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Layoutlmv3 Finetuned Docvqa
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Layoutlmv3 Finetuned Docvqa

Developed by am-infoweb
Document question answering model fine-tuned based on LayoutLMv3-base, suitable for document visual question answering tasks
Image-to-Text
Transformers
#Document Visual Question Answering#Multimodal Understanding#Structured Text Analysis
Downloads 22
Release Time : 9/5/2023

Model Overview

This model is a document understanding model based on Microsoft's LayoutLMv3 architecture, specifically fine-tuned for Document Visual Question Answering (DocVQA) tasks, capable of understanding document layouts and text content to answer questions

Model Features

Document Layout Understanding
Capable of processing both text content and document layout information simultaneously
Visual Question Answering Capability
Specifically optimized for document visual question answering tasks
Multimodal Processing
Combines textual and visual information for comprehensive understanding

Model Capabilities

Document Understanding
Visual Question Answering
Text Position Recognition
Document Content Analysis

Use Cases

Document Processing
Form Information Extraction
Extract specific information from structured documents and answer questions
Contract Analysis
Understand contract document content and answer related questions
Education
Automated Test Grading
Analyze student answer sheets and evaluate answer correctness
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