Update README.md

README.md

@@ -60,3 +60,45 @@ The image is a close-up shot of a vibrant garden scene, focusing on pink cosmos
 
 **Overall, the image is a charming depiction of a summer garden, highlighting the beauty of nature and the important role of pollinators like bumblebees.**
 ```
+
+## Generate the model
+
+Here is the sample command to reproduce the model.
+
+```bash
+pip install git+https://github.com/intel/auto-round.git@main
+auto-round-mllm \
+--model google/gemma-3-27b-it \
+--device 0 \
+--bits 4 \
+--group_size 32 \
+--batch_size 1 \
+--gradient_accumulate_steps 8 \
+--format 'gguf:q4_0' \
+--output_dir "./tmp_autoround"
+```
+
+
+## Ethical Considerations and Limitations
+
+The model can produce factually incorrect output, and should not be relied on to produce factually accurate information. Because of the limitations of the pretrained model and the finetuning datasets, it is possible that this model could generate lewd, biased or otherwise offensive outputs.
+
+Therefore, before deploying any applications of the model, developers should perform safety testing.
+
+## Caveats and Recommendations
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model.
+
+Here are a couple of useful links to learn more about Intel's AI software:
+
+- Intel Neural Compressor [link](https://github.com/intel/neural-compressor)
+
+## Disclaimer
+
+The license on this model does not constitute legal advice. We are not responsible for the actions of third parties who use this model. Please consult an attorney before using this model for commercial purposes.
+
+## Cite
+
+@article{cheng2023optimize, title={Optimize weight rounding via signed gradient descent for the quantization of llms}, author={Cheng, Wenhua and Zhang, Weiwei and Shen, Haihao and Cai, Yiyang and He, Xin and Lv, Kaokao and Liu, Yi}, journal={arXiv preprint arXiv:2309.05516}, year={2023} }
+
+[arxiv](https://arxiv.org/abs/2309.05516) [github](https://github.com/intel/auto-round)