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

  • source group: English

  • target group: Chinese

  • OPUS readme: eng-zho

  • model: transformer

  • source language(s): eng

  • target language(s): cjy_Hans cjy_Hant cmn cmn_Hans cmn_Hant gan lzh lzh_Hans nan wuu yue yue_Hans yue_Hant

  • 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-2020-07-17.zip

  • test set translations: opus-2020-07-17.test.txt

  • test set scores: opus-2020-07-17.eval.txt

Benchmarks

testset BLEU chr-F
Tatoeba-test.eng.zho 31.4 0.268

System Info:

  • hf_name: eng-zho

  • source_languages: eng

  • target_languages: zho

  • opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-zho/README.md

  • original_repo: Tatoeba-Challenge

  • tags: ['translation']

  • languages: ['en', 'zh']

  • src_constituents: {'eng'}

  • tgt_constituents: {'cmn_Hans', 'nan', 'nan_Hani', 'gan', 'yue', 'cmn_Kana', 'yue_Hani', 'wuu_Bopo', 'cmn_Latn', 'yue_Hira', 'cmn_Hani', 'cjy_Hans', 'cmn', 'lzh_Hang', 'lzh_Hira', 'cmn_Hant', 'lzh_Bopo', 'zho', 'zho_Hans', 'zho_Hant', 'lzh_Hani', 'yue_Hang', 'wuu', 'yue_Kana', 'wuu_Latn', 'yue_Bopo', 'cjy_Hant', 'yue_Hans', 'lzh', 'cmn_Hira', 'lzh_Yiii', 'lzh_Hans', 'cmn_Bopo', 'cmn_Hang', 'hak_Hani', 'cmn_Yiii', 'yue_Hant', 'lzh_Kana', 'wuu_Hani'}

  • src_multilingual: False

  • tgt_multilingual: False

  • prepro: normalization + SentencePiece (spm32k,spm32k)

  • url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/eng-zho/opus-2020-07-17.zip

  • url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/eng-zho/opus-2020-07-17.test.txt

  • src_alpha3: eng

  • tgt_alpha3: zho

  • short_pair: en-zh

  • chrF2_score: 0.268

  • bleu: 31.4

  • brevity_penalty: 0.8959999999999999

  • ref_len: 110468.0

  • src_name: English

  • tgt_name: Chinese

  • train_date: 2020-07-17

  • src_alpha2: en

  • tgt_alpha2: zh

  • prefer_old: False

  • long_pair: eng-zho

  • helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535

  • transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b

  • port_machine: brutasse

  • port_time: 2020-08-21-14:41