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Layoutlm Invoices
A document QA model fine-tuned based on the LayoutLM architecture, specifically designed for handling invoice and other document QA tasks
Downloads 75.42k
Release Time : 9/6/2022
Model Overview
This model is a fine-tuned version based on the multimodal LayoutLM architecture, specifically designed for handling invoice and other document QA tasks. Its training data incorporates proprietary invoice datasets, the SQuAD2.0 QA dataset, and the DocVQA document visual QA dataset to achieve general comprehension capabilities.
Model Features
Discontinuous Text Recognition
Through an additional classifier head, it can predict discontinuous text sequences across regions, solving the problem where traditional QA models can only predict continuous text segments.
Multimodal Understanding
Combines text and layout information to understand the visual structure and content of documents.
Invoice-Specific Optimization
Specifically optimized for invoice processing, capable of accurately extracting key information such as invoice numbers and purchase amounts.
Model Capabilities
Document QA
Invoice Information Extraction
Discontinuous Text Recognition
Multimodal Document Understanding
Use Cases
Document Processing
Invoice Information Extraction
Extract key information such as numbers and amounts from invoices
Accurately identifies discontinuous text, such as two-line address information
Contract Analysis
Extract key clauses and data from contract documents
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