Update README.md

README.md

@@ -7,7 +7,7 @@ license: bsd-3-clause
 
 CodeT5 is a family of encoder-decoder language models for code from the paper: [CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation](https://arxiv.org/pdf/2109.00859.pdf) by Yue Wang, Weishi Wang, Shafiq Joty, and Steven C.H. Hoi.
 
-The checkpoint included in this repository is denoted as **CodeT5-large** (770M), which is introduced by the paper: [CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning](https://arxiv.org/pdf/2207.01780.pdf) by Hung Le, Yue Wang, Akhilesh Deepak Gotmare, Silvio Savarese, Steven C.H. Hoi
+The checkpoint included in this repository is denoted as **CodeT5-large** (770M), which is introduced by the paper: [CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning](https://arxiv.org/pdf/2207.01780.pdf) by Hung Le, Yue Wang, Akhilesh Deepak Gotmare, Silvio Savarese, Steven C.H. Hoi.
 
 ## Training data
 
@@ -24,7 +24,7 @@ We validate the effectiveness of this checkpoint pretrained with simplified stra
 
 ## How to use
 
-This model can be easily loaded using the `AutoModelForCausalLM` functionality:
+This model can be easily loaded using the `T5ForConditionalGeneration` functionality:
 
 ```python
 from transformers import AutoTokenizer, T5ForConditionalGeneration
@@ -41,7 +41,7 @@ print(tokenizer.decode(generated_ids[0], skip_special_tokens=True))
 ## BibTeX entry and citation info
 
 ```bibtex
-@inproceedings{DBLP:conf/emnlp/0034WJH21,
+@inproceedings{CodeT52021,
   author    = {Yue Wang and Weishi Wang and Shafiq R. Joty and Steven C. H. Hoi},
   title     = {CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation},
   booktitle = {EMNLP},
@@ -50,7 +50,7 @@ print(tokenizer.decode(generated_ids[0], skip_special_tokens=True))
   year      = {2021}
 }
 
-@article{coderl2022
+@article{CodeRL2022
   author    = {Hung Le, Yue Wang, Akhilesh Deepak Gotmare, Silvio Savarese, Steven C.H. Hoi},
   title     = {CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning},
   journal   = {arXiv preprint},