Update README.md

README.md

@@ -22,6 +22,12 @@ This model aims to detect visual manipulation in bar charts.
 - **Model type:** Multi-Modal LLM
 - **Finetuned from model:** llava-1.6-mistral-7b
 
+## How to Get Started with the Model
+
+This is not a HuggingFace-based model, please refer to this 
+[Colab notebook](https://colab.research.google.com/drive/1UpnztYv46faXj-kmFpL_GAbOCjP2u6zM?usp=sharing) 
+to run inference. Only works on GPU.
+
 ## Training Details
 
 Finetuned with LoRA for 1 epoch on ~2700 images of misleading and non misleading bar charts
@@ -49,3 +55,16 @@ bias="none"
 #### Training Hyperparameters
 
 - **Training regime:** bf16 non-mixed precision
+
+
+## Citation
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+- Liu, Haotian, Li, Chunyuan, Li, Yuheng, Li, Bo, Zhang, Yuanhan, Shen, Sheng, & Lee, Yong Jae. (2024, January). **LLaVA-NeXT: Improved reasoning, OCR, and world knowledge**. Retrieved from [https://llava-vl.github.io/blog/2024-01-30-llava-next/](https://llava-vl.github.io/blog/2024-01-30-llava-next/).
+
+- Liu, Haotian, Li, Chunyuan, Li, Yuheng, & Lee, Yong Jae. (2023). **Improved Baselines with Visual Instruction Tuning**. *arXiv:2310.03744*.
+
+- Liu, Haotian, Li, Chunyuan, Wu, Qingyang, & Lee, Yong Jae. (2023). **Visual Instruction Tuning**. *NeurIPS*.