MAUD: An Expert-Annotated Legal NLP Dataset for Merger Agreement Understanding
Paper • 2301.00876 • Published
How to use TracyWang/MAUD_KWM_AWS_Roberta-base with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="TracyWang/MAUD_KWM_AWS_Roberta-base") # Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("TracyWang/MAUD_KWM_AWS_Roberta-base")
model = AutoModelForQuestionAnswering.from_pretrained("TracyWang/MAUD_KWM_AWS_Roberta-base")Dataset and Training Script offered by the Atticus Project MAUD.
Trained on AWS Sagemaker with 4 A10 GPUs.
Model owned by King & Wood Mallesons Law Firm AI LAB.
Project Member:
Reference:
@misc{wang2023maud,
title={MAUD: An Expert-Annotated Legal NLP Dataset for Merger Agreement Understanding},
author={Steven H. Wang and Antoine Scardigli and Leonard Tang and Wei Chen and Dimitry Levkin and Anya Chen and Spencer Ball and Thomas Woodside and Oliver Zhang and Dan Hendrycks},
year={2023},
eprint={2301.00876},
archivePrefix={arXiv},
primaryClass={cs.CL}
}