Update README.md

README.md

@@ -12,25 +12,25 @@ widget:
 license: apache-2.0
 ---
 
-# The [BERTić](https://huggingface.co/CLASSLA/bcms-bertic)* [bert-ich] /bɜrtitʃ/ model fine-tuned for the task of named entity recognition in Bosnian, Croatian, Montenegrin and Serbian (BCMS)
+# The [BERTić](https://huggingface.co/classla/bcms-bertic)* [bert-ich] /bɜrtitʃ/ model fine-tuned for the task of named entity recognition in Bosnian, Croatian, Montenegrin and Serbian (BCMS)
 
 * The name should resemble the facts (1) that the model was trained in Zagreb, Croatia, where diminutives ending in -ić (as in fotić, smajlić, hengić etc.) are very popular, and (2) that most surnames in the countries where these languages are spoken end in -ić (with diminutive etymology as well).
 
-This is a fine-tuned version of the [BERTić](https://huggingface.co/CLASSLA/bcms-bertic) model for the task of named entity recognition (PER, LOC, ORG, MISC). The fine-tuning was performed on the following datasets:
+This is a fine-tuned version of the [BERTić](https://huggingface.co/classla/bcms-bertic) model for the task of named entity recognition (PER, LOC, ORG, MISC). The fine-tuning was performed on the following datasets:
 
 - the [hr500k](http://hdl.handle.net/11356/1183) dataset, 500 thousand tokens in size, standard Croatian
 - the [SETimes.SR](http://hdl.handle.net/11356/1200) dataset, 87 thousand tokens in size, standard Serbian
 - the [ReLDI-hr](http://hdl.handle.net/11356/1241) dataset, 89 thousand tokens in size, Internet (Twitter) Croatian
 - the [ReLDI-sr](http://hdl.handle.net/11356/1240) dataset, 92 thousand tokens in size, Internet (Twitter) Serbian
 
-The data was augmented with missing diacritics and standard data was additionally over-represented. The F1 obtained on dev data (train and test was merged into train) is 91.38. For a more detailed per-dataset evaluation of the BERTić model on the NER task have a look at the [main model page](https://huggingface.co/CLASSLA/bcms-bertic).
+The data was augmented with missing diacritics and standard data was additionally over-represented. The F1 obtained on dev data (train and test was merged into train) is 91.38. For a more detailed per-dataset evaluation of the BERTić model on the NER task have a look at the [main model page](https://huggingface.co/classla/bcms-bertic).
 
 If you use this fine-tuned model, please cite the following paper:
 
 ```
 @inproceedings{ljubesic-lauc-2021-bertic,
     title = "{BERTić} - The Transformer Language Model for {B}osnian, {C}roatian, {M}ontenegrin and {S}erbian",
-    author = "Ljube{\v{s}}i{\'c}, Nikola  and
+    author = "Ljube{\\v{s}}i{\\'c}, Nikola  and
       Lauc, Davor",
     booktitle = "Proceedings of the 8th Workshop on Balto-Slavic Natural Language Processing",
     year = "2021",