ExllamaV2 version of the model created by liuhaotian
Requires ExllamaV2, which is being developed by turboderp
https://github.com/turboderp/exllamav2 under an MIT license.
Main branch is 8bpw 8h (req 18gb)
5b8h branch is 5bpw 8h (req 14gb)
LLaVA Model Card
Model details
Model type:
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:
LLaVA-v1.5-13B was trained in September 2023.
Paper or resources for more information:
https://llava-vl.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/haotian-liu/LLaVA/issues
Intended use
Primary intended uses:
The primary use of 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 12 benchmarks, including 5 academic VQA benchmarks and 7 recent benchmarks specifically proposed for instruction-following LMMs.
