import tensorflow as tf

		vocab = data.frequent_vocab_list
		embed = wv.load_matrix(args.embedding_size, vocab)

	embed = np.array(embed, dtype = np.float32)

	with tf.Session(config=config) as sess:
		model = create_model(sess, data, args, embed)
		if args.mode == "train":
			model.train_process(sess, data, args)
		else:
