from transformers import AutoModelForSeq2SeqLM, AutoTokenizer

model = AutoModelForSeq2SeqLM.from_pretrained("cif-ai/nllb-tarjumi")
tokenizer = AutoTokenizer.from_pretrained("cif-ai/nllb-tarjumi")

tokenizer.src_lang = "eng_Latn"
inputs = tokenizer("Hello, how are you?", return_tensors="pt")
tgt_id = tokenizer.convert_tokens_to_ids("kik_Latn")

translated = model.generate(**inputs, forced_bos_token_id=tgt_id, max_new_tokens=128)
print(tokenizer.decode(translated[0], skip_special_tokens=True))

Product

Base model: facebook/nllb-200-distilled-600M
Method: LoRA (rank-16, alpha-32)
Corpus: 124K parallel pairs (Bible + JW300)
Hardware: NVIDIA H100 80GB
Training time: 13 minutes
Cost: ~$0.75

This model powers Tarjumi — a free translation service for African mother-tongue languages.

Built by CIF AI.