtime/onnxruntime/readme.md
@@ -4,9 +4,10 @@
 ### Install [modelscope and funasr](https://github.com/alibaba-damo-academy/FunASR#installation)
 
 ```shell
-pip3 install torch torchaudio
-pip install -U modelscope
-pip install -U funasr
+# pip3 install torch torchaudio
+pip install -U modelscope funasr
+# For the users in China, you could install with the command:
+# 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
 ```
 
 ### Export [onnx model](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/export)

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