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InkubaLM: A small language model for low-resource African languages

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arxiv 2408.17024 v2 pith:WXXRBJ3W submitted 2024-08-30 cs.CL

Atnafu Lambebo Tonja , Bonaventure F. P. Dossou , Jessica Ojo , Jenalea Rajab , Fadel Thior , Eric Peter Wairagala , Anuoluwapo Aremu , Pelonomi Moiloa
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Jade Abbott Vukosi Marivate Benjamin Rosman
This is my paper · ORCID
classification cs.CL
keywords modelslanguageinkubalmlanguagesmodelafricandatalarger
verification ladder T0 review T1 audit T2 compute T3 formal
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High-resource language models often fall short in the African context, where there is a critical need for models that are efficient, accessible, and locally relevant, even amidst significant computing and data constraints. This paper introduces InkubaLM, a small language model with 0.4 billion parameters, which achieves performance comparable to models with significantly larger parameter counts and more extensive training data on tasks such as machine translation, question-answering, AfriMMLU, and the AfriXnli task. Notably, InkubaLM outperforms many larger models in sentiment analysis and demonstrates remarkable consistency across multiple languages. This work represents a pivotal advancement in challenging the conventional paradigm that effective language models must rely on substantial resources. Our model and datasets are publicly available at https://huggingface.co/lelapa to encourage research and development on low-resource languages.

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Cited by 4 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. KinyaColBERT: A Lexically Grounded Retrieval Model for Low-Resource Retrieval-Augmented Generation

    cs.CL 2025-07 conditional novelty 5.0 of 10

    KinyaColBERT, a morphology-aware two-tier ColBERT retriever, reports large MRR gains over multilingual baselines and commercial APIs on a new Kinyarwanda agricultural retrieval benchmark.

  2. HausaNLP: Current Status, Challenges and Future Directions for Hausa Natural Language Processing

    cs.CL 2025-05 conditional novelty 4.0 of 10

    A review of Hausa NLP that catalogs existing datasets and tools and launches the HausaNLP Catalogue as a central access point.

  3. The Human Labour of Data Work: Capturing Cultural Diversity through World Wide Dishes

    cs.CY 2025-02 conditional novelty 4.0 of 10

    A design retrospective of World Wide Dishes identifies three dimensions of community ambassador labor, trust building, accessibility, and cultural contextualization, as essential to participatory dataset creation.

  4. LLMs and Agentic AI in Insurance Decision-Making: Opportunities and Challenges For Africa

    cs.CE 2025-08 unverdicted novelty 3.0 of 10

    LLMs and agentic AI are presented as a transformative opportunity for African insurance, with a call for African-led, equitable AI strategies.

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