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WindyTranslate/translate-de-da
translate-de-da is a translation model from WindyTranslate. 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-de-da
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.safetensors294 MB · 99%
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-de-da
Machine translation model, de to da, published by Windstorm Labs.
Derived from Helsinki-NLP/opus-mt-de-da, licensed apache-2.0.
Windstorm Labs did not train the original model. This notice provides the attribution the
licence requires.
The weights in this repository have been modified from the original. A full fine-tune on OPUS-100 parallel corpus data.
| Method | deep-finetune |
| Tensors modified | 253 of 254 |
| Max absolute weight delta | 1.677e-02 |
| Verified | tensor-by-tensor against the upstream original, 2026-07-26 |
The comparison is tensor-level rather than file-level: safetensors and PyTorch .bin
containers hash differently even when the tensors inside are identical, so a file-hash
mismatch would prove nothing.
A single transformers build in safetensors format, loadable directly:
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tok = AutoTokenizer.from_pretrained("WindyTranslate/translate-de-da")
model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-de-da")
batch = tok(["<your text here>"], return_tensors="pt", padding=True)
print(tok.batch_decode(model.generate(**batch), skip_special_tokens=True))
Other builds of this pair, including CTranslate2 INT8, are not included in this repository.
| Benchmark | chrF++ | BLEU | Band |
|---|---|---|---|
| FLORES-200 dev, 48 sentences (German → Danish) | 61.37 | 38.95 | Excellent |
Measured 2026-08-04; screening score, not a publication result. Bands: Excellent ≥60, Good 45–60, Usable 30–45, Limited 15–30, Not recommended <15 (chrF++).
de to da.