DjangoPeng / DjangoPeng/word2vec
freebase vector file in python gensim
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Description
```
What steps will reproduce the problem?
1. Load freebase.bin files into a word2vec model on freebase
2. attempy .most_similar function
3. error returned
What is the expected output? What do you see instead?
see beloe
What version of the product are you using? On what operating system?
mac osx anaconda python
Please provide any additional information below.
I’m trying to get started by loading the pretrained .bin files from the
google word2vec site ( freebase-vectors-skipgram1000.bin.gz) into the gensim
implementation of word2vec. The model loads fine,
using ..
model = word2vec.Word2Vec.load_word2vec_format('...../free....-en.bin', binary=
True)
and creates a
>>> print model
but when I run the most similar function. It cant find the words in the
vocabulary. My error code is below.
Any ideas where I’m going wrong?
>>> model.most_similar(['girl', 'father'], ['boy'], topn=3)
2013-10-11 10:22:00,562 : WARNING : word ‘girl’ not in vocabulary; ignoring
it
2013-10-11 10:22:00,562 : WARNING : word ‘father’ not in vocabulary;
ignoring it
2013-10-11 10:22:00,563 : WARNING : word ‘boy’ not in vocabulary; ignoring
it
Traceback (most recent call last):
File “”, line 1, in
File
“/....../anaconda/python.app/Contents/lib/python2.7/site-packages/gensim-0.8.7
/py2.7.egg/gensim/models/word2vec.py”, line 312, in most_similar
raise ValueError(“cannot compute similarity with no input”)
ValueError: cannot compute similarity with no input
any ideas welcome?
```
Original issue reported on code.google.com by `Mark.d.g...@gmail.com` on 11 Oct 2013 at 3:41
Contributor guide
No contributing guide indexed for this repository
Research direction
Start by reproducing the reported load and model.most_similar calls with the freebase-vectors-skipgram1000.bin.gz file and gensim 0.8.7 on the stated Anaconda/macOS setup. Inspect gensim/models/word2vec.py around most_similar and load_word2vec_format; done means identifying why the loaded vocabulary does not contain girl, father, or boy and documenting or correcting the supported loading behavior.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100