Yashsonaar/LayoutLMv3-Fine-Tuning

Welcome to the LayoutLMv3 Fine-Tuning project! 🚀 This project focuses on extracting structured data from invoices and PDFs using LayoutLMv3, PaddleOCR, and Label Studio. The system extracts key fields like invoice number, date, vendor GSTIN, PAN, product description, rate, quantity, and amount.

27
/ 100
Experimental

This project helps businesses automate the painful process of extracting specific data from invoice PDFs, including scanned versions. It takes your invoices, whether digital or scanned, and pulls out key details like invoice numbers, dates, vendor information, product descriptions, rates, quantities, and amounts. This tool is for accounts payable teams, finance departments, or anyone who regularly processes a high volume of invoices.

No commits in the last 6 months.

Use this if you need to quickly and accurately extract structured data from diverse invoice formats to streamline your accounting or record-keeping workflows.

Not ideal if you only process a handful of invoices occasionally or need to extract data from a wider variety of document types beyond invoices.

invoice-processing accounts-payable financial-automation data-entry document-management
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 8 / 25
Community 14 / 25

How are scores calculated?

Stars

12

Forks

3

Language

Python

License

Last pushed

Jan 06, 2025

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/Yashsonaar/LayoutLMv3-Fine-Tuning"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.