Instructions to use Helsinki-NLP/opus-mt-ru-da with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-ru-da 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-ru-da")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-ru-da") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-ru-da") - Notebooks
- Google Colab
- Kaggle
| {"hf_name":"rus-dan","source_languages":"rus","target_languages":"dan","opus_readme_url":"https:\/\/github.com\/Helsinki-NLP\/Tatoeba-Challenge\/tree\/master\/models\/rus-dan\/README.md","original_repo":"Tatoeba-Challenge","tags":["translation"],"languages":["ru","da"],"src_constituents":["rus"],"tgt_constituents":["dan"],"src_multilingual":false,"tgt_multilingual":false,"prepro":" normalization + SentencePiece (spm32k,spm32k)","url_model":"https:\/\/object.pouta.csc.fi\/Tatoeba-MT-models\/rus-dan\/opus-2020-06-17.zip","url_test_set":"https:\/\/object.pouta.csc.fi\/Tatoeba-MT-models\/rus-dan\/opus-2020-06-17.test.txt","src_alpha3":"rus","tgt_alpha3":"dan","short_pair":"ru-da","chrF2_score":0.714,"bleu":56.6,"brevity_penalty":0.977,"ref_len":11746.0,"src_name":"Russian","tgt_name":"Danish","train_date":"2020-06-17","src_alpha2":"ru","tgt_alpha2":"da","prefer_old":false,"long_pair":"rus-dan","helsinki_git_sha":"480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535","transformers_git_sha":"2207e5d8cb224e954a7cba69fa4ac2309e9ff30b","port_machine":"brutasse","port_time":"2020-08-21-14:41"} |