LayoutLM Large Uncased
| Property | Value |
|---|---|
| Parameters | 343M |
| Architecture | 24-layer, 1024-hidden, 16-heads |
| Training Data | 11M documents, 2 epochs |
| Paper | arXiv:1912.13318 |
| Author | Microsoft |
What is layoutlm-large-uncased?
LayoutLM Large Uncased is a sophisticated multimodal pre-trained model designed specifically for document AI tasks. It uniquely combines text, layout/format, and image information to understand document structure and content. Developed by Microsoft, this large variant contains 343M parameters and was trained on 11 million documents.
Implementation Details
The model features a robust architecture with 24 transformer layers, 1024 hidden dimensions, and 16 attention heads. It's built on a pre-training methodology that incorporates both textual and spatial information from documents, making it particularly effective for document understanding tasks.
- 24-layer transformer architecture
- 1024-dimensional hidden states
- 16 attention heads
- 343M total parameters
- Trained on IIT-CDIP Test Collection 1.0
Core Capabilities
- Document layout analysis
- Form understanding
- Receipt processing
- Information extraction
- Document image understanding
Frequently Asked Questions
Q: What makes this model unique?
LayoutLM's uniqueness lies in its ability to jointly process text, layout, and visual information from documents, making it particularly effective for tasks requiring understanding of document structure and content relationships.
Q: What are the recommended use cases?
The model excels in document AI tasks such as form understanding, receipt processing, and information extraction from structured documents. It's particularly useful for applications requiring understanding of both text content and spatial layout.
