Wolof-Adapted Industry-Ready Open-Weight Language Models

Gwénolé Lecorvé, Delphine Charlet, Pierre Adam, Floriane Behanzin, Lionel Delphin-Poulat +13 more
10/14/2026
cs.CLcs.AI

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Abstract

Wolof is spoken by 23M people, mostly in Senegal, but remains weakly supported by open-weight language models, while API models raise cost, governance, and sovereignty constraints for local deployments. In this paper, we present 0.6B-14B open-weight models adapted to Wolof through instruction tuning, preference alignment, and model merging. After presenting the pipeline and data, extensive experiments on 63~public and in-house tasks show good performance on Wolof understanding and generation while remaining effective on other languages and cross-lingual skills, with the 8B and 14B models being particularly competitive with substantially larger commercial systems. The models are currently being evaluated in internal customer-care pilots and are publicly available at https://huggingface.co/collections/Orange/wolof-lm .

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@article{lecorv2026wolofadapted,
  title  = {Wolof-Adapted Industry-Ready Open-Weight Language Models},
  author = {Gwénolé Lecorvé and Delphine Charlet and Pierre Adam and Floriane Behanzin and Lionel Delphin-Poulat and Johannes Heinecke and Géraldine Damnati and Pelin Kaytmaz and Nourredine Khaous and Charbel Kindji and Meriam Maadi and Abdoulaye Mbaye and Claire Perroux and Ismaël Rousseau and Papa Séga Wadé and Gilles Xiberras and Olivier Zhang and Malek Zitouni},
  year   = {2026},
  eprint = {2610.20824},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2610.20824v1}
}

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