README.md

metadata

dataset_info:
  features:
    - name: source
      dtype: string
    - name: target
      dtype: string
    - name: src_lang
      dtype: string
    - name: tgt_lang
      dtype: string
  splits:
    - name: train
      num_bytes: 1195761745
      num_examples: 3218822
  download_size: 733073516
  dataset_size: 1195761745
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
language:
  - ar
  - am
  - af
  - arz
  - es
  - en
  - fr
  - ha
  - ln
  - pt
  - so
  - sw
  - wo
  - yo
  - zu
license: cc-by-nc-4.0
task_categories:
  - translation
size_categories:
  - 1M<n<10M

AfriNLLB Dataset

AfriNLLB is a series of efficient multilingual open-source models for African languages. AfriNLP/AfriNLLB-train is one of two datasets we curated and used for training AfriNLLB models. It comprises datasets from OPUS and Hugging Face, with additional data from GitHub and other publicly available online sources. Moreover, AfriNLP/AfriNLLB-train is the authentic dataset used to create the knowledge distillation dataset AfriNLLB-train-distilled More details about data sources and processing can be found in the paper.

Supported Languages

AfriNLLB supports 15 language pairs (30 translation directions), including Swahili, Hausa, Yoruba, Amharic, Somali, Zulu, Lingala, Afrikaans, Wolof, and Egyptian Arabic, as well as other African Union official languages such as Arabic (MSA), French, Portuguese, and Spanish. Our training data covers bidirectional translation between English and 13 languages, and between French and two languages (Lingala and Wolof).

Citation

If you use any of AfriNLLB models, datasets, or approaches, please cite the following paper:

@inproceedings{moslem-etal-2026-afrinllb,
    title = "{A}fri{NLLB}: Efficient Translation Models for African Languages",
    author = "Moslem, Yasmin  and
      Wassie, Aman Kassahun  and
      Gizachew, Amanuel",
    booktitle = "Proceedings of the Seventh Workshop on African Natural Language Processing (AfricaNLP)",
    month = jul,
    year = "2026",
    address = "Rabat, Morocco",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/2602.09373"
}