added citation

README.md

@@ -65,7 +65,7 @@ Follow the guide linked [here](https://towardsdatascience.com/fine-tuning-gpt2-o
 
 ## Finetuning using our code with TF 1.15.4:
 
-- Create the Training TFRecords:
+Create the Training TFRecords:
 ```bash
 python create_pretraining_data.py
  --input_file=<RAW TEXT FILE with documents/article sperated by an empty line>
@@ -73,26 +73,26 @@ python create_pretraining_data.py
  --tokenizer_dir=<Directory with the GPT2 Tokenizer files>
  ```
 
- - Finetuning:
+ Finetuning:
  ```bash
- python3 run_pretraining.py \
- --input_file="gs://<GS_BUCKET>/pretraining_data/*" \
- --output_dir="gs://<GS_BUCKET>/pretraining_model/" \
- --config_file="config/small_hparams.json" \
- --batch_size=128 \
- --eval_batch_size=8 \
- --num_train_steps= \
- --num_warmup_steps= \
- --learning_rate= \
- --save_checkpoints_steps= \
- --max_seq_length=1024 \
- --max_eval_steps= \
- --optimizer="lamb" \
- --iterations_per_loop=5000 \
- --keep_checkpoint_max=10 \
- --use_tpu=True \
- --tpu_name=<TPU NAME> \
- --do_train=True \
+ python3 run_pretraining.py \\
+ --input_file="gs://<GS_BUCKET>/pretraining_data/*" \\
+ --output_dir="gs://<GS_BUCKET>/pretraining_model/" \\
+ --config_file="config/small_hparams.json" \\
+ --batch_size=128 \\
+ --eval_batch_size=8 \\
+ --num_train_steps= \\
+ --num_warmup_steps= \\
+ --learning_rate= \\
+ --save_checkpoints_steps= \\
+ --max_seq_length=1024 \\
+ --max_eval_steps= \\
+ --optimizer="lamb" \\
+ --iterations_per_loop=5000 \\
+ --keep_checkpoint_max=10 \\
+ --use_tpu=True \\
+ --tpu_name=<TPU NAME> \\
+ --do_train=True \\
  --do_eval=False
  ```
 # Model Sizes
@@ -137,18 +137,23 @@ For the new dataset we added the unshuffled OSCAR corpus, after we thoroughly fi
 # If you used this model please cite us as :
 
 ```
-@misc{antoun2020aragpt2,
-      title={AraGPT2: Pre-Trained Transformer for Arabic Language Generation},
-      author={Wissam Antoun and Fady Baly and Hazem Hajj},
-      year={2020},
-      eprint={2012.15520},
-      archivePrefix={arXiv},
-      primaryClass={cs.CL}
+@inproceedings{antoun-etal-2021-aragpt2,
+    title = "{A}ra{GPT}2: Pre-Trained Transformer for {A}rabic Language Generation",
+    author = "Antoun, Wissam  and
+      Baly, Fady  and
+      Hajj, Hazem",
+    booktitle = "Proceedings of the Sixth Arabic Natural Language Processing Workshop",
+    month = apr,
+    year = "2021",
+    address = "Kyiv, Ukraine (Virtual)",
+    publisher = "Association for Computational Linguistics",
+    url = "https://www.aclweb.org/anthology/2021.wanlp-1.21",
+    pages = "196--207",
 }
 ```
 
 # Acknowledgments
-Thanks to TensorFlow Research Cloud (TFRC) for the free access to Cloud TPUs, couldn't have done it without this program, and to the [AUB MIND Lab](https://sites.aub.edu.lb/mindlab/) Members for the continous support. Also thanks to [Yakshof](https://www.yakshof.com/#/) and Assafir for data and storage access. Another thanks for Habib Rahal (https://www.behance.net/rahalhabib), for putting a face to AraBERT.
+Thanks to TensorFlow Research Cloud (TFRC) for the free access to Cloud TPUs, couldn't have done it without this program, and to the [AUB MIND Lab](https://sites.aub.edu.lb/mindlab/) Members for the continuous support. Also thanks to [Yakshof](https://www.yakshof.com/#/) and Assafir for data and storage access. Another thanks for Habib Rahal (https://www.behance.net/rahalhabib), for putting a face to AraBERT.
 
 # Contacts
 **Wissam Antoun**: [Linkedin](https://www.linkedin.com/in/wissam-antoun-622142b4/) | [Twitter](https://twitter.com/wissam_antoun) | [Github](https://github.com/WissamAntoun) | <[email protected]> | <[email protected]>