Missing first letters in precompiled word vectors file: GoogleNews-vectors-negative300.bin

[GoogleCodeExporter]

What steps will reproduce the problem?
--Using the python word2vec module in ipython. Loaded the model from 
GoogleNews-vectors-negative300.bin using the command:
model = word2vec.load("~/Downloads/GoogleNews-vectors-negative300.bin")

What is the expected output? What do you see instead?
The vocab of the model looks like it is made of of english words that have been 
stripped of their first character. As a result, many common words are missing. 
Correctly spelled words which are found in vocab actually represent collisions 
created when removing the first character.

For instance:

model.cosine('out')  

returns:

{'out': [('outs', 0.8092596703376076),
  ('eavyweight_bout', 0.65542583911176289),
  ('ightweight_bout', 0.64856198153561295),
  ('ndercard_bout', 0.62005739361720136),
  ('iddleweight_bout', 0.61811559624397572),
  ('assily_Jirov', 0.61172633394627596),
  ('atchweight_bout', 0.60739346001729411),
  ('uper_middleweight_bout', 0.60237084554945242),
  ('eatherweight_bout', 0.60183827323165029),
  ("KO'd", 0.60002383627451883)]}

The string 'out' actually represents the english word 'bout' which has been 
correctly grouped with other boxing terms. Note the similar terms are also 
missing their first characters.

Another example:

model.cosine('aul')

returns

{'aul': [('ohn', 0.82979825790046702),
  ('eter', 0.750119256790031),
  ('ark', 0.71162490811744983),
  ('ndrew', 0.66359523924163855),
  ('hris', 0.66228796043431837),
  ('ichard', 0.66142257169136376),
  ('hilip', 0.6576444040097873),
  ('ichael', 0.64312885937086905),
  ('on', 0.64042190735670823),
  ('avid', 0.63592487085268301)]}  

This group of words is gibberish but represents a cluster of common male names. 
The full names like 'john' however are not present in the vocabularly.

It looks like the vector representation is doing a very good job of capturing 
the linguistic structure. However, the inconvenient absence of first characters 
creates many unfortunate collisions. 

Original issue reported on code.google.com by moza...@gmail.com on 15 Dec 2014 at 7:54

[GoogleCodeExporter]

I noticed this problem myself. In the file wordvectors.py on line 171 they read 
an extra character after each vector. This just sends the first letter to 
nowhere. If you comment this line out then it works i.e. 

171: #fin.read(1)  # newline

Original comment by matthewm...@gmail.com on 31 Mar 2015 at 3:00

[GoogleCodeExporter]

I noticed this problem myself. In the file wordvectors.py on line 171 they read 
an extra character after each vector. This just sends the first letter to 
nowhere. If you comment this line out then it works i.e. 

171: #fin.read(1)  # newline

The suggestion above worked for me. Note that you have to undo this if you were 
to read binary files other than the google news one. If you continue with 
commenting out the new line you will get corrupt vocabs like this :

vocab
-->
array([u'\nthe', u'\nof', u'\nand', u'\nto', u'\nin', u'\nor', u'\na',
       u'\nfor', u'\nany', u'\nby', u'\nas', u'\nThe', u'\nbe', u'\nsuch',
       u'\nshall', u'\nCompany', u'\nis', u'\non', u'\n._.'], 
      dtype='<U78')

Original comment by mtsh...@gmail.com on 4 Jun 2015 at 2:40