🏬QAmden🏬: Question-Answering-based Multi-DocumENt model

HF-version of the QAmden model: 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')

model = LEDForConditionalGeneration.from_pretrained('biu-nlp/QAmden')

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}
}