RVA

  • Saving embeddings in a dictionary, and updating the shelve database in batches seems to work best.
  • After many trials the code to generate the embeddings finally works on the whole corpus without running out of memory.
  • I’ll upload the analogy evaluation results once the all the embeddings are generated.
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