model_fasttext.Rd
Train word embeddings from a training corpus with the additional ability to obtain word vectors for out-of-vocabulary words.
model_fasttext(...) load_fasttext(file)
... | Any option, from the official documentation. |
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file | Path to a saved model. |
#> → Preprocessing 9 documents #> ← 9 documents after perprocessing# fit model ft <- model_fasttext(size = 4L, window = 3L, min_count = 1L) # build vocabulary ft$build_vocab(sentences = unname(docs))#> None#> None#> [('system', 0.4660586714744568), ('user', 0.43439602851867676), ('trees', 0.37251460552215576), ('time', 0.25313329696655273), ('survey', 0.08980631828308105), ('graph', 0.08002881705760956), ('interface', -0.12998628616333008), ('response', -0.1862679272890091), ('minors', -0.2511548101902008), ('eps', -0.863673746585846)]#> tree#> 0.51893425