Machine Translation

Currently supported machine translation engines:

Not Language Left Behind

Notes

  1. There are distilled and dense models, a LLB-200 1.3B parameters model distilled from NLLB-200 54B parameters model should give better results then LLB-200 1.3B parameters dense model.

References

Seamless M4T

Alternatives

MADLAD-400

Great Apache license from Google, MADLAD-400 top model is still not as good as NLLB top model at 54B parameters but its is much smaller at 10.7B parameters.

Opus-MT

High quality and great MIT license, with web app available.

Note this is not one big model for MANY languages, there is one model for EACH language pair.

Notes

  1. Problem with the Chinese-English models:
    https://github.com/Helsinki-NLP/OPUS-MT-train/issues/13
    they are available here
    Tatoeba-Challenge/models at master · Helsinki-NLP/Tatoeba-Challenge · GitHub
    in this model list, Chinese is "zho" and English is "eng"

Opennmt

Tools:

Lingva

If you must use Google Translate, try bypassing its API with this: