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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-13B was trained in November 2023.

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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