# OCR-Donut-CORD

**Repository Path**: hf-models/OCR-Donut-CORD

## Basic Information

- **Project Name**: OCR-Donut-CORD
- **Description**: OCR-Donut-CORD 是一种针对文字识别的模型。它通过深度学习技术实现对图片中文字的快速识别，具有高度的准确性和效率，适用于各种文字识别任务。
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 1
- **Forks**: 0
- **Created**: 2023-10-25
- **Last Updated**: 2025-01-10

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

---
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. 

![model image](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/model_doc/donut_architecture.jpg)

## 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. 
![cord](https://github.com/clovaai/cord/blob/master/figure/sample.png?raw=true)