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I'm getting an AttributeError while loading the gensim model available at word2vec repository:
from gensim import models
w = models.Word2Vec()
w.load_word2vec_format('GoogleNews-vectors-negative300.bin', binary=True)
print w["queen"]
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-3-8219e36ba1f6> in <module>()
----> 1 w["queen"]
C:\Anaconda64\lib\site-packages\gensim\models\word2vec.pyc in __getitem__(self, word)
761
762 """
--> 763 return self.syn0[self.vocab[word].index]
764
765
AttributeError: 'Word2Vec' object has no attribute 'syn0'
Is this a known issue ?
930
Introduces Gensim’s Word2Vec model and demonstrates its use on the Lee Evaluation Corpus. In case you missed the buzz, Word2Vec is a widely used algorithm based on neural networks, commonly referred to as “deep learning” (though word2vec itself is rather shallow).
# # To load a saved model: # new_model = gensim.models.Word2Vec.load(temporary_filepath) which uses pickle internally, optionally mmap ‘ing the model’s internal large NumPy matrices into virtual memory directly from disk files, for inter-process memory sharing.
The Word2Vec Skip-gram model, for example, takes in pairs (word1, word2) generated by moving a window across text data, and trains a 1-hidden-layer neural network based on the synthetic task of given an input word, giving us a predicted probability distribution of nearby words to the input.
AttributeError: 'Word2VecKeyedVectors' object has no attribute 'negative' During handling of the above exception, another exception occurred: 977 logger.info ('Model saved using code from earlier Gensim Version. Re-loading old model in a compatible way.')
Fixed the problem with:
from gensim import models
w = models.Word2Vec.load_word2vec_format('GoogleNews-vectors-negative300.bin', binary=True)
print w["queen"]
In order to share word vector querying code between different training algos(Word2Vec, Fastext, WordRank, VarEmbed) the authors have separated storage and querying of word vectors into a separate class KeyedVectors.
Two methods and several attributes in word2vec class have been deprecated.
Methods
Attributes
These have been moved to KeyedVectors class.
After upgrading to this release you might get exceptions about deprecated methods or missing attributes.
To remove the exceptions, you should use
KeyedVectors.load_word2vec_format (instead ofWord2Vec.load_word2vec_format)
word2vec_model.wv.save_word2vec_format (instead of word2vec_model.save_word2vec_format)
model.wv.syn0norm instead of (model.syn0norm)
model.wv.syn0 instead of (model.syn0)
model.wv.vocab instead of (model.vocab)
model.wv.index2word instead of (model.index2word)
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