Word2vec embedding trainer Path pimlico.modules.embeddings.word2vec Executable yes Word2vec embedding learning algorithm, using Gensim's implementation. Find out more about word2vec. This module is simply a wrapper to call Gensim's Python (+C) implementation of word2vec on a Pimlico corpus. Inputs Name Type(s) text TarredCorpus<TokenizedDocumentType> Outputs Name Type(s) model ~pimlico.datatypes.word2vec.Word2VecModel Options Name Description Type iters number of iterations over the data to perform. Default: 5 int min_count word2vec's min_count option: prunes the dictionary of words that appear fewer than this number of times in the corpus. Default: 5 int negative_samples number of negative samples to include per positive. Default: 5 int size number of dimensions in learned vectors. Default: 200 int