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README.md

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-MiLMo:Minority Multilingual Pre-trained Language Model constructs a minority multilingual text classification dataset named MiTC，While training the pre-trained model of minority languages,this paper constructs a multilingual text classification dataset
-MiTC for various languages, which contains 82,662 samples.
+# MiTC
+
+## Introduction
+
+[MiLMo](https://github.com/CMLI-NLP/MiLMo) constructs a minority multilingual text classification dataset named MiTC which contains five languages, including Mongolian, Tibetan, Uyghur, Kazakh and Korean.
+
+We also use [MiLMo](https://github.com/CMLI-NLP/MiLMo) for the downstream experiment of text classification on MiTC.
+
+## Hugging Face
+
+https://huggingface.co/datasets/CMLI-NLP/MiTC
+
+## Citation
+
+Plain Text:  
+J. Deng, H. Shi, X. Yu, W. Bao, Y. Sun and X. Zhao, "MiLMo:Minority Multilingual Pre-Trained Language Model," 2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Honolulu, Oahu, HI, USA, 2023, pp. 329-334, doi: 10.1109/SMC53992.2023.10393961.
+
+BibTeX:
+```
+@INPROCEEDINGS{10393961,
+  author={Deng, Junjie and Shi, Hanru and Yu, Xinhe and Bao, Wugedele and Sun, Yuan and Zhao, Xiaobing},
+  booktitle={2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)}, 
+  title={MiLMo:Minority Multilingual Pre-Trained Language Model}, 
+  year={2023},
+  volume={},
+  number={},
+  pages={329-334},
+  keywords={Soft sensors;Text categorization;Social sciences;Government;Data acquisition;Morphology;Data models;Multilingual;Pre-trained language model;Datasets;Word2vec},
+  doi={10.1109/SMC53992.2023.10393961}}
+```