If you have worked with building text classification models, chances are you got familiar with the usual drill: collecting hundreds to thousands of labeled examples, cleaning the raw text, converting it to suitable numerical representations for machine learning models — like embeddings or TF-IDF — and training your model, such as a logistic regression or…
