Instructions to use WindyWord/translate-hu-de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyWord/translate-hu-de 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="WindyWord/translate-hu-de")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindyWord/translate-hu-de", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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license: apache-2.0
tags:
- translation
- marian
- windyword
- hungarian
- german
language:
- hu
- de
library_name: transformers
pipeline_tag: translation
base_model: Helsinki-NLP/opus-mt-hu-de
---
# WindyWord.ai Translation — Hungarian → German
> Part of the Windstorm Labs open model catalogue. Scores, licence and attribution for every model: https://windytranslate.com/models/translate-hu-de
>
> Canonical copy: https://huggingface.co/WindyTranslate/translate-hu-de
> **Note (2026-10-04):** the WindyScripture variants (`herm0-scripture/`, `scripture-ct2-int8/`) were removed from this repository's current files while the licences of their eBible source texts are reviewed. This is a precaution, not a legal conclusion. The other variants are unchanged.
**Translates Hungarian → German.**
## Quality
No quality score is published in this repository. Current screening scores, where measured, are on the catalogue page linked above.
## Available Variants
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. |
### Quick usage
**Transformers (PyTorch):**
```python
from transformers import MarianMTModel, MarianTokenizer
tokenizer = MarianTokenizer.from_pretrained("WindyWord/translate-hu-de", subfolder="lora")
model = MarianMTModel.from_pretrained("WindyWord/translate-hu-de", subfolder="lora")
```
**CTranslate2 (fast CPU inference):**
```python
import ctranslate2
translator = ctranslate2.Translator("path/to/translate-hu-de/lora-ct2-int8")
```
## Apps
The [Windy Word](https://windyword.ai) apps are built on this model family.
---
## Provenance & License
Weights derived from [Helsinki-NLP/opus-mt-hu-de](https://huggingface.co/Helsinki-NLP/opus-mt-hu-de) (OPUS-MT, Helsinki-NLP, University of Helsinki), licensed Apache-2.0. Windy variants are released under the same licence.
Licence text: [`LICENSE`](LICENSE). Attribution: [`NOTICE.md`](NOTICE.md).
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