README.md

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}
}