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Sharka/
CIVQA_LayoutXLM

Name: CIVQA_LayoutXLM
Availability: InStock

transformers

pytorch

layoutlmv2

document-question-answering

document question answering

fimu-docproc-research/CIVQA-TesseractOCR

mit

endpoints_compatible

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LayoutXLM Model Fine-tuned with CIVQA (Tesseract) dataset

This is a fine-tuned version of the LayoutXLM model, which was trained on Czech Invoice Visual Question Answering (CIVQA) datasets containing invoices in the Czech language.

This model enables Document Visual Question Answering on Czech invoices.

All invoices used in this dataset were obtained from public sources. Over these invoices, we were focusing on 15 different entities, which are crucial for processing the invoices.

Invoice number
Variable symbol
Specific symbol
Constant symbol
Bank code
Account number
ICO
Total amount
Invoice date
Due date
Name of supplier
IBAN
DIC
QR code
Supplier's address

You can find more information about this model in this paper.

Sharka/CIVQA_LayoutXLM

LayoutXLM Model Fine-tuned with CIVQA (Tesseract) dataset

Sharka/
CIVQA_LayoutXLM