Closed stephbuon closed 3 years ago
period_model = gensim.models.Word2Vec(sentences = sentences_df['sentence'], workers = n_cores, min_count = 20, # remove words stated less than 20 times vector_size = 100) # size of neuralnet layers; default is 100 - go higher for larger corpora
instead of size
period_model = gensim.models.Word2Vec(sentences = sentences_df['sentence'], workers = n_cores, min_count = 20, # remove words stated less than 20 times vector_size = 100) # size of neuralnet layers; default is 100 - go higher for larger corpora
instead of size