如何将我自己训练过的word嵌入模型保存为使用word2vec保存的Google word2vec和Glove的相同格式？

import numpy as np
from gensim.models import KeyedVectors

# 假设自己训练的模型保存为"my_word2vec_model.bin"
my_model = KeyedVectors.load_word2vec_format('my_word2vec_model.bin', binary=True)

# 获取词汇表和词向量
vocab = my_model.vocab
vectors = my_model.vectors

# 保存为与Google word2vec相同格式的文件
with open('my_word2vec_model.txt', 'w', encoding='utf-8') as f:
    f.write(f"{len(vocab)} {len(vectors[0])}\n")
    for word, vector in zip(vocab, vectors):
        vector_str = ' '.join(str(num) for num in vector)
        f.write(f"{word} {vector_str}\n")

# 保存为与Glove相同格式的文件
with open('my_glove_model.txt', 'w', encoding='utf-8') as f:
    for word, vector in zip(vocab, vectors):
        vector_str = ' '.join(str(num) for num in vector)
        f.write(f"{word} {vector_str}\n")