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Helsinki-NLP/opus-mt-en-cel Helsinki-NLP/opus-mt-en-cel
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Contributed by

Language Technology Research Group at the University of Helsinki university
1 team member · 1325 models

How to use this model directly from the 🤗/transformers library:

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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-cel") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-cel")
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  • source group: English

  • target group: Celtic languages

  • OPUS readme: eng-cel

  • model: transformer

  • source language(s): eng

  • target language(s): bre cor cym gla gle glv

  • model: transformer

  • pre-processing: normalization + SentencePiece (spm32k,spm32k)

  • a sentence initial language token is required in the form of >>id<< (id = valid target language ID)

  • download original weights:

  • test set translations: opus2m-2020-08-01.test.txt

  • test set scores: opus2m-2020-08-01.eval.txt


testset BLEU chr-F
Tatoeba-test.eng-bre.eng.bre 11.5 0.338
Tatoeba-test.eng-cor.eng.cor 0.3 0.095
Tatoeba-test.eng-cym.eng.cym 31.0 0.549
Tatoeba-test.eng-gla.eng.gla 7.6 0.317 35.9 0.582
Tatoeba-test.eng-glv.eng.glv 9.9 0.454
Tatoeba-test.eng.multi 18.0 0.342

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