morisien-embed — Mauritian Creole embeddings
A text embedding model for Kreol Morisien. It measures the meaning of a sentence, so sentences that mean the same thing sit close together — even in different languages. Type below and see for yourself.
Enter any two sentences — Creole, English, French, or a mix — and see how close their meanings are.
Type a Creole sentence; the model finds the closest match among the candidates. Edit the candidates to try your own.
Good to know
What this is (and is not)
It reads a sentence and produces a vector — numbers that stand for the sentence's meaning. Two sentences with the same meaning get near-identical vectors, which is what powers semantic search and cross-language matching. It is not a chatbot and not a translator: it never writes text back. It is the understanding layer that sits underneath such tools.
Limitations — please read before judging a result
- Not native-perfect. On the formal-register benchmark it ranks the correct match first about 94% of the time — strong, but below a native speaker.
- Register skew. The public training data leans towards religious text, politics and literature. Street Creole, slang and SMS-style spelling perform worse.
- This demo runs a compressed (int8) copy of the model so it can load in your browser. Scores are close to, but not identical to, the full model — the ordering of results is preserved. For exact numbers, use the model from the repository.
- This is version 0.1.0, trained on ~35,000 sentence pairs — effectively all the public Creole parallel data that exists today.
Feedback — I would genuinely like to hear from you
This model is for the Mauritian Creole community, and your feedback is what makes it better, especially from native speakers. Tried it and it got something wrong — a bad match, an odd score, slang it misunderstands? Please tell me; that is exactly the signal the next version needs. Questions and doubts are welcome too. Leave a note in the Community tab of this Space, or open an issue on GitHub. No feedback is too small.