Donut Sroie Company Sample Demo
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Donut Sroie Company Sample Demo
Developed by Chan-yeong
Donut is a Transformer-based document understanding model specifically designed for document question-answering tasks.
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Release Time : 4/26/2025
Model Overview
Donut is a Transformer-based document understanding model capable of extracting information from documents and answering questions. It is particularly suitable for information extraction tasks involving structured documents (e.g., invoices, receipts).
Model Features
Document Understanding
Capable of extracting and comprehending information from structured documents (e.g., invoices, receipts).
Transformer-based
Leverages the powerful capabilities of the Transformer architecture to process visual and linguistic information.
End-to-End Training
Supports end-to-end training and inference, simplifying the document processing pipeline.
Model Capabilities
Document Information Extraction
Visual Question Answering
Structured Document Processing
Use Cases
Business Document Processing
Invoice Information Extraction
Automatically extracts key information (e.g., amount, date, vendor) from invoices.
Improves data entry efficiency and reduces manual errors.
Receipt Analysis
Analyzes receipt content to automatically categorize and record expenses.
Simplifies financial management and reimbursement processes.
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