Matryoshka Query Transformer for Large Vision-Language Models
Paper • 2405.19315 • Published • 1
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
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.
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