# Invoice Information Extraction

A YOLOv8-based object detection model specialized in extracting structured information from documents such as invoices and receipts.

A multimodal LayoutLM model fine-tuned for invoice and other document QA tasks, supporting discontinuous text recognition

A document Q&A model based on the Donut architecture, capable of extracting text information from images and answering questions

A document QA model fine-tuned based on the LayoutLM architecture, specifically designed for processing discontinuous text recognition in invoices and other documents

Invoice information extraction model fine-tuned based on Donut architecture, enabling OCR-free document understanding

An invoice recognition model fine-tuned based on LayoutLMv3-base, trained on the wild_receipt dataset, excelling in extracting structured information from invoices.

A document QA model fine-tuned based on the LayoutLM architecture, specifically designed for handling invoice and other document QA tasks

Donut is an OCR-free document understanding Transformer model, fine-tuned on the DocVQA dataset, capable of directly extracting and comprehending text information from images.

A version of LayoutLMv3-base fine-tuned on an invoice dataset for invoice information extraction