From 9b6b4474187e0a4aa348fc1e4ec97ddde866d534 Mon Sep 17 00:00:00 2001 From: Niels Rogge Date: Fri, 12 Aug 2022 16:42:08 +0000 Subject: [PATCH] Update README.md --- README.md | 3 +++ 1 file changed, 3 insertions(+) diff --git a/README.md b/README.md index 719e643..358287a 100644 --- a/README.md +++ b/README.md @@ -7,12 +7,15 @@ tags: # 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