|
--- |
|
license: mit |
|
tags: |
|
- donut |
|
- image-to-text |
|
- vision |
|
--- |
|
|
|
# Donut (base-sized model, fine-tuned on CORD) |
|
|
|
Donut model fine-tuned on CORD. 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 |
|
|
|
This model is fine-tuned on CORD, a document parsing dataset. |
|
|
|
We refer to the [documentation](https://huggingface.co/docs/transformers/main/en/model_doc/donut) which includes code examples. |
|
|
|
## CORD Dataset |
|
|
|
CORD: A Consolidated Receipt Dataset for Post-OCR Parsing. |
|
 |
|
|
|
|
