datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
QariOCR-v0.3-markdown-mixed-dataset
QARI Markdown Mixed Dataset
📋 Dataset Summary
The QARI v0.3 Markdown Mixed Dataset is a specialized synthetic dataset designed for training Arabic OCR models with a focus on complex document layouts and HTML structure understanding.
This dataset is part of the QARI-OCR project, which achieves state-of-the-art performance in Arabic text recognition.
This dataset contains 37,000 synthetically generated Arabic document images (29.6k train, 3.7k… See the full description on the dataset page: https://huggingface.co/datasets/NAMAA-Space/QariOCR-v0.3-markdown-mixed-dataset.safedocs-markdown
SafeDocs PaddleOCR-VL 1.6 production
This public corpus contains exactly 2,000,000 eligible document pages from 355,429 documents processed with PaddleOCR-VL 1.6.
Eligible PDFs contain 1–39 pages and were rendered at 144 DPI. The published reduction is deterministic and document-safe: it retains 1,600 complete ordered Parquet shards (1,999,469 pages), then 103 whole documents from the next shard (531 pages). No document is split across the selection boundary.
The exact public… See the full description on the dataset page: https://huggingface.co/datasets/albertklorer/safedocs-markdown.arabic_doc_to_markdown
Dataset Card for presightai/arabic_doc_to_markdown
This dataset contains OCR image–markdown pairs specifically curated for document structure retrieval and reconstruction tasks,focusing on Arabic and English documents across a variety of domains.
Dataset Summary
Source of Information:This dataset was created by crawling publicly accessible Arabic and English PDFs from:
Official Arabic government document portals
Arabic news websites and online magazines
Community and… See the full description on the dataset page: https://huggingface.co/datasets/presightai/arabic_doc_to_markdown.Viet-Table-MarkdownKITAB_pdf_to_markdown_reviewed
KITAB_pdf_to_markdown_reviewed (Corrected KITAB-Bench PDF→Markdown)
Short description. A carefully reviewed and corrected version of the KITAB-Bench PDF-to-Markdown subset for Arabic document OCR evaluation. We fixed ground-truth errors (hallucinated text, missing page numbers, omissions of small-font text) and standardized formatting to provide a reliable benchmark for model comparison.
TL;DR
✅ Human-verified ground truth for Arabic PDF→Markdown
✅ Removes hallucinations and fills… See the full description on the dataset page: https://huggingface.co/datasets/Misraj/KITAB_pdf_to_markdown_reviewed.khmer-doc-markdown-pdf-kh3Image-2-Markdown
Image-to-Markdown
100,000 (page image, OCR markdown) pairs for training/evaluating document OCR
and image-to-markdown models.
Columns
image: a rendered image of a single PDF page (grayscale, longest side 1536px).
text: the OCR transcription in olmOCR's markdown dialect (LaTeX for equations,
HTML for tables,  tags for figures/diagrams).
pdf_relpath, url, page_number, primary_language, is_table, is_diagram:
carried-over metadata.
How it was… See the full description on the dataset page: https://huggingface.co/datasets/DBlake-BoxedLogic/Image-2-Markdown.arabic-ocr-markdown-dataset
Arabic Document OCR Markdown Dataset
Dataset Description
This dataset contains 1,256 pairs of document images and their corresponding Markdown representations, specifically designed for Arabic document OCR tasks. The dataset is intended for training and evaluating models that convert document images into structured Markdown text (image-to-markdown OCR).
Features
The dataset consists of two main features:
image: Document images in various formats
markdown:… See the full description on the dataset page: https://huggingface.co/datasets/Omar-youssef/arabic-ocr-markdown-dataset.Text-to-Markdowndotsocr-markdown-dataset
dotsocr_markdown_dataset
Dataset Description
This dataset contains training data for DotsOCR to convert document images directly to markdown format.
Training Objective
The model learns to:
Convert document images to clean markdown format
Preserve document structure and hierarchy
Extract all text content accurately
Use appropriate markdown formatting for different content types
Dataset Structure
Training samples: 798
Validation samples: 200
Total… See the full description on the dataset page: https://huggingface.co/datasets/rita1706/dotsocr-markdown-dataset.OCR-Markdown-Dense-200x
OCR-Markdown-Dense-200x
Overview
OCR-Markdown-Dense-200x is a synthetic dataset designed for dense document OCR tasks. It focuses on extracting structured HTML/Markdown representations from densely packed document pages.
The dataset is generated using outputs from open multimodal models, making it suitable for training and evaluating:
Image-to-Text models
Image-to-Markdown/HTML models
Document understanding systems
OCR post-processing pipelines
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/prithivMLmods/OCR-Markdown-Dense-200x.v7_markdown_basearabic_to_markdown
arabic_to_markdown
This is a subset of an Arabic document-to-markdown dataset for multimodal model fine-tuning.
Format: Image + Markdown text
Samples: ~50
Usage:
from datasets import load_dataset
ds = load_dataset("Salmankotakuth/arabic_to_markdown")