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README.md

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+
+# CAMeLBERT-CATiB-parser
+
+## Model description
+The **CAMeLBERT-CATiB-parser** is a neural dependency parsing model for Arabic text, specifically designed for the CATiB dependency formalism. 
+It is based on the Biaffine Attention Dependency Parsing model introduced by [Dozat and Manning (2017)](https://arxiv.org/pdf/1611.01734.pdf) and implemented in 
+[SuPar](https://github.com/yzhangcs/parser), which has been shown to be very effective for dependency parsing in many languages. 
+The model is trained on the CamelTB and PATB combined train sets, which are both large Arabic corpora. 
+The model uses a CamelBERT-MSA word embedding layer, which is a pre-trained language model that has been trained on a massive dataset of Arabic text. 
+The model was introduced in our paper "CamelParser2.0: A State-of-the-Art Dependency Parser for Arabic". 
+The paper describes the model in detail and evaluates its performance on various Arabic dependency parsing tasks.
+
+## Intended uses
+The CAMeLBERT-CATiB-parser is shipped with the (CAMeLParser)[https://github.com/CAMeL-Lab/camel_parser] as one of the default parsing models, 
+and can be selected when parsing texts using the CATiB formalism.
+
+## Citation
+```bibtex
+@inproceedings{Elshabrawy:2023:camelparser,
+    title = "{CamelParser2.0: A State-of-the-Art Dependency Parser for Arabic}",
+    author = {Ahmed Elshabrawy and
+              Muhammed AbuOdeh and
+              Go Inoue and
+              Nizar Habash} ,
+    booktitle = {Proceedings of The First Arabic Natural Language Processing Conference (ArabicNLP 2023)},
+    year = "2023"
+}
+```