Instructions to use Helsinki-NLP/opus-mt-en-urj with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-en-urj with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-en-urj")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-urj") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-urj", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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{"hf_name":"eng-urj","source_languages":"eng","target_languages":"urj","opus_readme_url":"https:\/\/github.com\/Helsinki-NLP\/Tatoeba-Challenge\/tree\/master\/models\/eng-urj\/README.md","original_repo":"Tatoeba-Challenge","tags":["translation"],"languages":["en","se","fi","hu","et","urj"],"src_constituents":["eng"],"tgt_constituents":["izh","mdf","vep","vro","sme","myv","fkv_Latn","krl","fin","hun","kpv","udm","liv_Latn","est","mhr","sma"],"src_multilingual":false,"tgt_multilingual":true,"prepro":" normalization + SentencePiece (spm32k,spm32k)","url_model":"https:\/\/object.pouta.csc.fi\/Tatoeba-MT-models\/eng-urj\/opus2m-2020-08-02.zip","url_test_set":"https:\/\/object.pouta.csc.fi\/Tatoeba-MT-models\/eng-urj\/opus2m-2020-08-02.test.txt","src_alpha3":"eng","tgt_alpha3":"urj","short_pair":"en-urj","chrF2_score":0.588,"bleu":35.1,"brevity_penalty":0.943,"ref_len":59664.0,"src_name":"English","tgt_name":"Uralic languages","train_date":"2020-08-02","src_alpha2":"en","tgt_alpha2":"urj","prefer_old":false,"long_pair":"eng-urj","helsinki_git_sha":"480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535","transformers_git_sha":"
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{"hf_name":"eng-urj","source_languages":"eng","target_languages":"urj","opus_readme_url":"https:\/\/github.com\/Helsinki-NLP\/Tatoeba-Challenge\/tree\/master\/models\/eng-urj\/README.md","original_repo":"Tatoeba-Challenge","tags":["translation"],"languages":["en","se","fi","hu","et","urj"],"src_constituents":["eng"],"tgt_constituents":["izh","mdf","vep","vro","sme","myv","fkv_Latn","krl","fin","hun","kpv","udm","liv_Latn","est","mhr","sma"],"src_multilingual":false,"tgt_multilingual":true,"prepro":" normalization + SentencePiece (spm32k,spm32k)","url_model":"https:\/\/object.pouta.csc.fi\/Tatoeba-MT-models\/eng-urj\/opus2m-2020-08-02.zip","url_test_set":"https:\/\/object.pouta.csc.fi\/Tatoeba-MT-models\/eng-urj\/opus2m-2020-08-02.test.txt","src_alpha3":"eng","tgt_alpha3":"urj","short_pair":"en-urj","chrF2_score":0.588,"bleu":35.1,"brevity_penalty":0.943,"ref_len":59664.0,"src_name":"English","tgt_name":"Uralic languages","train_date":"2020-08-02","src_alpha2":"en","tgt_alpha2":"urj","prefer_old":false,"long_pair":"eng-urj","helsinki_git_sha":"480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535","transformers_git_sha":"2207e5d8cb224e954a7cba69fa4ac2309e9ff30b","port_machine":"brutasse","port_time":"2020-08-21-14:41"}
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