DALE: Generative Data Augmentation for Low-Resource Legal NLP
Paper • 2310.15799 • Published
How to use ckevuru/DALE with Transformers:
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("ckevuru/DALE")
model = AutoModelForSeq2SeqLM.from_pretrained("ckevuru/DALE")This model is created as part of the EMNLP 2023 paper: DALE: Generative Data Augmentation for Low-Resource Legal NLP. The code for the git repo can be found here.
If you find our paper/code/demo useful, please cite our paper:
@misc{ghosh2023dale,
title={DALE: Generative Data Augmentation for Low-Resource Legal NLP},
author={Sreyan Ghosh and Chandra Kiran Evuru and Sonal Kumar and S Ramaneswaran and S Sakshi and Utkarsh Tyagi and Dinesh Manocha},
year={2023},
eprint={2310.15799},
archivePrefix={arXiv},
primaryClass={cs.CL}
}