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+ ---
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+ inference: false
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+ ---
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+
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+ <br>
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+ <br>
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+
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+ # LLaVA Model Card
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+
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+ ## Model details
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+
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+ **Model type:**
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+ LLaVA is an open-source chatbot trained by fine-tuning LLM on multimodal instruction-following data.
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+ It is an auto-regressive language model, based on the transformer architecture.
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+ Base LLM: [lmsys/vicuna-13b-v1.5](https://huggingface.co/lmsys/vicuna-13b-v1.5)
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+
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+ **Model date:**
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+ LLaVA-v1.6-Vicuna-13B was trained in December 2023.
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+
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+ **Paper or resources for more information:**
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+ https://llava-vl.github.io/
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+
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+ ## License
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+ Llama 2 is licensed under the LLAMA 2 Community License,
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+ Copyright (c) Meta Platforms, Inc. All Rights Reserved.
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+
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+ **Where to send questions or comments about the model:**
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+ https://github.com/haotian-liu/LLaVA/issues
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+
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+ ## Intended use
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+ **Primary intended uses:**
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+ The primary use of LLaVA is research on large multimodal models and chatbots.
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+
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+ **Primary intended users:**
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+ 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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+
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+ ## Training dataset
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+ - 558K filtered image-text pairs from LAION/CC/SBU, captioned by BLIP.
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+ - 158K GPT-generated multimodal instruction-following data.
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+ - 500K academic-task-oriented VQA data mixture.
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+ - 50K GPT-4V data mixture.
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+ - 40K ShareGPT data.
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+
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+ ## Evaluation dataset
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+ A collection of 12 benchmarks, including 5 academic VQA benchmarks and 7 recent benchmarks specifically proposed for instruction-following LMMs.