Model Introduction
LLaMA-E is meticulously crafted for e-commerce authoring tasks, incorporating specialized features to excel in generating product descriptions, advertisements, and other related content, as outlined in https://arxiv.org/abs/2308.04913#/.
Usage
Inference using Huggingface transformers on NVIDIA GPUs. Requirements tested on python 3.10:
python inference.py --load_8bit --base_model 'meta-llama/Llama-2-7b-hf' --lora_weights 'DSMI/LLaMA-E'
***Instruction: Where can I buy the handmade jewellery?
***Response: Etsy, NOVICA, UncommonGoods, World Market, and Global Crafts offer unique handmade jewelry from artisans worldwide.
***Instruction: Create an attractive advertisement for the Christmas sale of the following product.
***Input: Custom Photo Music Plaque,Personalized Photo Frame,Album Cover Song Plaque,Music Photo Name Night Lamp,Photo and Music Gift, Music Prints
***Response: Personalize your music space with a Custom Photo Music Plaque. Add your favorite photo and song lyrics to create a unique gift for music lovers.
Citation
If you find our work helpful, please consider citing the following papers.
@article{shi2023llama,
title={LLaMA-E: Empowering E-commerce Authoring with Multi-Aspect Instruction Following},
author={Shi, Kaize and Sun, Xueyao and Wang, Dingxian and Fu, Yinlin and Xu, Guandong and Li, Qing},
journal={arXiv preprint arXiv:2308.04913},
year={2023}
}
License
The model released here is under the Llama-2 LICENSE to ensure more flexible accessibility; please adhere to the corresponding licence.
Acknowledgements
Our code for the inference is based on the tloen.
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