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# ViP-LLaVA Model Card
## Model details
**Model type:**
ViP-LLaVA is an open-source chatbot trained by fine-tuning LLaMA/Vicuna on both image level instruction data and region-level instruction data annotated with visual prompts.
It is an auto-regressive language model, based on the transformer architecture.
**Model date:**
ViP-LLaVA-7B was trained in November 2023. [Paper](https://arxiv.org/abs/2312.00784)
**Paper or resources for more information:**
https://vip-llava.github.io/
## License
Llama 2 is licensed under the LLAMA 2 Community License,
Copyright (c) Meta Platforms, Inc. All Rights Reserved.
**Where to send questions or comments about the model:**
https://github.com/mu-cai/ViP-LLaVA/issues
## Intended use
**Primary intended uses:**
The primary use of ViP-LLaVA 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.
## Training dataset
- 558K filtered image-text pairs from LAION/CC/SBU, captioned by BLIP.
- 665K image level instruction data from LLaVA-1.5.
- 520K image-text pairs marked with visual prompts.
- 13K region-level instruction data generated from GPT-4V.
## Evaluation dataset
ViP-LLaVA achieves state-of-the-art performance in 4 academic region-level benchmarks and our newly proposed RegionBench.
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