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WindyWord/translate-en-sit
translate-en-sit is a translation model from WindyWord. Use it when you need text moved from one language to another. It is set up for transformers. The card lists the license as apache-2.0.
Part of the Windstorm Labs open model catalogue. Scores, licence and attribution for every model: https://windytranslate.com/models/translate-en-sit Canonical copy: https://huggingface.co/WindyTranslate/translate-en-sit
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Updated Oct 1, 2026
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From the Hugging Face model README
Part of the Windstorm Labs open model catalogue. Scores, licence and attribution for every model: https://windytranslate.com/models/translate-en-sit
Canonical copy: https://huggingface.co/WindyTranslate/translate-en-sit
Translates English → Sino-Tibetan (Mandarin, Cantonese, Tibetan, Burmese).
No quality score is published in this repository. Current screening scores, where measured, are on the catalogue page linked above.
Deployment formats in this repository (subfolders):
| Variant | Description |
|---|---|
lora/ | WindyStandard — production baseline. Transformers format for GPU inference. |
lora-ct2-int8/ | WindyStandard · CPU INT8 — CTranslate2 INT8 quantization of WindyStandard for CPU inference. |
herm0/ | WindyEnhanced — further fine-tuned on the OPUS-100, Tatoeba and WikiMatrix parallel corpora. |
herm0-ct2-int8/ | WindyEnhanced · CPU INT8 — CTranslate2 INT8 quantization of WindyEnhanced. |
Transformers (PyTorch):
from transformers import MarianMTModel, MarianTokenizer
tokenizer = MarianTokenizer.from_pretrained("WindyWord/translate-en-sit", subfolder="lora")
model = MarianMTModel.from_pretrained("WindyWord/translate-en-sit", subfolder="lora")
CTranslate2 (fast CPU inference):
import ctranslate2
translator = ctranslate2.Translator("path/to/translate-en-sit/lora-ct2-int8")
The Windy Word apps are built on this model family.
Weights derived from Helsinki-NLP/opus-mt-en-sit (OPUS-MT, Helsinki-NLP, University of Helsinki), licensed Apache-2.0. Windy variants are released under the same licence.