🏬QAmden🏬: Question-Answering-based Multi-DocumENt model
HF-version of the QAmden model fine-tuned over multinews: Peek Across: Improving Multi-Document Modeling via Cross-Document Question-Answering (ACL 2023).
You can use it by
from transformers import (
AutoTokenizer,
LEDConfig,
LEDForConditionalGeneration,
)
# load model and tokenizer
tokenizer = AutoTokenizer.from_pretrained('biu-nlp/QAmden')
config=LEDConfig.from_pretrained('biu-nlp/QAmden-multinews')
model = LEDForConditionalGeneration.from_pretrained('biu-nlp/QAmden-multinews')
The original repo is here.
If you find our work useful, please cite the paper as:
@article{caciularu2023peekacross,
title={Peek Across: Improving Multi-Document Modeling via Cross-Document Question-Answering},
author={Caciularu, Avi and Peters, Matthew E and Goldberger, Jacob and Dagan, Ido and Cohan, Arman},
journal={The 61st Annual Meeting of the Association for Computational Linguistics: ACL 2023},
year={2023}
}
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