Instructions to use Helsinki-NLP/opus-mt-en-mos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-en-mos 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-mos")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-mos") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-mos", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from Helsinki-NLP/opus-mt-en-mos: direct link, hf CLI and curl.
- Browser
- Download file 824 Bytes
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https://huggingface.co/Helsinki-NLP/opus-mt-en-mos/resolve/main/README.md
- Command line
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hf download hf://Helsinki-NLP/opus-mt-en-mos/README.md
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curl -L -o README.md https://huggingface.co/Helsinki-NLP/opus-mt-en-mos/resolve/main/README.md
824 Bytes
metadata
tags:
- translation
license: apache-2.0
opus-mt-en-mos
source languages: en
target languages: mos
OPUS readme: en-mos
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.en.mos | 26.9 | 0.417 |