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@ -32,7 +32,6 @@ Here we provided several pretrained models on different datasets. The details of
| [UniASR Urdu](https://modelscope.cn/models/damo/speech_UniASR_asr_2pass-ur-16k-common-vocab877-pytorch/summary) | Urdu | Alibaba Speech Data (? hours) | 877 | 95M | Online | UniASR streaming offline unifying models |
#### Conformer Models
#### Paraformer Models
| Model Name | Language | Training Data | Vocab Size | Parameter | Offline/Online | Notes |
|:----------------------------------------------------------------------------------------------------------------------:|:--------:|:---------------------:|:----------:|:---------:|:--------------:|:--------------------------------------------------------------------------------------------------------------------------------|
| [Conformer](https://modelscope.cn/models/damo/speech_conformer_asr_nat-zh-cn-16k-aishell1-vocab4234-pytorch/summary) | CN | AISHELL (178hours) | 4234 | 44M | Offline | Duration of input wav <= 20s |