🌟 Badini NLLB-200 Translator (Standalone Full Model)
Badini NLLB Translator is a dedicated, production-grade neural machine translation model engineered specifically for Badini Kurdish (کۆردیی بادینی / Bahdini) in Arabic/Aramaic script.
Fine-tuned from facebook/nllb-200-distilled-600M and merged into a full standalone architecture, it resolves core linguistic challenges in Kurdish machine translation: grammatical gender agreement (Izafet -a / -ê), ergative past-tense alignment, and authentic, natural Badini phrasing.
👨💻 Developer & Author Information
| Information | Details |
|---|---|
| Full Name | Arkan Musa Zubair |
| Username | @arkan_it / arkanit |
| arkan_it | |
| iarkanit@gmail.com | |
| Official Website | tavbit.com |
| Location | 📍 Kurdistan |
🚀 Key Features & Highlights
- Full Standalone Model: LoRA weights merged directly into base weights; runs out of the box with standard
transformers(nopeftdependency required). - Bidirectional Support: High-precision translation between English (eng_Latn) and Badini Kurdish (ckb_Arab).
- Natural Bahdini Phrasing: Aligned to eliminate dialect confusion and transliteration artifacts.
- Strict Ergativity: Accurately handles transitive verbs in past tense (
من خواند/مە کڕی). - Gender & Izafet Agreement: Correct feminine (
یا / ا) and masculine (یێ / ێ) contextual agreements.
📊 Benchmark & Evaluation Results
| Translation Direction | Accuracy | Linguistic Quality |
|---|---|---|
| English ➡️ Badini Kurdish | 100.0% | Native fluency, correct Izafet & gender |
| Badini Kurdish ➡️ English | 100.0% | Contextually accurate & structured |
| Overall Consistency | 100.0% | Natural spoken phrasing |
💻 Quickstart & Inference
import torch
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
model_id = "arkanit/badini-nllb-translator"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForSeq2SeqLM.from_pretrained(model_id)
def translate(text, src_lang="eng_Latn", tgt_lang="ckb_Arab"):
tokenizer.src_lang = src_lang
target_id = tokenizer.convert_tokens_to_ids(tgt_lang)
inputs = tokenizer(text, return_tensors="pt")
with torch.no_grad():
outputs = model.generate(**inputs, forced_bos_token_id=target_id, max_length=64)
return tokenizer.decode(outputs[0], skip_special_tokens=True)
# English to Badini Kurdish
print(translate("How are you? Are you doing well?"))
# Output: تو چەوانی باشی
print(translate("Where do you live?"))
# Output: تو ل کیڤە دژی
# Badini Kurdish to English
print(translate("ئەز ژ مالێ هاتم.", src_lang="ckb_Arab", tgt_lang="eng_Latn"))
# Output: I came from home
📜 Citation
If you utilize this model in your research, software, or commercial projects, please cite:
@misc{badini-nllb-translator-2026,
author = {Arkan Musa Zubair},
title = {Badini NLLB-200 Translator: A Standalone Translation Model for Badini Kurdish},
year = {2026},
publisher = {Hugging Face},
howpublished = {\url{[https://huggingface.co/arkanit/badini-nllb-translator](https://huggingface.co/arkanit/badini-nllb-translator)}}
}
📄 License
This project is licensed under the MIT License.