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PrimeQA/tydi-reader_bpes-xlmr_large-20221117
tydi-reader_bpes-xlmr_large-20221117 is a machine learning model from PrimeQA. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
An XLM-RoBERTa Large reading comprehension model initialized from nqtydisq1-xlmrlarge-20221110 with continued training on TyDi QA with passage answer spans used for the begin and end of boolean questions.
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From the Hugging Face model README
An XLM-RoBERTa Large reading comprehension model initialized from nq_tydi_sq1-xlmr_large-20221110 with continued training on TyDi QA with passage answer spans used for the begin and end of boolean questions.
You can use the raw model for the reading comprehension task. Biases associated with the pre-existing language model, xlm-roberta-large, that we used may be present in our fine-tuned model.
You can use this model directly with the PrimeQA pipeline for reading comprehension squad.ipynb.
@article{Rosenthal2021DoAT,
title={Do Answers to Boolean Questions Need Explanations? Yes},
author={Sara Rosenthal and Mihaela A. Bornea and Avirup Sil and Radu Florian and Scott McCarley},
journal={ArXiv},
year={2021},
volume={abs/2112.07772}
}
@misc{https://doi.org/10.48550/arxiv.2206.08441,
author = {McCarley, Scott and
Bornea, Mihaela and
Rosenthal, Sara and
Ferritto, Anthony and
Sultan, Md Arafat and
Sil, Avirup and
Florian, Radu},
title = {GAAMA 2.0: An Integrated System that Answers Boolean and Extractive Questions},
journal = {CoRR},
publisher = {arXiv},
year = {2022},
url = {https://arxiv.org/abs/2206.08441},
}