diff --git a/readme.md b/readme.md
index adae912..441e929 100644
--- a/readme.md
+++ b/readme.md
@@ -7,10 +7,11 @@ We derived the image embeddings by using a CLIP encoder and mapping it with the
 
 ### Prerequisites
 1. install requirements.txt
-2. Make sure you have downloaded `pytorch_model-00003-of-00003.bin`
+2. Make sure you have downloaded [pytorch_model-00003-of-00003.bin](https://huggingface.co/liuhaotian/LLaVA-13b-delta-v1-1/blob/main/pytorch_model-00003-of-00003.bin")
+3. For example image data, I use [2017 Val images 5K/1GB](http://images.cocodataset.org/zips/val2017.zip) and [2017 Train/Val annotations 241MB](http://images.cocodataset.org/annotations/annotations_trainval2017.zip)
 
 ### Usage
 
-Replace **image-dir** and **llava-ckpt** to your **test image folder addr** and **pytorch_model-00003-of-00003.bin addr**
+Replace **image-dir** and **llava-ckpt** to your **test image folder addr** and **pytorch_model-00003-of-00003.bin addr** and run:
 
 `python convert_images_to_vectors.py --image-dir ./datasets/coco/val2017 --output-dir imgVecs --vision-model openai/clip-vit-large-patch14-336 --proj-dim 5120 --llava-ckpt ./datasets/pytorch_model-00003-of-00003.bin --batch-size 64`