--- 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](https://huggingface.co/datasets/HuggingFaceFW/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](https://arxiv.org/abs/2605.31401)). ## Citation ```bibtex @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}} } ``` ```bibtext @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}, } ```