How do I classify strings with possibly no meaning? I am quite new to text classification. 

Using EAST text detection model, I get multiple strings that aren't words and most often have no meaning. For example, IDs, brand names, etc. I would like to classify them into two groups. Which models work the best and how should I preprocess the strings?  I wanted to use Word2Vec, but I think it only works with real words and not with arbitrary strings.
I would just use a dictionary. A simple list lookup would tell you whether it's a recognised word or not. As an added bonus you can add some basic language processing, eg to identify inflected forms without listing them in your dictionary. Or use regular expressions to recognise ID numbers. ML is not really the right tool here.