theano-word2vec 0.1.1

word2vec using Theano and Lasagne

Theano-word2vec ~~~

::

>>> from word2vec import Word2Vec

>>> word2vec = Word2Vec()

>>> # Train an embedding on a corpus
>>> word2vec.train_on_corpus(
...     open('my-corpus.txt').read(),
...     num_embedding_dimensions=500
... )

>>> # Get embeddings using a trained model
>>> embeddings = word2vec.embed(
...     'this will produce a list of vectors.  If the input is a string it '
...     'gets tokenized'
... )
>>> other_embeddings = word2vec.embed([
...     'control', 'tokenization', 'by', 'passing', 'a', 'tokenized', 'list'
... ])

>>> # Do anological arithmetic
>>> king, man, woman = word2vec.embed('king man woman')
>>> queen = king - man + woman
>>> print word2vec.nearest(queen)
'queen'

>>> # Save and load models
>>> word2vec.save('my-embedding.npz')
>>> word2vec.load('my-embedding.npz')

>>> # Get a fresh Lasagne layer out of the trained model
>>> my_deep_learning_architecture = word2vec.layer(input_layer)