Preparing Dataset for Donut Fine-Tuning (part 1, Document AI)

I explain the dataset I will be using to fine-tune Donut model. I show how PDFs are converted to image files for further processing and OCR data extraction. In the next step, JSON data is converted to the format understandable by Sparrow annotation processing/review tool.

 

How To Fine-tune Donut Model

Donut is an awesome Document AI model to extract data from docs. I share my experiences in fine-tuning the model, with CORD dataset, based on example from Transformers Tutorials.

 

Donut 🍩 - ChatGPT for Document AI

Donut - OCR-free Document Understanding Transformer. This ML model can process documents (images, scans) and return JSON structured info about the content. It works for different use cases: form understanding, visual question answering about the document, document image classification.

 

Best Platform for Python Apps Deployment - Hugging Face Spaces with Docker

I walk through Hugging Face Spaces Docker SDK deployment option. I was using it to deploy our Streamlit/Python app Sparrow. So far very happy with Spaces Docker SDK - simple setup, very stable and good runtime performance, HTTPS out of the box, content compression out of the box too.