AIbase
EN
Home
Layoutlmv2 Base Uncased Finetuned Docvqa V2
L

Layoutlmv2 Base Uncased Finetuned Docvqa V2

Developed by MariaK
This model is a fine-tuned version of microsoft/layoutlmv2-base-uncased for document visual question answering tasks, focusing on processing text and layout information in document images.
Image-to-Text
Transformers
#Document Visual Question Answering#Layout Understanding#OCR Enhancement
Downloads 54
Release Time : 2/9/2023

Model Overview

The LayoutLMv2 model combines text, layout, and visual information specifically for document understanding tasks. This fine-tuned version is optimized for Document Visual Question Answering (DocVQA) tasks.

Model Features

Multimodal Understanding
Simultaneously processes textual content, spatial layout, and visual features in documents
Document QA Capability
Provides accurate textual answers to questions about document images
Layout Awareness
Understands spatial arrangement relationships of text in documents to enhance semantic understanding

Model Capabilities

Document Image Understanding
Visual Question Answering
Text Layout Analysis
Multimodal Information Processing

Use Cases

Document Processing
Form Information Extraction
Extract specific field information from scanned form documents
Contract Analysis
Answer specific questions about contract document content
Education
Automated Test Grading
Analyze student answer sheets and respond to grading-related questions
Featured Recommended AI Models
AIbase
Empowering the Future, Your AI Solution Knowledge Base
EnglishįŽ€äŊ“中文įšéĢ”中文ãĢãģんご
Š 2025AIbase