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docs/huggingface_models.md
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@ -9,11 +9,9 @@ Here we provided several pretrained models on different datasets. The details of
### Speech Recognition Models
#### Paraformer Models
[//]: # (| Model Name | Language | Training Data | Vocab Size | Parameter | Offline/Online | Notes |)
[//]: # (|:--------------------------------------------------------------------------------------------------------------------------------------------------:|:--------:|:--------------------------------:|:----------:|:---------:|:--------------:|:--------------------------------------------------------------------------------------------------------------------------------|)
[//]: # (| [Paraformer-large]&#40;https://www.modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary&#41; | CN & EN | Alibaba Speech Data &#40;60000hours&#41; | 8404 | 220M | Offline | Duration of input wav <= 20s |)
| Model Name | Language | Training Data | Vocab Size | Parameter | Offline/Online | Notes |
|:-----------------------------------------------------------------------:|:--------:|:----------------------------------:|:----------:|:---------:|:--------------:|:--------------------------------------------------------------------------------------------------------------------------------|
| [Paraformer-large](https://huggingface.co/funasr/paraformer-large) | CN & EN | Alibaba Speech Data (60000hours) | 8404 | 220M | Offline | Duration of input wav <= 20s |
[//]: # (| [Paraformer-large-long]&#40;https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary&#41; | CN & EN | Alibaba Speech Data &#40;60000hours&#41; | 8404 | 220M | Offline | Which ould deal with arbitrary length input wav |)
@ -77,21 +75,17 @@ Here we provided several pretrained models on different datasets. The details of
### Voice Activity Detection Models
[//]: # (| Model Name | Training Data | Parameters | Sampling Rate | Notes |)
[//]: # (|:----------------------------------------------------------------------------------------------:|:----------------------------:|:----------:|:-------------:|:------|)
[//]: # (| [FSMN-VAD]&#40;https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/summary&#41; | Alibaba Speech Data &#40;5000hours&#41; | 0.4M | 16000 | |)
| Model Name | Training Data | Parameters | Sampling Rate | Notes |
|:----------------------------------------------------:|:----------------------------:|:----------:|:-------------:|:------|
| [FSMN-VAD](https://huggingface.co/funasr/FSMN-VAD) | Alibaba Speech Data (5000hours) | 0.4M | 16000 | |
[//]: # (| [FSMN-VAD]&#40;https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-8k-common/summary&#41; | Alibaba Speech Data &#40;5000hours&#41; | 0.4M | 8000 | |)
### Punctuation Restoration Models
[//]: # (| Model Name | Training Data | Parameters | Vocab Size| Offline/Online | Notes |)
[//]: # (|:--------------------------------------------------------------------------------------------------------------------------:|:----------------------------:|:----------:|:----------:|:--------------:|:------|)
[//]: # (| [CT-Transformer]&#40;https://modelscope.cn/models/damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch/summary&#41; | Alibaba Text Data | 70M | 272727 | Offline | offline punctuation model |)
| Model Name | Training Data | Parameters | Vocab Size| Offline/Online | Notes |
|:--------------------------------------------------------------------:|:----------------------------:|:----------:|:----------:|:--------------:|:------|
| [CT-Transformer](https://huggingface.co/funasr/CT-Transformer-punc) | Alibaba Text Data | 70M | 272727 | Offline | offline punctuation model |
[//]: # (| [CT-Transformer]&#40;https://modelscope.cn/models/damo/punc_ct-transformer_zh-cn-common-vad_realtime-vocab272727/summary&#41; | Alibaba Text Data | 70M | 272727 | Online | online punctuation model |)