Instructions to use Helsinki-NLP/opus-mt-en-cs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-en-cs 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-cs")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-cs") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-cs") - Inference
- Notebooks
- Google Colab
- Kaggle
opus-mt-en-cs
source languages: en
target languages: cs
OPUS readme: en-cs
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 |
|---|---|---|
| newssyscomb2009.en.cs | 22.8 | 0.507 |
| news-test2008.en.cs | 20.7 | 0.485 |
| newstest2009.en.cs | 21.8 | 0.500 |
| newstest2010.en.cs | 22.1 | 0.505 |
| newstest2011.en.cs | 23.2 | 0.507 |
| newstest2012.en.cs | 20.8 | 0.482 |
| newstest2013.en.cs | 24.7 | 0.514 |
| newstest2015-encs.en.cs | 24.9 | 0.527 |
| newstest2016-encs.en.cs | 26.7 | 0.540 |
| newstest2017-encs.en.cs | 22.7 | 0.503 |
| newstest2018-encs.en.cs | 22.9 | 0.504 |
| newstest2019-encs.en.cs | 24.9 | 0.518 |
| Tatoeba.en.cs | 46.1 | 0.647 |
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