Datasets:
license: cc-by-sa-4.0
language:
- en
- fr
multilinguality:
- multilingual
task_categories:
- text-generation
- text2text-generation
task_ids:
- language-modeling
tags:
- text-generation
- conditional-text-generation
configs:
- config_name: default
data_files:
- path: data/v*/*parquet
split: train
Corpus overview
Croissant Aligned Instruct is an instruction-formatted version of the parallel French-English data in croissantllm/croissant_dataset_no_web_data (subset: aligned_36b).
The original dataset
The original CroissantAligned dataset contains samples of parallel French/English (or English/French) data from OPUS’13 (99.6% of the data in CroissantAligned), thesis abstracts, and translated song lyrics.
Data extracted from OPUS takes the form of sentences pairs, where one sentence is in French and the other is in English. OPUS pairs were passed through a custom pipeline designed to select the highest quality translation examples. The thesis abstract subset contains thesis abstracts paired with translations written by the thesis authors. The song lyrics are translated by contributors to www.lacoccinelle.net. Parallel data are used to boost the multilingual capabilities of models trained on them (Faysse et al. (2024). "CroissantLLM: A Truly Bilingual French-English Language Model").
Preparation of the instruction dataset
Croissant Aligned Instruct uses the Croissant Aligned data formatted for the Lucie Training Dataset.
Pre-processing of the data for the Lucie Training Dataset proceeded as follows:
Language separation and tagging: The original text field of the Croissant dataset contains a sentence or passage in French or English immediately followed by its translation without any indication of which passage is in which language. The first step was thus to split each text into separate, monolingual passages and tag each passage with the appropriate language code, identified automatically using the langid Python library. In the Lucie Training Dataset, the extra metadata field for CroissantAligned contains separate keys, text_fr for French and text_en for English, that stores the texts separately.
Random combination of texts prefixed by language : To create the text values, each monolingual text was repaired with its translation, but random separators and various methods of prefixing the text with the language (name or code) were added. This was done as a precaution to prevent models trained on this data from switching languages when generating text and can be seen as a very basic instruction to translate the source (first) text into the target (second) text.
To create the instructions, a number of templates were created for the "user" role, e.g. "Transformez ce texte en Francais: {text}" or "Could you translate the provided text from French to English\t {text}". The first member of a language pair was treated as "text" for the user field and the second was treated as the assistant response.
Citation
When using the Croissant Aligned Instruct dataset, please cite the following paper:
✍ Olivier Gouvert, Julie Hunter, Jérôme Louradour, Evan Dufraisse, Yaya Sy, Pierre-Carl Langlais, Anastasia Stasenko, Laura Rivière, Christophe Cerisara, Jean-Pierre Lorré (2025) Lucie-7B LLM and its training dataset
@misc{openllm2023claire,
title={The Lucie-7B LLM and the Lucie Training Dataset:
open resources for multilingual language generation},
author={Olivier Gouvert and Julie Hunter and Jérôme Louradour and Evan Dufraisse and Yaya Sy and Pierre-Carl Langlais and Anastasia Stasenko and Laura Rivière and Christophe Cerisara and Jean-Pierre Lorré},
year={2025},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
Acknowledgements
The Croissant Aligned Dataset was created by Jérôme Louradour on behalf of OpenLLM France.