layoutlm-document-qa
| Property | Value |
|---|---|
| Parameter Count | 128M |
| License | MIT |
| Framework | PyTorch |
| Downloads | 35,747 |
What is layoutlm-document-qa?
layoutlm-document-qa is a specialized document understanding model developed by Impira that combines visual and textual information processing. It's built on the multi-modal LayoutLM architecture and has been fine-tuned specifically for document question answering tasks using both SQuAD2.0 and DocVQA datasets.
Implementation Details
The model leverages the LayoutLM architecture to process both textual content and spatial layout information from documents. It requires PIL, pytesseract, and PyTorch for operation, making it a comprehensive solution for document analysis.
- Multi-modal architecture combining text and layout understanding
- Fine-tuned on both general QA (SQuAD2.0) and document-specific (DocVQA) datasets
- Supports various document formats including invoices, contracts, and financial statements
Core Capabilities
- Extract specific information from documents through natural language queries
- Process various document types including invoices, contracts, and financial statements
- High accuracy scoring (demonstrated by >99% confidence in example cases)
- Handle complex document structures and layouts
Frequently Asked Questions
Q: What makes this model unique?
This model's uniqueness lies in its ability to understand both the textual content and spatial layout of documents, making it particularly effective for real-world document processing tasks. The combination of SQuAD2.0 and DocVQA training makes it versatile across different document types.
Q: What are the recommended use cases?
The model excels in automated document processing scenarios such as invoice processing, contract analysis, and financial document review. It's particularly useful for tasks requiring specific information extraction from structured documents.
