Translation
Transformers
PyTorch
TensorFlow
American Sign Language
German
marian
text2text-generation
Instructions to use Helsinki-NLP/opus-mt-ase-de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-ase-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="Helsinki-NLP/opus-mt-ase-de")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-ase-de") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-ase-de") - Notebooks
- Google Colab
- Kaggle
opus-mt-ase-de
source languages: ase
target languages: de
OPUS readme: ase-de
dataset: opus
model: transformer-align
pre-processing: normalization + SentencePiece
download original weights: opus-2020-01-20.zip
test set translations: opus-2020-01-20.test.txt
test set scores: opus-2020-01-20.eval.txt
Benchmarks
| testset | BLEU | chr-F |
|---|---|---|
| JW300.ase.de | 27.2 | 0.478 |
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