rajpurkar/squad
Viewer • Updated • 98.2k • 150k • 363
How to use Dingyun-Huang/oe-roberta-base-qa with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("question-answering", model="Dingyun-Huang/oe-roberta-base-qa") # Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("Dingyun-Huang/oe-roberta-base-qa")
model = AutoModelForQuestionAnswering.from_pretrained("Dingyun-Huang/oe-roberta-base-qa")The OE-RoBERTa model is domain adapted from RoBERTa-base over research literature in optoelectronics. The adapted model is then fine-tuned on SQuAD v1.1 for question answering capabilities.
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("question-answering", model="Dingyun-Huang/oe-roberta-base-qa")
BibTeX:
@article{doi:10.1021/acs.jcim.4c02029,
author = {Huang, Dingyun and Cole, Jacqueline M.},
title = {Cost-Efficient Domain-Adaptive Pretraining of Language Models for Optoelectronics Applications},
journal = {Journal of Chemical Information and Modeling},
volume = {65},
number = {5},
pages = {2476-2486},
year = {2025},
doi = {10.1021/acs.jcim.4c02029},
note ={PMID: 39933074},
URL = {
https://doi.org/10.1021/acs.jcim.4c02029
},
eprint = {
https://doi.org/10.1021/acs.jcim.4c02029
}
}
Base model
FacebookAI/roberta-base