require 'word_to_vec'
corpus=['<sentence 1>', '<sentence 2>']
Eg: corpus=['this is great', 'I am great']
model=WordToVec.build_from_corpus(
  corpus,
  <No of dimensions of final vector>,
  <No of iterations(default=10)>,
  <Size of context(default=3)>,
  <n, where print every nth iteration(default=5)>,
  <step_size of stochastic gradient descent(default=)>
  )

WordToVec.build_from_corpus corpus,dimensions, num_iterations=10,context=3 ,print_every=5, step_size=0.01

model.print_inputV(<word>)

model.print_outputV(<word>)

model.closest(<word>)