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	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