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inference: false |
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pipeline_tag: image-text-to-text |
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# LLaVA Model Card |
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## Model details |
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**Model type:** |
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Follows LLaVA, CCA-LLaVA(arxiv.org/abs/2410.15926) is an open-source chatbot trained by fine-tuning LLaMA/Vicuna on GPT-generated multimodal instruction-following data. |
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It is an auto-regressive language model, based on the transformer architecture. |
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**Model date:** |
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CCA-LLaVA-v1.5-7B was trained in April 2024. |
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**Paper or resources for more information:** |
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https://github.com/xing0047/cca-llava.git |
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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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**Where to send questions or comments about the model:** |
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https://github.com/xing0047/cca-llava/issues |
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## Intended use |
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**Primary intended uses:** |
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The primary use of CCA-LLaVA is research on large multimodal models and chatbots. |
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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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## 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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- 450K academic-task-oriented VQA data mixture. |
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- 40K ShareGPT data. |
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## Evaluation dataset |
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A collection of 8 benchmarks, including 3 visual hallucination benchmarks and 5 recent benchmarks specifically proposed for instruction-following LMMs. |
