I want to train a Fasttext model in Python using the “gensim” library. First, I should tokenize each sentences to its words, hence converting each sentence to a list of words. Then, this list should be appended to a final list. Therefore, at the end, I will have a nested list containing all tokenized sentences: Then, the model should be
Tag: fasttext
Mocking FastText model for utest
I am using fasttext models in my python library (from the official fasttext library). To run my u-tests, I need at some point a model (fasttext.FastText._FastText object), as light as possible so that I can version it in my repo. I have tried to create a fake text dataset with 5 lines “fake.txt” and a few words and called It