Update README.md

README.md

@@ -132,14 +132,12 @@ The model was evaluated using the seqeval metric, with the following results on
 If you use this model or the base model in your work, please consider citing **NepBERTa** as follows:
 
 ```bibtex
-@misc{adhikari2021nepberta,
-  title={NepBERTa: A Pretrained BERT Model for the Nepali Language},
-  author={Adhikari, Bharat},
-  year={2021},
-  eprint={2109.08654},
-  archivePrefix={arXiv},
-  primaryClass={cs.CL},
-  url={https://arxiv.org/abs/2109.08654}
+@inproceedings{timilsina2022nepberta,
+  title={NepBERTa: Nepali language model trained in a large corpus},
+  author={Timilsina, Sulav and Gautam, Milan and Bhattarai, Binod},
+  booktitle={Proceedings of the 2nd conference of the Asia-pacific chapter of the association for computational linguistics and the 12th international joint conference on natural language processing},
+  year={2022},
+  organization={Association for Computational Linguistics (ACL)}
 }
 ```