Does the Google News Word2Vec model take up storage every time you run it?
Just loading a model won't usually use any more disk storage. (An exception: if load or use needs addressable memory beyond your RAM, you may start using virtual memory, which might show up as less disk space depending on your OS. But, with these sorts of models, you want to avoid relying on any virtual memory, as basic most_similar() operations cycle through the full model, & will be very slow if they're reading from disk each time.) 
Loading the model will use memory, then more when 1st doing most_similar(). (That requires unit-normalized vectors, which are calculated the 1st time needed then cached.) 
But terminating a notebook should free that memory. (Note that closing a tab may not cleanly terminate a Jupyter notebook. If the notebook is still running at the notebook server, even with no browsers viewing it, it will still use/hold memory.)
This may seem like an odd question but I'm new to this so thought I'd ask anyway.
I want to use this Google News model over various different files on my laptop. This means I will be running this line over and over again in different Jupyter notebooks: 
model=word2vec.KeyedVectors.load_word2vec_format("GoogleNews-vectors-negative300.bin",binary=True)
Does this eat 1) Storage (I've noticed my storage filling up exponentially for no reason) 
2) Less memory than it would otherwise if I close the previous notebook before running the next.
My storage has gone down by 50GB in one day and the only thing I have done on this computer is run the Google News model (I didn't do most_similar()). Restarting and closing notebooks hasn't helped and there aren't any big files on the laptop. Any ideas?
Thanks.