有没有方法用我们的数据来重新训练雨前的Googlenewsvctorsnegative300.bin模型？

Question

import os
import gensim.models as g
import logging
import gensim
os.chdir("/home/ai/path");
#doc2vec parameters
vector_size = 300
window_size = 5  
min_count = 1 
sampling_threshold = 1e-5 
negative_size = 5 
train_epoch = 100
dm= 0 

worker_count = 2 #number of parallel processes

#pretrained word embeddings
pretrained_emb = "GoogleNews-vectors-negative300.bin"

#input corpus
train_corpus = "mydata.txt"

#output model
saved_path = "Googlemodel.bin"

#enable logging
logging.basicConfig(format='%(asctime)s : %(levelname)s : %
(message)s', 
level=logging.INFO)

#train doc2vec model
docs = g.doc2vec.TaggedLineDocument(train_corpus)
model = g.Doc2Vec(docs, size=vector_size, window=window_size, 
min_count=min_count, sample=sampling_threshold, workers=worker_count, 
hs=0, dm=dm, negative=negative_size, dbow_words=1, dm_concat=1, 
pretrained_emb=pretrained_emb, iter=train_epoch)

GoogleNews-vectors-negative300.bin的大小是3.6gb，我的数据大小是455mb。在

运行此代码或完成培训过程后，我的输出模型只显示850MB。在