metadata

library_name: transformers
license: apache-2.0
datasets:
  - liuhaotian/LLaVA-Instruct-150K
pipeline_tag: image-text-to-text

Model Card: LLaVA_MORE-llama_3_1-8B-siglip-finetuning

LLaVA-MORE enhances the well-known LLaVA architecture by integrating the use of LLaMA 3.1 as the language model. We are publicly releasing the checkpoints for stages one and two for the first model with 8B parameters.

In this model space, you will find the stage two (finetuning) weights of LLaVA-MORE LLaMA 3.1 8B.

For more information, visit our LLaVA-MORE repository.

Inference

You can try our LLaVA-MORE in the Image-To-Text task by cloning our repository and running the following script.

python -u llava/eval/run_llava.py --model-path "aimagelab/LLaVA_MORE-llama_3_1-8B-S2-finetuning"

Citation

If you make use of our work, please cite our repo:

@misc{cocchi2024llavamore,
title={{LLaVA-MORE: Enhancing Visual Instruction Tuning with LLaMA 3.1}},
author={Cocchi, Federico and Moratelli, Nicholas and Caffagni, Davide and Sarto, Sara and Cornia, Marcella and Baraldi, Lorenzo and Cucchiara, Rita},
url={https://github.com/aimagelab/LLaVA-MORE},
year={2024}
}