57 lines
2.3 KiB
Markdown
57 lines
2.3 KiB
Markdown
---
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license: mit
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pipeline_tag: document-question-answering
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tags:
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- donut
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- image-to-text
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- vision
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widget:
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- text: "What is the invoice number?"
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src: "https://huggingface.co/spaces/impira/docquery/resolve/2359223c1837a7587402bda0f2643382a6eefeab/invoice.png"
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- text: "What is the purchase amount?"
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src: "https://huggingface.co/spaces/impira/docquery/resolve/2359223c1837a7587402bda0f2643382a6eefeab/contract.jpeg"
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---
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# Donut (base-sized model, fine-tuned on DocVQA)
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Donut model fine-tuned on DocVQA. It was introduced in the paper [OCR-free Document Understanding Transformer](https://arxiv.org/abs/2111.15664) by Geewok et al. and first released in [this repository](https://github.com/clovaai/donut).
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Disclaimer: The team releasing Donut did not write a model card for this model so this model card has been written by the Hugging Face team.
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## Model description
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Donut consists of a vision encoder (Swin Transformer) and a text decoder (BART). Given an image, the encoder first encodes the image into a tensor of embeddings (of shape batch_size, seq_len, hidden_size), after which the decoder autoregressively generates text, conditioned on the encoding of the encoder.
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## Intended uses & limitations
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This model is fine-tuned on DocVQA, a document visual question answering dataset.
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We refer to the [documentation](https://huggingface.co/docs/transformers/main/en/model_doc/donut) which includes code examples.
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### BibTeX entry and citation info
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```bibtex
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@article{DBLP:journals/corr/abs-2111-15664,
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author = {Geewook Kim and
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Teakgyu Hong and
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Moonbin Yim and
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Jinyoung Park and
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Jinyeong Yim and
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Wonseok Hwang and
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Sangdoo Yun and
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Dongyoon Han and
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Seunghyun Park},
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title = {Donut: Document Understanding Transformer without {OCR}},
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journal = {CoRR},
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volume = {abs/2111.15664},
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year = {2021},
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url = {https://arxiv.org/abs/2111.15664},
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eprinttype = {arXiv},
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eprint = {2111.15664},
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timestamp = {Thu, 02 Dec 2021 10:50:44 +0100},
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biburl = {https://dblp.org/rec/journals/corr/abs-2111-15664.bib},
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bibsource = {dblp computer science bibliography, https://dblp.org}
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}
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``` |