Translation
Transformers
PyTorch
TensorFlow
Spanish
Argentine Sign Language
marian
text2text-generation
Instructions to use Helsinki-NLP/opus-mt-es-aed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-es-aed 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-es-aed")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-es-aed") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-es-aed") - Notebooks
- Google Colab
- Kaggle
opus-mt-es-aed
source languages: es
target languages: aed
OPUS readme: es-aed
dataset: opus
model: transformer-align
pre-processing: normalization + SentencePiece
download original weights: opus-2020-01-16.zip
test set translations: opus-2020-01-16.test.txt
test set scores: opus-2020-01-16.eval.txt
Benchmarks
| testset | BLEU | chr-F |
|---|---|---|
| JW300.es.aed | 89.2 | 0.915 |
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