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

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# LLaVA Model Card

## Model details

**Model type:**
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.
It is an auto-regressive language model, based on the transformer architecture.

**Model date:**
CCA-LLaVA-v1.5-7B was trained in April 2024.

**Paper or resources for more information:**
https://github.com/xing0047/cca-llava.git

## 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/xing0047/cca-llava/issues

## Intended use
**Primary intended uses:**
The primary use of CCA-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 8 benchmarks, including 3 visual hallucination benchmarks and 5 recent benchmarks specifically proposed for instruction-following LMMs.