# Structured data extraction

RT-DETR-L_wireless_table_cell_det is a high-precision table cell detection model designed specifically for table recognition tasks. It can accurately locate and mark each cell area in the table image.

RT-DETR-L_wired_table_cell_det is a key module in the table recognition task, mainly responsible for locating and marking each cell area in the table image.

Qwen2.5-VL-32B-Instruct is a powerful vision-language model with enhanced mathematical and problem-solving abilities, suitable for multimodal tasks.

Qwen2.5-VL-32B-Instruct is the latest vision - language model in the Qwen family, with powerful multimodal understanding and generation capabilities, supporting the interaction of images, videos, and text.

Gemma-2-2B-TR-Knowledge-Graph is a model fine-tuned based on gemma-2-2b-it, focusing on generating structured knowledge graphs from document content.

A model based on the Donut architecture, specifically fine-tuned for Latvian receipt data

This model is a fine-tuned version of donut-base on a Latvian receipt dataset, primarily used for receipt image processing tasks

A fine-tuned invoice information extraction model based on LayoutLMv3-base on the SROIE dataset, excelling in token classification tasks