nileagi-nym
Collection
Runyambo (Orunyambo) Swahili↔Runyambo lexical MT (NileAGI). • 3 items • Updated
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Runyambo MT
Authors: Zephania and Isack Odero
Swahili → Runyambo (Orunyambo) lexical / phrase machine translation. Fine-tuned from NLLB-200 distilled 600M.
This is not sentence bitext MT. Prefer short lemmas and dictionary-style phrases.
| Lite sibling | nileagi/nileagi-nym-mt-lite |
| Reverse | nileagi/nileagi-nym-mt-rev |
| Collection | nileagi/nileagi-nym |
| Technical report | TECHNICAL_REPORT.tex |
Quick example
Always set the source language to swh_Latn and force the Runyambo BOS token nym_Latn. If you skip that, output will not match this card.
Summary
| Task | Lexical / phrase MT |
| Direction | Swahili → Runyambo |
| Language codes | swh_Latn → nym_Latn |
| Base | facebook/nllb-200-distilled-600M |
| Primary metric | chrF2 |
Evaluation
Held-out test. Identity baseline (copy Swahili) ≈ chrF2 8.0.
| System | Test chrF2 | BLEU | exact % |
|---|---|---|---|
| This SKU (600M) | 16.6 | 0.0 | 0.0 |
| Lite (1.3B) | 16.6 | 3.4 | 0.2 |
| Tiny Aya LoRA | 10.0 | 0.0 | 0.0 |
A mid-teens chrF2 means stems are often partially recovered; surfaces are not reliable dictionary lookups. Research preview only.
How to use
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
tok = AutoTokenizer.from_pretrained("nileagi/nileagi-nym-mt", use_fast=False)
model = AutoModelForSeq2SeqLM.from_pretrained("nileagi/nileagi-nym-mt")
tok.src_lang = "swh_Latn"
inputs = tok("habari", return_tensors="pt")
bos = tok.convert_tokens_to_ids("nym_Latn")
out = model.generate(**inputs, forced_bos_token_id=bos, max_new_tokens=64)
print(tok.decode(out[0], skip_special_tokens=True))
HTTP API
On the NileAGI host: port 8096 (nileagi-nym-mt-api).
Intended use
- Lexicon lookup / short phrase Swahili → Runyambo
- Research on low-resource Bantu MT
Out of scope
- Full-sentence or document translation
- Runyambo → Swahili (use the reverse SKU)
- Direct English → Runyambo
- Chat, legal, medical, news
- Commercial products without a NileAGI licence
Limitations
- Trained on dictionary-style phrases; sentence quality is weak
- Decode can insert spaces inside Runyambo words; prefer chrF2 over BLEU
- Research preview scores — not a substitute for a human lexicographer
Related
- Lite:
nileagi/nileagi-nym-mt-lite - Reverse:
nileagi/nileagi-nym-mt-rev - Sukuma MT:
nileagi/nileagi-suk-mt
Access
Weights are gated under CC BY-NC-SA 4.0.
- Open Request access and describe your intended use.
- After approval, authenticate (
hf auth loginorHF_TOKEN) and load the model.
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-nym-mt-2026,
title = {Runyambo machine translation (Swahili to Runyambo)},
author = {Zephania and Isack Odero},
year = {2026},
howpublished = {Hugging Face},
url = {https://huggingface.co/nileagi/nileagi-nym-mt},
note = {NileAGI}
}
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