How to use the sense2vec.word2vec.Word2Vec function in sense2vec

level=logging.INFO)
    logger.info("running %s", " ".join(sys.argv))
    logger.info("using optimization %s", FAST_VERSION)

    # check and process cmdline input
    program = os.path.basename(sys.argv[0])
    if len(sys.argv) < 2:
        print(globals()['__doc__'] % locals())
        sys.exit(1)
    infile = sys.argv[1]
    from gensim.models.word2vec import Word2Vec  # avoid referencing __main__ in pickle

    seterr(all='raise')  # don't ignore numpy errors

    # model = Word2Vec(LineSentence(infile), size=200, min_count=5, workers=4)
    model = Word2Vec(Text8Corpus(infile, 10), size=256, min_count=5, workers=4, sg=0, hs=0, cbow_mean=1, negative=5)

    if len(sys.argv) > 3:
        outfile = sys.argv[3]
        model.save(outfile + '.model')
        model.save_word2vec_format(outfile + '.model.bin', binary=True)
        model.save_word2vec_format(outfile + '.model.txt', binary=False)

    if len(sys.argv) > 2:
        questions_file = sys.argv[2]
        model.accuracy(sys.argv[2])

    logger.info("finished running %s", program)

def load(cls, *args, **kwargs):
        model = super(Word2Vec, cls).load(*args, **kwargs)
        # update older models
        if hasattr(model, 'table'):
            delattr(model, 'table')  # discard in favor of cum_table
        if model.negative and hasattr(model, 'index2word'):
            model.make_cum_table()  # rebuild cum_table from vocabulary
        if not hasattr(model, 'corpus_count'):
            model.corpus_count = None
        for v in model.vocab.values():
            if hasattr(v, 'sample_int'):
                break  # already 0.12.0+ style int probabilities
            elif hasattr(v, 'sample_probability'):
                v.sample_int = int(round(v.sample_probability * 2**32))
                del v.sample_probability
        if not hasattr(model, 'syn0_lockf') and hasattr(model, 'syn0'):
            model.syn0_lockf = ones(len(model.syn0), dtype=REAL)
        if not hasattr(model, 'random'):