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Open Source Model Profile · Helsinki-NLP

opus-mt-en-nl

opus-mt-en-nl is a Helsinki-NLP Marian translation model for English to Dutch. According to the model card, it uses a transformer-align model trained on OPUS data.

Publisher
Helsinki-NLP
Task
translation
Model type
marian
License
apache-2.0
Library
transformers
Publication status
Approved for indexing

Model overview

opus-mt-en-nl is published by Helsinki-NLP as a Marian translation model. The captured configuration identifies MarianMTModel with model type marian, and card data records an apache-2.0 license. According to the model card, it translates English to Dutch with a transformer-align model trained on OPUS data.

Recorded capabilities

English-to-Dutch OPUS model

According to the model card, the model translates English to Dutch using a transformer-align model trained on OPUS data.

Marian Transformers design

Captured configuration identifies MarianMTModel with model type marian, and the hub lists Transformers support with pytorch, tf, and rust tags.

Reported Tatoeba scores

According to the model card, the publisher reports BLEU 57.1 and chr-F 0.730 on the Tatoeba.en.nl test set.

Use cases in the source record

  • English-to-Dutch text translation work using the publisher-documented OPUS-trained Marian model.
  • Transformers-based translation experimentation following the publisher's OPUS readme and SentencePiece pre-processing description.

Limitations and unknowns

  • No Ethen-measured evaluation results were extracted from this record.
  • No parameter count was extracted.
  • Provider state is historical snapshot data and should be refreshed before being presented as current.
  • Language, data, and score claims are publisher model-card statements and were not independently verified by Ethen.

Source and provenance

Source: Helsinki-NLP/opus-mt-en-nl

Captured: Unknown. Processed: 2026-09-07T19:34:31.345637+00:00.

opus-mt-en-nl source languages: en target languages: nl OPUS readme: en-nl dataset: opus model: transformer-align pre-processing: normalization + SentencePiece download original weights: opus-2019-12-04.zip test set translations: opus-2019-12-04.test.txt test set scores: opus-2019-12-04.eval.txt Benchmarks testset BLEU chr-F Tatoeba.en.nl 57.1 0.730

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