# Structured Information Extraction

A document Q&A model fine-tuned based on LayoutLMv3-base, capable of understanding documents using OCR data and answering related questions.

A version fine-tuned for 1 day using the Docmatix dataset (5% data volume) based on Microsoft's Florence-2 model, suitable for image-text understanding tasks

ICKG is a knowledge graph construction-specific instruction-following language model fine-tuned based on Vicuna-7B, excelling in extracting structured knowledge triples from text documents

A 7-billion-parameter model based on LLamA v1 for key information extraction from receipts in English and Arabic

This is a vision-language model based on the Donut architecture, specifically fine-tuned for the CORD-V2 dataset for document image-to-text tasks.

A triple extraction model fine-tuned based on the Flan-T5-XL model, used to identify subject-relation-object structures from text

A Transformer model based on the Donut architecture, specifically designed for extracting structured information from driver's license images

A model based on the Donut architecture, specifically designed for extracting information from medical handwritten prescriptions.

An invoice information extraction model fine-tuned based on the LayoutLMv3 architecture, demonstrating outstanding performance on the SROIE dataset

A document understanding model fine-tuned based on LayoutLMv3-base, specifically designed for named entity recognition tasks on the CORD dataset

A fine-tuned version of the LayoutLMv3-large model based on the FUNSD dataset, specializing in document intelligence understanding tasks

A document AI model fine-tuned on the FUNSD dataset based on the LayoutLMv3-base model, designed for form understanding tasks

A document understanding model fine-tuned on the CORD dataset based on the LayoutLMv2 architecture, suitable for structured document information extraction tasks

A document visual question answering model based on the LayoutLMv2 architecture, fine-tuned for document understanding tasks