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StructTable InternVL2 1B

StructEqTable-Deploy: A High-efficiency Open-source Toolkit for Table-to-Latex Transformation

TipoText modelVersiónmodel

Fuente del modelo

Tipo
Text model
Tamaño del archivo
1,75 GB
Versión
vmodel
Actualizado
17 sept 2026
Descargas
1,6 mil
Tareas
Descripción
Fuente
Hugging Face

Extracto de la fuente

StructEqTable-Deploy: A High-efficiency Open-source Toolkit for Table-to-Latex Transformation

Fuentes

1 fuente
Hugging FacePrincipalVersión 7f46f7b8172568a455b423956ecb65b340a944ed
huggingface.co/InternScience/StructTable-InternVL2-1B/tree/7f46f7b8172568a455b423956ecb65b340a944ed

Verificado 17 sept

Artefactos del modelo

1 artefacto

model.safetensors

safetensors · 1,75 GB · SHA-256 59901e249fd2…57fb · Hugging Face

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Extractos de fuentes

2 extractos

--- language: - en - zh pipeline_tag: image-to-text inference: false license: apache-2.0 --- <div align="center"> <h1>StructEqTable-Deploy: A High-efficiency Open-source Toolkit for Table-to-Latex Transformation</h1> [[ Github Repo ]](https://github.com/UniModal4Reasoning/StructEqTable-Deploy) [[ Related Paper ]](https://arxiv.org/abs/2505.16938) [[ Website ]](https://discovery.intern-ai.org.cn/home) [[ Dataset🤗 ]](https://huggingface.co/datasets/U4R/DocGenome/tree/main) [[ Models🤗 ]](https://huggingface.co/U4R/StructTable-InternVL2-1B/tree/main) [[ Demo💬 ]](https://www.modelscope.cn/studios/HongbinZhou/StructEqTable-Demo/) </div> Welcome to the official repository of StructEqTable-Deploy, a solution that converts images of Table into LaTeX/HTML/MarkDown, powered by scalable data from [DocGenome benchmark](https://unimodal4reasoning.github.io/DocGenome_page/). ## Overview Table is an effective way to represent structured data in scientific publications, financial statements, invoices, web pages, and many other scenarios. Extracting tabular data from a visual table image and performing the downstream reasoning tasks according to the extracted data is challenging, mainly due to that tables often present complicated column and row headers with spanning cell operation. To address these challenges, we present TableX, a large-scale multi-modal table benchmark extracted from [DocGenome benchmark](https://unimodal4reasoning.github.io/DocGenome_page/) for table pre-training, comprising more than 2 million high-quality Image-LaTeX pair data covering 156 disciplinary classes. Besides, benefiting from such large-scale data, we train an end-to-end model, StructEqTable, which provides the capability to precisely obtain the corresponding LaTeX description from a visual table image and perform multiple table-related reasoning tasks, including structural extraction and question answering, broadening its application scope and potential. ## Changelog - [2024/12/12] 🔥 We have released latest model **[StructTable-InternVL2-1B v0.2](https://huggingface.co/U4R/StructTable-InternVL2-1B/tree/main)** with enhanced recognition stability for HTML and Markdown formats! - [2024/10/19] We have released our latest model StructTable-InternVL2-1B! Thanks to IntenrVL2 powerful foundational capabilities, and through fine-tuning on the synthetic tabular data and DocGenome dat...

Source context: 1578 downloads · 49 likes · Pipeline image-to-text · Repo InternScience/StructTable-InternVL2-1B