Bugs: If you see something strange, file a Github Issue
and assign @patrickvonplaten.
Translations should be similar, but not identical to output in the test set linked to in each model card.
Implementation Notes
Each model is about 298 MB on disk, there are more than 1,000 models.
The list of supported language pairs can be found here.
Models were originally trained by Jörg Tiedemann using the Marian C++ library, which supports fast training and translation.
All models are transformer encoder-decoders with 6 layers in each component. Each model's performance is documented
  in a model card.
The 80 opus models that require BPE preprocessing are not supported.
The modeling code is the same as [BartForConditionalGeneration] with a few minor modifications:
static (sinusoid) positional embeddings (MarianConfig.static_position_embeddings=True)
