naver-clova-ix
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donut-base

vision-encoder-decoder

image-text-to-text

Inference Endpoints

Model card Files Files and versions Community

nielsr HF staff commited on Aug 12, 2022

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 # Donut (base-sized model, pre-trained only)
 Donut model pre-trained-only. 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).
 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.
 ## Model description
 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.
 ## Intended uses & limitations
 You can use the raw model for image classification. See the [model hub](https://huggingface.co/models?search=google/vit) to look for

 # Donut (base-sized model, pre-trained only)
 Donut model pre-trained-only. 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).
 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.
 ## Model description
 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.
+![model image](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/model_doc/donut_architecture.jpg)
 ## Intended uses & limitations
 You can use the raw model for image classification. See the [model hub](https://huggingface.co/models?search=google/vit) to look for