Instructions to use Helsinki-NLP/opus-mt-tr-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-tr-en 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-tr-en")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-tr-en") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-tr-en") - Inference
- Notebooks
- Google Colab
- Kaggle
opus-mt-tr-en
source languages: tr
target languages: en
OPUS readme: tr-en
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 |
|---|---|---|
| newsdev2016-entr.tr.en | 27.6 | 0.548 |
| newstest2016-entr.tr.en | 25.2 | 0.532 |
| newstest2017-entr.tr.en | 24.7 | 0.530 |
| newstest2018-entr.tr.en | 27.0 | 0.547 |
| Tatoeba.tr.en | 63.5 | 0.760 |
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