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https://api-inference.huggingface.co/models/Helsinki-NLP/opus-mt-en-ar
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Helsinki-NLP/opus-mt-en-ar Helsinki-NLP/opus-mt-en-ar
272 downloads
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pytorch

tf

Contributed by

Language Technology Research Group at the University of Helsinki university
1 team member · 1323 models

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

			
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from transformers import AutoTokenizer, AutoModelWithLMHead tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-ar") model = AutoModelWithLMHead.from_pretrained("Helsinki-NLP/opus-mt-en-ar")
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eng-ara

  • source group: English

  • target group: Arabic

  • OPUS readme: eng-ara

  • model: transformer

  • source language(s): eng

  • target language(s): acm afb apc apc_Latn ara ara_Latn arq arq_Latn ary arz

  • 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: opus-2020-07-03.zip

  • test set translations: opus-2020-07-03.test.txt

  • test set scores: opus-2020-07-03.eval.txt

Benchmarks

testset BLEU chr-F
Tatoeba-test.eng.ara 14.0 0.437

System Info: