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+ ---
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+ license: apache-2.0
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+ tags:
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+ - vision
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+ pipeline_tag: image-to-text
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+ ---
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+
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+ # Nougat model, small-sized version
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+
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+ Nougat model trained on PDF-to-markdown. It was introduced in the paper [Nougat: Neural Optical Understanding for Academic Documents](https://arxiv.org/abs/2308.13418) by Blecher et al. and first released in [this repository](https://github.com/facebookresearch/nougat/tree/main).
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+
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+ Disclaimer: The team releasing Nougat 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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+
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+ Note: this model corresponds to the "0.1.0-small" version of the original repository/
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+
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+ ## Model description
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+
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+ Nougat is a [Donut](https://huggingface.co/docs/transformers/model_doc/donut) model trained to transcribe scientific PDFs into an easy-to-use markdown format. The model consists of a Swin Transformer as vision encoder, and an mBART model as text decoder.
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+ The model is trained to autoregressively predict the markdown given only the pixels of the PDF image as input.
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+
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+ <img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/model_doc/nougat_architecture.jpg"
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+ alt="drawing" width="600"/>
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+
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+ <small> Nougat high-level overview. Taken from the <a href="https://arxiv.org/abs/2308.13418">original paper</a>. </small>
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+
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+ ## Intended uses & limitations
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+
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+ You can use the raw model for transcribing a PDF into Markdown. See the [model hub](https://huggingface.co/models?search=nougat) to look for other
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+ fine-tuned versions that may interest you.
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+
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+ ### How to use
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+
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+ We refer to the [docs](https://huggingface.co/docs/transformers/main/en/model_doc/nougat).
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+
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+ ### BibTeX entry and citation info
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+
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+ ```bibtex
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+ @misc{blecher2023nougat,
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+ title={Nougat: Neural Optical Understanding for Academic Documents},
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+ author={Lukas Blecher and Guillem Cucurull and Thomas Scialom and Robert Stojnic},
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+ year={2023},
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+ eprint={2308.13418},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.LG}
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+ }
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+ ```