This is a fork of Tomas Mikolov's word2vec repository here:

https://github.com/tmikolov/word2vec

I've provided pre-trained models for Irish as well as
intrinsic test sets similar to the ones for English in
the original repo.

The original README text follows below.

Kevin Scannell
St. Louis
January 2019




Tools for computing distributed representtion of words
------------------------------------------------------

We provide an implementation of the Continuous Bag-of-Words (CBOW) and the Skip-gram model (SG), as well as several demo scripts.

Given a text corpus, the word2vec tool learns a vector for every word in the vocabulary using the Continuous
Bag-of-Words or the Skip-Gram neural network architectures. The user should to specify the following:
 - desired vector dimensionality
 - the size of the context window for either the Skip-Gram or the Continuous Bag-of-Words model
 - training algorithm: hierarchical softmax and / or negative sampling
 - threshold for downsampling the frequent words 
 - number of threads to use
 - the format of the output word vector file (text or binary)

Usually, the other hyper-parameters such as the learning rate do not need to be tuned for different training sets. 

The script demo-word.sh downloads a small (100MB) text corpus from the web, and trains a small word vector model. After the training
is finished, the user can interactively explore the similarity of the words.

More information about the scripts is provided at https://code.google.com/p/word2vec/