Update README.md

README.md

@@ -14,6 +14,7 @@ library_name: nemo
 ## Model Overview
 
 Nemotron-4-Mini-Hindi-4B-Instruct is a model for generating responses to questions grounded in the Indian context. It supports queries in Hindi, English, and Hinglish. It is a small language model (SLM) which is fine-tuned/aligned version of [nvidia/Nemotron-4-Mini-Hindi-4B-Base](https://huggingface.co/nvidia/Nemotron-4-Mini-Hindi-4B-Base), which was continuously pre-trained on top of Nemotron-Mini-4B-Base (Minitron-4B-Base). The alignment stage uses a mix of real and synthetically generated alignment corpus. It supports a context length of 4,096 tokens. This model is ready for commercial use.
+Please refer to our [arXiv paper](https://arxiv.org/abs/2410.14815) for more details.
 
 Try this model on [build.nvidia.com](https://build.nvidia.com/nvidia/nemotron-4-mini-hindi-4b-instruct).
 
@@ -146,5 +147,15 @@ The model was trained on data that contains toxic language and societal biases o
 NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications.  When downloaded or used in accordance with our terms of service, developers should work with their internal model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse.  For more detailed information on ethical considerations for this model, please see the [Model Card++](https://build.nvidia.com/nvidia/nemotron-4-mini-hindi-4b-instruct/modelcard). Please report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).
 
 
+## Citation
 
-
+If you find our work helpful, please consider citing our paper:
+```
+@article{hindiminitron2024,
+      title={Adapting Multilingual LLMs to Low-Resource Languages using Continued Pre-training and Synthetic Corpus}, 
+      author={Raviraj Joshi and Kanishk Singla and Anusha Kamath and Raunak Kalani and Rakesh Paul and Utkarsh Vaidya and Sanjay Singh Chauhan and Niranjan Wartikar and Eileen Long},
+      journal={arXiv preprint arXiv:2410.14815},
+      year={2024},
+      url={https://arxiv.org/abs/2410.14815}, 
+}
+```