gensim word2vec accessing in/out vectors

Question

In the word2vec model, there are two linear transforms that take a word in vocab space to a hidden layer (the \"in\" vector), and then back to the vocab space (the \"out\" vecto

Answer 1

Below code will enable to save/load model. It uses pickle internally, optionally mmap‘ing the model’s internal large NumPy matrices into virtual memory directly from disk files, for inter-process memory sharing.

model.save('/tmp/mymodel.model')
new_model = gensim.models.Word2Vec.load('/tmp/mymodel')

Some background information Gensim is a free Python library designed to process raw, unstructured digital texts (“plain text”). The algorithms in gensim, such as Latent Semantic Analysis, Latent Dirichlet Allocation and Random Projections discover semantic structure of documents by examining statistical co-occurrence patterns of the words within a corpus of training documents.

Some good blog describing about the use and sample code base to kick start on the project

• http://mccormickml.com/2016/04/12/googles-pretrained-word2vec-model-in-python/
• https://rare-technologies.com/making-sense-of-word2vec/
• https://rare-technologies.com/word2vec-tutorial/
• https://rare-technologies.com/deep-learning-with-word2vec-and-gensim/

Installation reference here

Hope this helps!!!