NAVER CLOVA INFORMATION EXTRACTION

Donut model pre-trained-only. It was introduced in the paper OCR-free Document Understanding Transformer by Geewok et al. and first released in this repository. 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. 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 batchsize, seqlen, hiddensize), after which the decoder autoregressively generates text, conditioned on the encoding of the encoder. This model is meant to be fine-tuned on a downstream task, like document image classification…

Donut model fine-tuned on DocVQA. It was introduced in the paper OCR-free Document Understanding Transformer by Geewok et al. and first released in this repository. 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. 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 batchsize, seqlen, hiddensize), after which the decoder autoregressively generates text, conditioned on the encoding of the encoder. This model is fine-tuned on DocVQA, a document visual question answering dataset. We…