SciBERT-SQuAD-QuAC
This is the SciBERT language representation model fine tuned for Question Answering. SciBERT is a pre-trained language model based on BERT that has been trained on a large corpus of scientific text. When fine tuning for Question Answering we combined SQuAD2.0 and QuAC datasets.
If using this model, please cite the following paper:
@inproceedings{otegi-etal-2020-automatic,
title = "Automatic Evaluation vs. User Preference in Neural Textual {Q}uestion{A}nswering over {COVID}-19 Scientific Literature",
author = "Otegi, Arantxa and
Campos, Jon Ander and
Azkune, Gorka and
Soroa, Aitor and
Agirre, Eneko",
booktitle = "Proceedings of the 1st Workshop on {NLP} for {COVID}-19 (Part 2) at {EMNLP} 2020",
month = dec,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/2020.nlpcovid19-2.15",
doi = "10.18653/v1/2020.nlpcovid19-2.15",
}
- Downloads last month
- 82
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.