Train a model with 300-dimensional word embeddings, the structured skip-gram model, discarding words that occur fewer than 10 times:
finalfrontier skipgram --dims 300 --model structgram --epochs 10 --mincount 10 \
--threads 16 corpus.txt corpus-embeddings.fifu
The format of the input file is simple: tokens are separated by spaces,
sentences by newlines (\n).
After training, you can use and query the embeddings with
finalfusion and
finalfusion-utils:
finalfusion similar corpus-embeddings.fifu