code: def fit(self, **skip_gram_params):
          
  
          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)
docs: 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