Cascading Adaptors to Leverage English Data to Improve Performance of Question Answering for Low-Resource Languages
Paper • 2112.09866 • Published
How to use bhavikardeshna/multilingual-bert-base-cased-vietnamese with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("question-answering", model="bhavikardeshna/multilingual-bert-base-cased-vietnamese") # Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("bhavikardeshna/multilingual-bert-base-cased-vietnamese")
model = AutoModelForQuestionAnswering.from_pretrained("bhavikardeshna/multilingual-bert-base-cased-vietnamese")YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
@misc{pandya2021cascading,
title={Cascading Adaptors to Leverage English Data to Improve Performance of Question Answering for Low-Resource Languages},
author={Hariom A. Pandya and Bhavik Ardeshna and Dr. Brijesh S. Bhatt},
year={2021},
eprint={2112.09866},
archivePrefix={arXiv},
primaryClass={cs.CL}
}