Adapting Pre-trained Language Models to African Languages via Multilingual Adaptive Fine-Tuning
Research
NLP methods
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This paper introduces multilingual adaptive fine-tuning (MAFT) applied to 17 of the most-resourced African languages, producing the AfroXLMR family of models. Removing non-African-script tokens cuts model size by roughly 50 percent while matching the accuracy of single-language adaptation on named entity recognition, topic classification and sentiment analysis.
- Category
- Research
- Pricing
- Free / open
- Country
- 🌍 Pan-African
- Last verified
- 10 Jul 2026
Verification history
- 10 Jul 2026 · live
- 7 Jul 2026 · live
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Tags
nlp
african-languages
fine-tuning
language-models