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Helsinki-NLP/opus-mt-it-ms Helsinki-NLP/opus-mt-it-ms
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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-it-ms") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-it-ms")
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ita-msa

  • source group: Italian

  • target group: Malay (macrolanguage)

  • OPUS readme: ita-msa

  • model: transformer-align

  • source language(s): ita

  • target language(s): ind zsm_Latn

  • model: transformer-align

  • 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-2020-06-17.zip

  • test set translations: opus-2020-06-17.test.txt

  • test set scores: opus-2020-06-17.eval.txt

Benchmarks

testset BLEU chr-F
Tatoeba-test.ita.msa 26.0 0.536

System Info: