Instructions to use Helsinki-NLP/opus-mt-fi_nb_no_nn_ru_sv_en-SAMI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-fi_nb_no_nn_ru_sv_en-SAMI 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-fi_nb_no_nn_ru_sv_en-SAMI")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-fi_nb_no_nn_ru_sv_en-SAMI") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-fi_nb_no_nn_ru_sv_en-SAMI", device_map="auto") - Notebooks
- Google Colab
- Kaggle
opus-mt-fi_nb_no_nn_ru_sv_en-SAMI
source languages: fi,nb,no,nn,ru,sv,en
target languages: se,sma,smj,smn,sms
OPUS readme: fi+nb+no+nn+ru+sv+en-se+sma+smj+smn+sms
dataset: opus+giella
model: transformer-align
pre-processing: normalization + SentencePiece
a sentence initial language token is required in the form of
>>id<<(id = valid target language ID)download original weights: opus+giella-2020-04-18.zip
test set translations: opus+giella-2020-04-18.test.txt
test set scores: opus+giella-2020-04-18.eval.txt
Benchmarks
| testset | BLEU | chr-F |
|---|---|---|
| giella.fi.sms | 58.4 | 0.776 |
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