Community masterclass on Transformer architecture and its mathematical foundations, open to all.
You can use a model without understanding how it works. You cannot adapt one to a low-resource language without that. Which is the whole point of a masterclass that goes at the mathematics rather than the surface.
The mathematics behind the models
In July 2025 a masterclass on Transformers and large language models ran in Kara on the 14th and 15th, then in Lomé on the 18th and 19th. It was delivered by Togo Data Lab at the initiative of the ministry responsible for the digital economy, and led by Dr Pagdame Tiébékabé, a lecturer-researcher in mathematics at the University of Kara.
The programme went straight at the foundations: the attention mechanism, vector representations, encoding — the machinery that actually makes a model run, with theory and Python side by side.
Why it matters for African languages
The choices that decide whether a model can handle Ewe or Kabiyè are not made at the interface. They are made in tokenisation, in how sounds are represented, in how attention treats sequences it was never calibrated for. Those are mathematical decisions.
- Tokenisation designed for English segments a tonal language badly.
- A small corpus forces architectural trade-offs an abundant one never raises.
- Without understanding the mechanism, you observe that a model fails without knowing why.
A series, not a one-off
Togo Data Lab runs these back to back. After Transformers in July, a “Generative AI and common goods” session ran in September in Kara and Lomé, then a masterclass on AI for healthcare access in rural areas. The turnout at each says enough about the need.
Train locally, or depend indefinitely
Umbaji follows these initiatives closely, for a simple reason: technical skill in Togolese languages will not arrive from outside. It forms on the ground, in rooms like this one, in people who speak the languages concerned and understand how the models work. Both halves are necessary, and it is their meeting that is rare.
Do you teach, research, or want to contribute to the corpus that makes these models possible? Let's talk.
