Instructions to use Helsinki-NLP/opus-mt-en-ml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-en-ml 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-ml")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-ml") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-ml") - Inference
- Notebooks
- Google Colab
- Kaggle
opus-mt-en-ml
source languages: en
target languages: ml
OPUS readme: en-ml
dataset: opus+bt+bt
model: transformer-align
pre-processing: normalization + SentencePiece
download original weights: opus+bt+bt-2020-04-28.zip
test set translations: opus+bt+bt-2020-04-28.test.txt
test set scores: opus+bt+bt-2020-04-28.eval.txt
Benchmarks
| testset | BLEU | chr-F |
|---|---|---|
| Tatoeba.en.ml | 19.1 | 0.536 |
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