metadata
library_name: transformers
license: mit
datasets:
- YuukiAsuna/VietnameseTableVQA
language:
- vi
base_model:
- naver-clova-ix/donut-base
pipeline_tag: document-question-answering
Model Card for Model ID
VieTable Donut DocVQA is a fine-tuned version of the Donut model for the Vietnamese DocVQA (Table data)
BibTeX entry and citation info
@article{DBLP:journals/corr/abs-2111-15664,
author = {Geewook Kim and
Teakgyu Hong and
Moonbin Yim and
Jinyoung Park and
Jinyeong Yim and
Wonseok Hwang and
Sangdoo Yun and
Dongyoon Han and
Seunghyun Park},
title = {Donut: Document Understanding Transformer without {OCR}},
journal = {CoRR},
volume = {abs/2111.15664},
year = {2021},
url = {https://arxiv.org/abs/2111.15664},
eprinttype = {arXiv},
eprint = {2111.15664},
timestamp = {Thu, 02 Dec 2021 10:50:44 +0100},
biburl = {https://dblp.org/rec/journals/corr/abs-2111-15664.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}