%20--%3e%3cdefs%3e%3cstyle%3e%20.st0%20{%20fill:%20%23061b40;%20}%20.st1%20{%20fill:%20%23306af1;%20}%20.st2%20{%20fill:%20%235ce5cf;%20}%20%3c/style%3e%3c/defs%3e%3cg%3e%3cpath%20class='st0'%20d='M55,10.5h9v3h-9v9h12V7.5h-12v3ZM64,19.5h-6v-3h6v3Z'/%3e%3cpolygon%20class='st0'%20points='69%2016.5%2078%2016.5%2078%2019.5%2069%2019.5%2069%2022.5%2081%2022.5%2081%2013.5%2072%2013.5%2072%2010.5%2081%2010.5%2081%207.5%2069%207.5%2069%2016.5'/%3e%3cpolygon%20class='st0'%20points='95%2010.5%2095%207.5%2083%207.5%2083%2022.5%2095%2022.5%2095%2019.5%2086%2019.5%2086%2016.5%2095%2016.5%2095%2013.5%2086%2013.5%2086%2010.5%2095%2010.5'/%3e%3cpath%20class='st0'%20d='M40,1.5v21h11.6l1.4-1.4v-7.6h0c0,0-1.4-1.5-1.4-1.5l1.4-1.4V2.9l-1.4-1.4h-11.6ZM50,19.5h-7v-6h7v6ZM50,10.5h-7v-6h7v6Z'/%3e%3c/g%3e%3cpath%20class='st1'%20d='M23.1,24L14.7,4.8l-4.9,11.2h3.8l-1.8,4H3.3L12.1,0H2C.9,0,0,.9,0,2v20c0,1.1.9,2,2,2h21.1Z'/%3e%3cpath%20class='st2'%20d='M34,0h-16.8l10.6,24h6.2c1.1,0,2-.9,2-2V2C36,.9,35.1,0,34,0ZM32.5,20h-4V4h4v16Z'/%3e%3c/svg%3e)
Layoutlm Invoices
A document QA model fine-tuned based on the LayoutLM architecture, specifically designed for processing structured documents like invoices
Downloads 100
Release Time : 12/20/2022
Model Overview
This model is a fine-tuned version of the multimodal LayoutLM architecture, specifically designed for question-answering tasks involving invoices and other documents. It supports recognition of discontinuous text sequences and excels in invoice data extraction.
Model Features
Discontinuous Text Recognition
Predicts long-distance discontinuous text sequences through an additional classification head, solving the problem where traditional models can only predict continuous text fragments
Multi-dataset Fine-tuning
Fine-tuned on proprietary invoice datasets, SQuAD2.0, and DocVQA datasets, combining general QA and document visual QA capabilities
Invoice-specific Optimization
Specifically optimized for invoice document structures, excelling in extracting key information such as invoice numbers and amounts
Model Capabilities
Invoice Information Extraction
Document Visual Question Answering
Discontinuous Text Recognition
Structured Document Processing
Use Cases
Financial Automation
Invoice Number Extraction
Accurately extract invoice numbers from invoice documents
Successfully identifies cross-line discontinuous text
Purchase Amount Recognition
Extract purchase amount information from contracts or invoices
Accurately recognizes amounts in different formats
Document Processing
Contract Key Information Extraction
Extract key clauses and date information from contract documents
SafetensorsFeatured Recommended AI Models
Š 2025AIbase