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We currently train our own vocabularies on Wikipedia and other sources, and we align the vocabularies using MUSE with default settings (0-5000 dictionary for training, 5000-6500 dictionary for evaluation and 5 refinements).
You want LASER its a superbig model trained on tons of languages you can use it with sentence_transformers in python to compute embedings. Then you can use faiss or datasketch to find matches at K
If you have at least a decent gaming gpu or want to bother with colab, you could get a relevant dataset and use electra https://github.com/google-research/electra
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