Update README.md

README.md

@@ -71,4 +71,35 @@ The model is the result of further post-training [Qwen/Qwen2-7B-Instruct](https:
 The model was post-trained (freeze tuned & DPO) on a proprietary dataset consisting of diverse function calling, chat, and instruct data.
 
 ## How to use
-Refer to https://docs.rubra.ai/inference/llamacpp for usage. Feel free to ask/open issues up in our Github repo: https://github.com/rubra-ai/rubra 
+Refer to https://docs.rubra.ai/inference/llamacpp for usage. Feel free to ask/open issues up in our Github repo: https://github.com/rubra-ai/rubra 
+
+## Limitations and Bias
+
+While the model performs well on a wide range of tasks, it may still produce biased or incorrect outputs. Users should exercise caution and critical judgment when using the model in sensitive or high-stakes applications. The model's outputs are influenced by the data it was trained on, which may contain inherent biases.
+
+## Ethical Considerations
+
+Users should ensure that the deployment of this model adheres to ethical guidelines and consider the potential societal impact of the generated text. Misuse of the model for generating harmful or misleading content is strongly discouraged.
+
+## Acknowledgements
+
+We would like to thank Alibaba Cloud for the model.
+
+## Contact Information
+
+For questions or comments about the model, please reach out to [the rubra team](mailto:rubra@acorn.io).
+
+## Citation
+
+If you use this work, please cite it as:
+
+```
+@misc {rubra_ai_2024,
+	author       = { Sanjay Nadhavajhala and Yingbei Tong },
+	title        = { Rubra-Qwen2-7B-Instruct },
+	year         = 2024,
+	url          = { https://huggingface.co/rubra-ai/Qwen2-7B-Instruct },
+	doi          = { 10.57967/hf/2658 },
+	publisher    = { Hugging Face }
+}
+```