> Most libraries only use n-grams of size 3 (trigrams) which is satisfactory for detecting the language of longer text fragments consisting of multiple sentences. For short phrases or single words, however, trigrams are not enough.

I only dabbled in language detection at a workshop at a conference years ago, but I was very impressed how well such models work on short text with only bigrams.

Maybe once you expand to over 70 languages does bi- and tri-grams fall short, but I just wanted to say that this is a usecase here very simple models can get you really far.

If you see a blog post where a language detection problem is solved with deep learning chances are the author doesn’t know what they are doing (towards datascience, I’m looking at you!) or it’s a tutorial for working with an NN framework.