Instructions to use Helsinki-NLP/opus-mt-cs-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-cs-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-cs-en")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-cs-en") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-cs-en") - Inference
- Notebooks
- Google Colab
- Kaggle
opus-mt-cs-en
source languages: cs
target languages: en
OPUS readme: cs-en
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 |
|---|---|---|
| newstest2014-csen.cs.en | 34.1 | 0.612 |
| newstest2015-encs.cs.en | 30.4 | 0.565 |
| newstest2016-encs.cs.en | 31.8 | 0.584 |
| newstest2017-encs.cs.en | 28.7 | 0.556 |
| newstest2018-encs.cs.en | 30.3 | 0.566 |
| Tatoeba.cs.en | 58.0 | 0.721 |
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