Instructions to use WindyWord/translate-en-bat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyWord/translate-en-bat 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-en-bat")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindyWord/translate-en-bat", device_map="auto") - Notebooks
- Google Colab
- Kaggle
WindyWord.ai Translation β English β Baltic
Part of the Windstorm Labs open model catalogue. Scores, licence and attribution for every model: https://windytranslate.com/models/translate-en-bat
Canonical copy: https://huggingface.co/WindyTranslate/translate-en-bat
Translates English β Baltic (Lithuanian, Latvian).
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 β production baseline. Transformers format for GPU inference. |
Quick usage
Transformers (PyTorch):
from transformers import MarianMTModel, MarianTokenizer
tokenizer = MarianTokenizer.from_pretrained("WindyWord/translate-en-bat", subfolder="lora")
model = MarianMTModel.from_pretrained("WindyWord/translate-en-bat", subfolder="lora")
Apps
The Windy Word apps are built on this model family.
Provenance & License
Weights derived from Helsinki-NLP/opus-mt-en-bat (OPUS-MT, Helsinki-NLP, University of Helsinki), licensed Apache-2.0. Windy variants are released under the same licence.
Model tree for WindyWord/translate-en-bat
Base model
Helsinki-NLP/opus-mt-en-bat