--- inference: false pipeline_tag: image-text-to-text ---

# MQT-LLaVA Model Card ## Model details **Model type:** MQT-LLaVA is an open-source chatbot trained by fine-tuning LLaMA/Vicuna on GPT-generated multimodal instruction-following data. It is an auto-regressive language model, based on the transformer architecture. **Model date:** MQT-LLaVA-7B was trained in May 2024. [Paper](https://arxiv.org/abs/2405.19315) ## 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/gordonhu608/MQT-LLaVA/issues ## Intended use **Primary intended uses:** The primary use of MQT-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. - 158K GPT-generated multimodal instruction-following data. - 450K academic-task-oriented VQA data mixture. - 40K ShareGPT data. ## Evaluation dataset A collection of 11 benchmarks, including 4 academic VQA benchmarks and 7 recent benchmarks specifically proposed for instruction-following LMMs.