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Helsinki-NLP/opus-mt-mkh-en Helsinki-NLP/opus-mt-mkh-en
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last 30 days

pytorch

tf

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-mkh-en") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-mkh-en")
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mkh-eng

  • source group: Mon-Khmer languages

  • target group: English

  • OPUS readme: mkh-eng

  • model: transformer

  • source language(s): kha khm khm_Latn mnw vie vie_Hani

  • target language(s): eng

  • model: transformer

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

  • download original weights: opus-2020-07-27.zip

  • test set translations: opus-2020-07-27.test.txt

  • test set scores: opus-2020-07-27.eval.txt

Benchmarks

testset BLEU chr-F
Tatoeba-test.kha-eng.kha.eng 0.5 0.108
Tatoeba-test.khm-eng.khm.eng 8.5 0.206
Tatoeba-test.mnw-eng.mnw.eng 0.7 0.110
Tatoeba-test.multi.eng 24.5 0.407
Tatoeba-test.vie-eng.vie.eng 34.4 0.529

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