license: apache-2.0
library_name: sglang
tags:
- llava
inference: false
pipeline_tag: image-text-to-text
Inference Preparation
This is a fork of liuhaotian/llava-v1.6-mistral-7b to be fully compatible for inference with SGLang. No other changes were made.
LLaVA Model Card
Model details
Model type: LLaVA is an open-source chatbot trained by fine-tuning LLM on multimodal instruction-following data. It is an auto-regressive language model, based on the transformer architecture. Base LLM: mistralai/Mistral-7B-Instruct-v0.2
Model date: LLaVA-v1.6-Mistral-7B was trained in December 2023.
Paper or resources for more information: https://llava-vl.github.io/
License
mistralai/Mistral-7B-Instruct-v0.2 license.
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.
- 500K academic-task-oriented VQA data mixture.
- 50K GPT-4V 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.