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https://api-inference.huggingface.co/models/Helsinki-NLP/opus-mt-en-dra
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Helsinki-NLP/opus-mt-en-dra Helsinki-NLP/opus-mt-en-dra
47 downloads
last 30 days

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-dra") model = AutoModelWithLMHead.from_pretrained("Helsinki-NLP/opus-mt-en-dra")
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eng-dra

  • source group: English

  • target group: Dravidian languages

  • OPUS readme: eng-dra

  • model: transformer

  • source language(s): eng

  • target language(s): kan mal tam tel

  • 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-2020-07-26.zip

  • test set translations: opus-2020-07-26.test.txt

  • test set scores: opus-2020-07-26.eval.txt

Benchmarks

testset BLEU chr-F
Tatoeba-test.eng-kan.eng.kan 4.7 0.348
Tatoeba-test.eng-mal.eng.mal 13.1 0.515
Tatoeba-test.eng.multi 10.7 0.463
Tatoeba-test.eng-tam.eng.tam 9.0 0.444
Tatoeba-test.eng-tel.eng.tel 7.1 0.363

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