Update README.md

README.md

@@ -13,8 +13,8 @@ datasets:
 
 Chessgpt-Chat-v1 is the sft-tuned model of Chessgpt-Base-v1.
 
-  - Base Model: [Chessgpt-Base-v1](https://huggingface.co/Waterhorse/chessgpt-base-v1)
-  - Chat Version: [Chessgpt-Chat-v1](https://huggingface.co/Waterhorse/chessgpt-chat-v1)
+  - Base Model: [Chessgpt-base-v1](https://huggingface.co/Waterhorse/chessgpt-base-v1)
+  - Chat Version: [Chessgpt-chat-v1](https://huggingface.co/Waterhorse/chessgpt-chat-v1)
 
 ## Model Details
 - **Model type**: Language Model
@@ -74,4 +74,14 @@ Excluded uses are described below.
 Just as with any language model, chessgpt-chat-v1 carries inherent limitations that necessitate careful consideration. Specifically, it may occasionally generate responses that are irrelevant or incorrect, particularly when tasked with interpreting complex or ambiguous queries. Additionally, given that its training is rooted in online data, the model may inadvertently reflect and perpetuate common online stereotypes and biases.
 
 # Evaluation
-Please refer to our [paper](https://arxiv.org/abs/2306.09200) and [code](https://github.com/waterhorse1/ChessGPT)for benchmark results.
+Please refer to our [paper](https://arxiv.org/abs/2306.09200) and [code](https://github.com/waterhorse1/ChessGPT)for benchmark results.
+
+# Citation Information
+```bash
+@article{feng2023chessgpt,
+  title={ChessGPT: Bridging Policy Learning and Language Modeling},
+  author={Feng, Xidong and Luo, Yicheng and Wang, Ziyan and Tang, Hongrui and Yang, Mengyue and Shao, Kun and Mguni, David and Du, Yali and Wang, Jun},
+  journal={arXiv preprint arXiv:2306.09200},
+  year={2023}
+}
+```