Creates the embeddings using gensim's Word2Vec.
        :param skip_gram_params: Parameteres for gensim.models.Word2Vec - do not supply 'size' it is taken from the Node2Vec 'dimensions' parameter
        :type skip_gram_params: dict
        :return: A gensim word2vec model

def fit(self, **skip_gram_params):
        """
        Creates the embeddings using gensim's Word2Vec.
        :param skip_gram_params: Parameteres for gensim.models.Word2Vec - do not supply 'size' it is taken from the Node2Vec 'dimensions' parameter
        :type skip_gram_params: dict
        :return: A gensim word2vec model
        """

        if 'workers' not in skip_gram_params:
            skip_gram_params['workers'] = self.workers

        if 'size' not in skip_gram_params:
            skip_gram_params['size'] = self.dimensions

        return gensim.models.Word2Vec(self.walks, **skip_gram_params)