code: public Frame toFrame() {
      Vec zeroVec = null;
      try {
        zeroVec = Vec.makeZero(_output._words.length);
        byte[] types = new byte[1 + _output._vecSize];
        Arrays.fill(types, Vec.T_NUM);
        types[0] = Vec.T_STR;
        String[] colNames = new String[types.length];
        colNames[0] = "Word";
        for (int i = 1; i < colNames.length; i++)
          colNames[i] = "V" + i;
        return new ConvertToFrameTask(this).doAll(types, zeroVec).outputFrame(colNames, null);
      } finally {
        if (zeroVec != null) zeroVec.remove();
      }
    }
docs: Converts this word2vec model to a Frame.
  @return Frame made of columns: Word, V1, .., Vn. Word column holds the vocabulary associated
  with this word2vec model, and columns V1, .., Vn represent the embeddings in the n-dimensional space.