---
datasets:
- liuhaotian/LLaVA-Pretrain
pipeline_tag: visual-question-answering
---

<div align="center">
  <img src="https://github.com/InternLM/lmdeploy/assets/36994684/0cf8d00f-e86b-40ba-9b54-dc8f1bc6c8d8" width="600"/>


[![Generic badge](https://img.shields.io/badge/GitHub-%20XTuner-black.svg)](https://github.com/InternLM/xtuner)


</div>

## Model

llava-llama-3-8b-pretrain is a LLaVA projector pretrained from [Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) and [CLIP-ViT-Large-patch14-336](https://huggingface.co/openai/clip-vit-large-patch14-336) on [LLaVA-Pretrain](https://huggingface.co/datasets/liuhaotian/LLaVA-Pretrain) dataset by [XTuner](https://github.com/InternLM/xtuner).

The fine-tuned LLaVA model can be found on [xtuner/llava-llama-3-8b](https://huggingface.co/xtuner/llava-llama-3-8b).

## Citation

```bibtex
@misc{2023xtuner,
    title={XTuner: A Toolkit for Efficiently Fine-tuning LLM},
    author={XTuner Contributors},
    howpublished = {\url{https://github.com/InternLM/xtuner}},
    year={2023}
}
```