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---
base_model:
- mistralai/Mistral-7B-Instruct-v0.3
datasets:
- NingLab/MMECInstruct
license: cc-by-4.0
pipeline_tag: image-text-to-text
library_name: transformers
---
# CASLIE-M
This repository contains the CASLIE-M model presented in the paper [Captions Speak Louder than Images: Generalizing Foundation Models for E-commerce from High-quality Multimodal Instruction Data](https://huggingface.co/papers/2410.17337).
Project page: https://ninglab.github.io/CASLIE/
Code: https://github.com/ninglab/CASLIE
## CASLIE Models
The CASLIE-M model is instruction-tuned from the medium-size base model [Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3).
## Sample Usage
To conduct inference, run `python inference.py --model_path $model_path --task $task --output_path $output_path`.
`$model_path` is the path of the instruction-tuned model.
`$task` specifies the task to be tested.
`$output_path` specifies the path where you want to save the inference output.
Example:
```bash
python inference.py --model_path NingLab/CASLIE-M --task answerability_prediction --output_path ap.json
```
## Citation
```bibtex
@article{ling2024captions,
title={Captions Speak Louder than Images (CASLIE): Generalizing Foundation Models for E-commerce from High-quality Multimodal Instruction Data},
author={Ling, Xinyi and Peng, Bo and Du, Hanwen and Zhu, Zhihui and Ning, Xia},
journal={arXiv preprint arXiv:2410.17337},
year={2024}
}
``` |