layoutlmv2-base-uncased
Maintainer: microsoft - Last updated 9/6/2024
Property | Value |
---|---|
Run this model | Run on HuggingFace |
API spec | View on HuggingFace |
Github link | No Github link provided |
Paper link | No paper link provided |
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Model overview
LayoutLMv2
is a multimodal AI model developed by Microsoft that is designed for understanding visually-rich document understanding. It builds upon the original LayoutLM model by introducing new pre-training tasks to better model the interaction between text, layout, and images. This improved version outperforms strong baselines and achieves new state-of-the-art results on a variety of document understanding tasks.
Compared to similar models like [object Object], LayoutLMv2
is a monolingual English model, while LayoutXLM adds support for multilingual document understanding. [object Object] and [object Object] represent the latest advancements in the LayoutLM series, with a unified architecture and training objectives for both text-centric and image-centric document AI tasks.
Model inputs and outputs
LayoutLMv2
takes in multimodal document data, including the text content, layout/formatting information, and images. The model can then be used to perform a variety of downstream tasks, such as document classification, information extraction, and visual question answering.
Inputs
- Text content of the document
- Bounding box coordinates and other layout/formatting features
- Document images
Outputs
- Task-specific outputs, such as:
- Document classification labels
- Extracted entities or key information
- Answers to visual questions about the document
Capabilities
LayoutLMv2
excels at understanding the complex relationships between text, layout, and visual elements in documents. For example, it can accurately extract structured information from forms and receipts by jointly modeling the text content and visual cues. It also achieves state-of-the-art performance on document visual question answering, where the model must reason about both the textual and visual aspects of the document.
What can I use it for?
LayoutLMv2
is a powerful tool for automating various document processing tasks, such as invoice and contract analysis, document classification, and information extraction. It can be particularly useful for companies dealing with visually-rich documents, as it can significantly improve the accuracy and efficiency of these operations compared to traditional approaches.
Things to try
One interesting aspect of LayoutLMv2
is its ability to handle non-consecutive tokens when extracting information from documents. Unlike many QA models that can only predict contiguous text spans, LayoutLMv2
can identify and extract relevant information even when it is spread across multiple locations on the page. This can be especially useful for tasks like address extraction, where the relevant information may be split across multiple lines.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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