Gensim: how to retrain doc2vec model using previous word2vec model
<p>With Doc2Vec modelling, I have trained a model and saved following files:</p>

<pre><code>1. model
2. model.docvecs.doctag_syn0.npy
3. model.syn0.npy
4. model.syn1.npy
5. model.syn1neg.npy
</code></pre>

<p>However, I have a new way to label the documents and want to train the model again. since the word vectors already obtained from previous version. Is there any way to reuse that model (e.g., taking the previous w2v results as initial vectors for training)? Any one know how to do it? </p>

<p>I've figured out that, we can just load the model and continue to train. </p>

<pre><code>model = Doc2Vec.load("old_model")
model.train(sentences)
</code></pre>

python gensim word2vec doc2vec