Offline AI For African Languages: Model as a Library Architecture

Although large language models are often recommended as a solution of artificial intelligence applications in developing areas, reality is more complex. Especially in African languages these models perform the lowest performance and remain insufficient in places where you need it.

Basic problems include:

-Source failure: All African languages have low source status according to standard criteria Tags

• Dalekt and regional difference: Standard texts collected from the web represent wrong people’s actual forms of speech
• Local binding incompatible: General purpose models meet specific regional needs Tags
• Unfair access: In areas with low internet infrastructure, internet dependence was created Tags

Research published in arXiv introduces a new software architecture called **Model as a Library (MaaL). This approach predicts models as modular libraries that can work locally instead of central servers. Thus, African communities will be able to access solutions developed by offline and community that reflect the properties of their own languages better.

This approach opens the way artificial intelligence is accessible and effective for all people, not only for languages with high source.