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README.md
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---
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license: apache-2.0
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---
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---
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language:
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- zh
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license: apache-2.0
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tags:
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- bert
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- NLU
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- NLI
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inference: true
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widget:
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- text: "今天心情不好[SEP]今天很开心"
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---
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# Erlangshen-MegatronBert-1.3B-Similarity, model (Chinese),one model of [Fengshenbang-LM](https://github.com/IDEA-CCNL/Fengshenbang-LM).
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We collect 20 paraphrace datasets in the Chinese domain for finetune, with a total of 2773880 samples. Our model is mainly based on [MegatronBert-1.3B](https://huggingface.co/IDEA-CCNL/Erlangshen-MegatronBert-1.3B)
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## Usage
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```python
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from transformers import BertForSequenceClassification
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from transformers import BertTokenizer
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import torch
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tokenizer=BertTokenizer.from_pretrained('IDEA-CCNL/Erlangshen-MegatronBert-1.3B-Similarity')
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model=BertForSequenceClassification.from_pretrained('IDEA-CCNL/Erlangshen-MegatronBert-1.3B-Similarity')
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texta='今天的饭不好吃'
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textb='今天心情不好'
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output=model(torch.tensor([tokenizer.encode(texta,textb)]))
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print(torch.nn.functional.softmax(output.logits,dim=-1))
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```
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## Scores on downstream chinese tasks(The dev datasets of BUSTM and AFQMC may exist in the train set)
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| Model | BQ | BUSTM | AFQMC |
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| :--------: | :-----: | :----: | :-----: |
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| Erlangshen-Roberta-110M-Similarity | 85.41 | 95.18 | 81.72 |
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| Erlangshen-Roberta-330M-Similarity | 86.21 | 99.29 | 93.89 |
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| Erlangshen-MegatronBert-1.3B-Similarity | 86.31 | - | - |
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## Citation
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If you find the resource is useful, please cite the following website in your paper.
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```
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@misc{Fengshenbang-LM,
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title={Fengshenbang-LM},
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author={IDEA-CCNL},
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year={2021},
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howpublished={\url{https://github.com/IDEA-CCNL/Fengshenbang-LM}},
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}
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```
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