metadata
license: odc-by
language:
- ro
dataset_info:
features:
- name: id
dtype: string
- name: images
sequence: image
- name: text
dtype: string
- name: messages
list:
- name: role
dtype: string
- name: content
dtype: string
splits:
- name: train
num_bytes: 282401531337.178
num_examples: 379198
download_size: 303410496330
dataset_size: 282401531337.178
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
Dataset Description
FinePDFs is the largest publicly available corpus sourced exclusively from PDFs, containing about 3 trillion tokens across 475 million documents in 1733 languages.
Here we provide the Romanian split of FinePDFs training set, prepared for OCR: pairs of images (pages) and extracted text. This dataset is part of the instruction finetune protocol for Romanian VLMs proposed in "Înțelegi românește?" A Recipe for Romanian Vision-Language Models (Masala et al., 2026).
Citation
@misc{kydlicek2025finepdfs,
title={FinePDFs},
author={Hynek Kydl{\'\i}{\v{c}}ek and Guilherme Penedo and Leandro von Werra},
year={2025},
publisher = {Hugging Face},
journal = {Hugging Face repository},
howpublished = {\url{https://huggingface.co/datasets/HuggingFaceFW/finepdfs}}
}
@misc{masala2026intelegi,
title={``\^{I}n\c{t}elegi Rom\^{a}ne\c{s}te?'' A Recipe for Romanian Vision-Language Models},
author={Mihai Masala and Marius Leordeanu and Mihai Dascalu and Traian Rebedea},
year={2026},
eprint={2605.31401},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2605.31401},
}