Instructions to use nileagi/nileagi-suk-mt-rev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nileagi/nileagi-suk-mt-rev with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("translation", model="nileagi/nileagi-suk-mt-rev")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("nileagi/nileagi-suk-mt-rev") model = AutoModelForSeq2SeqLM.from_pretrained("nileagi/nileagi-suk-mt-rev", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Sukuma MT (reverse)
Authors: Zephania and Isack Odero
Sukuma → Swahili machine translation for the macron orthography (ā ē ī ō ū). Reads Sukuma text and writes Swahili text.
Companion to the forward SKU nileagi/nileagi-suk-mt (Swahili → Sukuma).
| Forward (quality) | nileagi/nileagi-suk-mt |
| Forward (lite) | nileagi/nileagi-suk-mt-lite |
| Collection | nileagi/nileagi-suk |
Summary
| Task | Machine translation |
| Direction | Sukuma → Swahili |
| Language codes | suk_Latn → swh_Latn |
| Base | facebook/nllb-200-distilled-600M |
| Orthography | Latin with vowel macrons (input) |
| Primary metric | chrF2 |
| Test chrF2 | 39.5 · BLEU 11.7 |
Held-out document-group test. Prefer chrF2; BLEU is secondary.
How to use
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
tok = AutoTokenizer.from_pretrained("nileagi/nileagi-suk-mt-rev", use_fast=False)
model = AutoModelForSeq2SeqLM.from_pretrained("nileagi/nileagi-suk-mt-rev")
tok.src_lang = "suk_Latn"
inputs = tok("Ūlī mhola?", return_tensors="pt")
bos = tok.convert_tokens_to_ids("swh_Latn")
out = model.generate(**inputs, forced_bos_token_id=bos, max_new_tokens=128)
print(tok.decode(out[0], skip_special_tokens=True))
Always set suk_Latn and force BOS swh_Latn.
Intended use
- Literary / read-aloud Sukuma → Swahili
- Research on low-resource Bantu MT
Out of scope
- Direct English ↔ Sukuma
- Chat, legal, medical, or news translation
- Conversational or social-media Sukuma without macrons (domain shift)
- Commercial products without a NileAGI licence
Limitations
- Literary macron orthography; macron-free input looks like domain shift
- Research-preview scores — not a substitute for a human translator
- Names and rare stems are often approximated
Access
Weights are gated under CC BY-NC-SA 4.0.
Attribute NileAGI. Adapted weights must stay CC BY-NC-SA 4.0. Commercial: hi@nileagi.com.
License
Weights: CC BY-NC-SA 4.0.
See LICENSE and NOTICE.md.
Citation
@misc{nileagi-suk-mt-rev-2026,
title = {Sukuma machine translation (Sukuma to Swahili)},
author = {Zephania and Isack Odero},
year = {2026},
howpublished = {Hugging Face},
url = {https://huggingface.co/nileagi/nileagi-suk-mt-rev},
note = {NileAGI}
}
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