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README.md
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## Model description
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This is the sentence embedding model pre-trained by [UER-py](https://github.com/dbiir/UER-py/), which is introduced in [this paper](https://arxiv.org/abs/1909.05658).
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## How to use
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journal={arXiv preprint arXiv:1908.10084},
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year={2019}
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}
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@article{zhao2019uer,
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title={UER: An Open-Source Toolkit for Pre-training Models},
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author={Zhao, Zhe and Chen, Hui and Zhang, Jinbin and Zhao, Xin and Liu, Tao and Lu, Wei and Chen, Xi and Deng, Haotang and Ju, Qi and Du, Xiaoyong},
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pages={241},
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year={2019}
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}
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```
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## Model description
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This is the sentence embedding model pre-trained by [UER-py](https://github.com/dbiir/UER-py/), which is introduced in [this paper](https://arxiv.org/abs/1909.05658). Besides, the model could also be pre-trained by [TencentPretrain](https://github.com/Tencent/TencentPretrain) introduced in [this paper](https://arxiv.org/abs/2212.06385), which inherits UER-py to support models with parameters above one billion, and extends it to a multimodal pre-training framework.
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## How to use
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journal={arXiv preprint arXiv:1908.10084},
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year={2019}
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}
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@article{zhao2019uer,
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title={UER: An Open-Source Toolkit for Pre-training Models},
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author={Zhao, Zhe and Chen, Hui and Zhang, Jinbin and Zhao, Xin and Liu, Tao and Lu, Wei and Chen, Xi and Deng, Haotang and Ju, Qi and Du, Xiaoyong},
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pages={241},
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year={2019}
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}
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@article{zhao2023tencentpretrain,
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title={TencentPretrain: A Scalable and Flexible Toolkit for Pre-training Models of Different Modalities},
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author={Zhao, Zhe and Li, Yudong and Hou, Cheng and Zhao, Jing and others},
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journal={ACL 2023},
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pages={217},
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year={2023}
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```
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