Can we take of benefit of using transfer learning while training a word2vec models?
Yes, you can take benefit of pre-trained models. Most famous one being the GoogleNewsData trained model which you can find here.

Pre-trained word and phrase vectors https://drive.google.com/file/d/0B7XkCwpI5KDYNlNUTTlSS21pQmM/edit?usp=sharing

You can then load the vectors in binary format in your model using gensim as shown below.

&gt;&gt;&gt; model = Word2Vec.load_word2vec_format('/tmp/vectors.txt', binary=False)  # C text format
&gt;&gt;&gt; model = Word2Vec.load_word2vec_format('/tmp/vectors.bin', binary=True)  # C binary format


Here is a different pre-built model for English Wikipedia:

https://github.com/idio/wiki2vec/raw/master/torrents/enwiki-gensim-word2vec-1000-nostem-10cbow.torrent

Source: https://github.com/idio/wiki2vec/

Using a prebuilt model

Get python 2.7
Install gensim: pip install gensim
uncompress downloaded model: tar -xvf model.tar.gz
Load model in gensim:
from gensim.models import Word2Vec
model = Word2Vec.load("path/to/word2vec/en.model")
model.similarity('woman', 'man')


You can also use Stanford NLP Glove 


http://nlp.stanford.edu/projects/glove/
https://github.com/stanfordnlp/GloVe


Here is a great compilation of pre-trained word2vec models.


https://github.com/3Top/word2vec-api#where-to-get-a-pretrained-models


Some additional pre-trained models:


http://www.zuccon.net/ntlm.html
https://code.google.com/archive/p/word2vec/


More on gensim and code here:  https://radimrehurek.com/gensim/models/word2vec.html

Quora forum with a similar questions 


https://www.quora.com/Where-can-I-find-pre-trained-models-of-word2vec-and-sentence2vec-trained-on-Wikipedia-or-other-large-text-corpus
https://www.quora.com/Where-can-I-find-some-pre-trained-word-vectors-for-natural-language-processing-understanding