Instructions to use Helsinki-NLP/opus-mt-en-et with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-en-et 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-en-et")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-et") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-et") - Notebooks
- Google Colab
- Kaggle
opus-mt-en-et
source languages: en
target languages: et
OPUS readme: en-et
dataset: opus
model: transformer-align
pre-processing: normalization + SentencePiece
download original weights: opus-2019-12-18.zip
test set translations: opus-2019-12-18.test.txt
test set scores: opus-2019-12-18.eval.txt
Benchmarks
| testset | BLEU | chr-F |
|---|---|---|
| newsdev2018-enet.en.et | 21.8 | 0.540 |
| newstest2018-enet.en.et | 23.3 | 0.556 |
| Tatoeba.en.et | 54.0 | 0.717 |
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