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@ -7,8 +7,8 @@ We derived the image embeddings by using a CLIP encoder and mapping it with the
### Prerequisites ### Prerequisites
1. install requirements.txt 1. install requirements.txt
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") 2. Make sure you have [llava-v1.5-mlp2x-336px-pretrain-vicuna-7b-v1.5](https://huggingface.co/liuhaotian/llava-v1.5-mlp2x-336px-pretrain-vicuna-7b-v1.5/tree/main) under your **models** folder.
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) 3. For example image data, I used [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 ### Usage