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LLaVA-Next-Interleave Bench Dataset Card

Dataset details

Dataset type: LLaVA-Next-Interleave Bench is a set of multi-image datasets which are collected from public datasets or generated by GPT-4V API. It is constructed for evaluate large multimodal models for their multi-image capbilities.

Dataset date: LLaVA-Next-Interleave Bench was collected in April 2024, by collecting from public datasets and prompting GPT-4V API.

Paper or resources for more information: https://llava-vl.github.io/blog/2024-06-16-llava-next-interleave/

Evaluate LLaVA-NeXT Interleave Model

Preparation

Please download the evaluation data.

Unzip eval_images.zip and there are Split1 and Split2 in it. Organize the downloaded data into the following structure:


interleave_data
β”œβ”€β”€ Split1
β”‚   β”œβ”€β”€ ...
β”‚   └── ...
|
β”œβ”€β”€ Split2
|   β”œβ”€β”€ ...
β”‚   └── ...
β”œβ”€β”€ multi_image_in_domain.json
β”œβ”€β”€ multi_image_out_domain.json
└── multi_view_in_domain.json

Inference and Evaluation

Example: Please first edit /path/to/ckpt to the path of checkpoint, /path/to/images to the path of "interleave_data" in scripts/interleave/eval_all.sh and then run

bash scripts/interleave/eval_all.sh

License: Creative Commons Attribution 4.0 International; and it should abide by the policy of OpenAI: https://openai.com/policies/terms-of-use

Where to send questions or comments about the model: fliay@connect.ust.hk

Intended use

Primary intended uses: The primary use of LLaVA-Next Interleave is research on large multimodal models and chatbots.

Primary intended users: The primary intended users of the model are researchers and hobbyists in computer vision, natural language processing, machine learning, and artificial intelligence.

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