Update README.md

README.md

@@ -19,7 +19,7 @@ widget:
 
 ## Model description
 
-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).
+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.
 
 ## How to use
 
@@ -68,6 +68,7 @@ python3 scripts/convert_sbert_from_uer_to_huggingface.py --input_model_path mode
   journal={arXiv preprint arXiv:1908.10084},
   year={2019}
 }
+
 @article{zhao2019uer,
   title={UER: An Open-Source Toolkit for Pre-training Models},
   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},
@@ -75,4 +76,11 @@ python3 scripts/convert_sbert_from_uer_to_huggingface.py --input_model_path mode
   pages={241},
   year={2019}
 }
+
+@article{zhao2023tencentpretrain,
+  title={TencentPretrain: A Scalable and Flexible Toolkit for Pre-training Models of Different Modalities},
+  author={Zhao, Zhe and Li, Yudong and Hou, Cheng and Zhao, Jing and others},
+  journal={ACL 2023},
+  pages={217},
+  year={2023}
 ```