Implements Global Word Vectors.
9 Stars
Updated Last
2 Years Ago
Started In
May 2015


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Implements Global Word Vectors.

using Pkg

See benchmark/perf.jl for a usage example.

Here's the rough idea:

  1. Take text and make a LookupTable. This is a dictionary that has a map from words -> ids and vice-versa. Preprocessing steps should be taken prior to this.

  2. Use weightedsums to get the weighted co-occurence sum totals. This returns a CooccurenceDict.

  3. Convert the CooccurenceDict to a CooccurenceVector. The reasoning for this is faster indexing when we train the model.

  4. Initialize a Model and train the model with the CooccurenceVector using the agagrad! method.

It's pretty fast at this point. On a single core it's roughly 3x slower than the optimized C version.


  • [ ] More docs.

  • [ ] See if precompile(args...) does anything

  • [ ] Notebook example ( has to have emojis )

  • [ ] Multi-threading