北念
2023-10-16 91630e73316c1e04cad46a8bdffa59765822cc45
docs/model_zoo/modelscope_models.md
@@ -17,7 +17,9 @@
|                                                                     Model Name                                                                     | Language |          Training Data           | Vocab Size | Parameter | Offline/Online | Notes                                                                                                                           |
|:--------------------------------------------------------------------------------------------------------------------------------------------------:|:--------:|:--------------------------------:|:----------:|:---------:|:--------------:|:--------------------------------------------------------------------------------------------------------------------------------|
|        [Paraformer-large](https://www.modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary)        | CN & EN  | Alibaba Speech Data (60000hours) |    8404    |   220M    |    Offline     | Duration of input wav <= 20s                                                                                                    |
| [Paraformer-large-long](https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary) | CN & EN  | Alibaba Speech Data (60000hours) |    8404    |   220M    |    Offline     | Which would deal with arbitrary length input wav                                                                                 |
| [Paraformer-large-long](https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary) | CN & EN  | Alibaba Speech Data (60000hours) |    8404    |   220M    |    Offline     | Which would deal with arbitrary length input wav                                                                                |
| [Paraformer-large-en-long](https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-en-16k-common-vocab10020/summary) | EN  | Alibaba Speech Data (50000hours) |    10020    |   220M    |    Offline     | Which would deal with arbitrary length input wav                                                                                 |
| [Paraformer-large-Spk](https://modelscope.cn/models/damo/speech_paraformer-large-vad-punc-spk_asr_nat-zh-cn/summary) | CN & EN  | Alibaba Speech Data (60000hours) |    8404    |   220M    |    Offline     | Supporting speaker diarizatioin for ASR results based on paraformer-large-long |
| [Paraformer-large-contextual](https://www.modelscope.cn/models/damo/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404/summary) | CN & EN  | Alibaba Speech Data (60000hours) |    8404    |   220M    |    Offline     | Which supports the hotword customization based on the incentive enhancement, and improves the recall and precision of hotwords. |
|              [Paraformer](https://modelscope.cn/models/damo/speech_paraformer_asr_nat-zh-cn-16k-common-vocab8358-tensorflow1/summary)              | CN & EN  | Alibaba Speech Data (50000hours) |    8358    |    68M    |    Offline     | Duration of input wav <= 20s                                                                                                    |
|           [Paraformer-online](https://www.modelscope.cn/models/damo/speech_paraformer_asr_nat-zh-cn-16k-common-vocab8404-online/summary)           | CN & EN  | Alibaba Speech Data (50000hours) |    8404    |    68M    |     Online     | Which could deal with streaming input                                                                                           |
@@ -80,9 +82,9 @@
|                                                         Model Name                                                         |        Language | Training Data         | Parameters | Vocab Size| Offline/Online | Notes |
|:--------------------------------------------------------------------------------------------------------------------------:|:---------|:----------------------------:|:----------:|:----------:|:--------------:|:------|
|      [CT-Transformer](https://modelscope.cn/models/damo/punc_ct-transformer_cn-en-common-vocab471067-large/summary)     | CN & EN | Alibaba Text Data |    100M     |    471067     |    Offline     |   large offline punctuation model    |
|      [CT-Transformer](https://modelscope.cn/models/damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch/summary)    | CN & EN  | Alibaba Text Data |    70M     |    272727     |    Offline     |   offline punctuation model    |
| [CT-Transformer](https://modelscope.cn/models/damo/punc_ct-transformer_zh-cn-common-vad_realtime-vocab272727/summary)    | CN & EN  | Alibaba Text Data |    70M     |    272727     |     Online     |  online punctuation model     |
|      [CT-Transformer-Large](https://modelscope.cn/models/damo/punc_ct-transformer_cn-en-common-vocab471067-large/summary)     | CN & EN | Alibaba Text Data(100M) |    1.1G     |    471067     |    Offline     |   large offline punctuation model    |
|      [CT-Transformer](https://modelscope.cn/models/damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch/summary)    | CN & EN  | Alibaba Text Data(70M) |    291M     |    272727     |    Offline     |   offline punctuation model    |
| [CT-Transformer-Realtime](https://modelscope.cn/models/damo/punc_ct-transformer_zh-cn-common-vad_realtime-vocab272727/summary)    | CN & EN  | Alibaba Text Data(70M) |    288M     |    272727     |     Online     |  online punctuation model     |
### Language Models