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X→français and a français→X model. The models were
trained on a corpus we compiled by hand — scripture as the aligned backbone plus
gathered books, pamphlets and other written material — normalised under the AGLC
alphabet (Alphabet Général des Langues Camerounaises). Background: the
research log.flagship-ai/cameroon-int8.
These fp32 weights are the originals / reference.1from transformers import MarianMTModel, MarianTokenizer
2
3model = MarianMTModel.from_pretrained("flagship-ai/fufulde-francais")
4# Shared SentencePiece tokenizer ships in the int8 bundle subfolders:
5tok = MarianTokenizer.from_pretrained("flagship-ai/cameroon-int8", subfolder="fufulde-francais")
6
7ids = tok("...", return_tensors="pt")
8print(tok.decode(model.generate(**ids)[0], skip_special_tokens=True))