Comments (19)
I came across the same error as well. I changed:
word_vectors = KeyedVectors.load_word2vec_format(path, binary=True)
into
word_vectors = KeyedVectors.load(path)
It turns out that load_word2vec_format
is used when we're trying to load word vectors that are trained using the original implementation of word2vec (in C). Since these pre-trained word vectors are trained using Python (gensim), we can use load
instead.
from wordvectors.
I have come across the same error. I changed gensim.models.KeyedVectors.load_word2vec_format()
into gensim.models.Word2Vec.load()
.Then it works
from wordvectors.
I have tried to read the files as you pointed, but I got the next error:
File "C:\ProgramData\Anaconda2\lib\site-packages\gensim\models\base_any2vec.py", line 380, in syn1neg
self.trainables.syn1neg = value
AttributeError: 'Word2Vec' object has no attribute 'trainables'
:(
from wordvectors.
I solve this error by executing on my own word embeddings with the .sh file.
from wordvectors.
@hinamu it works, Thanks
from wordvectors.
I solve this error by executing on my own word embeddings with the .sh file.
What do you mean?
from wordvectors.
I have tried to read the files as you pointed, but I got the next error:
File "C:\ProgramData\Anaconda2\lib\site-packages\gensim\models\base_any2vec.py", line 380, in syn1neg self.trainables.syn1neg = value AttributeError: 'Word2Vec' object has no attribute 'trainables'
:(
I solved this issue by degrading my gensim version from 3.6 to 3.0
from wordvectors.
I came across the same error as well. I changed:
word_vectors = KeyedVectors.load_word2vec_format(path, binary=True)
into
word_vectors = KeyedVectors.load(path)
It turns out that
load_word2vec_format
is used when we're trying to load word vectors that are trained using the original implementation of word2vec (in C). Since these pre-trained word vectors are trained using Python (gensim), we can useload
instead.
When I tried this , I am getting : UnpicklingError: unpickling stack underflow
from wordvectors.
of cause the vector should be trained using the proper codec, it seems the model is trained in other coding environment. Can you check that.
from wordvectors.
I have come across the same error, anybody help? Thank you ~
from wordvectors.
@galuhsahid Thank you so much, it works now. : )
from wordvectors.
Same error as @anavaldi . Any solution?
from wordvectors.
UnpicklingError Traceback (most recent call last)
in ()
3 #model=gensim.models.Word2Vec.load_word2vec_format('model_file', binary=True) Word2Vec.load_word2vec_format
4 #model_bin = KeyedVectors.load_word2vec_format(model_file,binary=True)
----> 5 model=gensim.models.Word2Vec.load(model_file)
6 #model=gensim.Word2Vec.load_word2vec_format('model_file',binary=True) word_vectors = KeyedVectors.load(path)
why is it giving
from wordvectors.
@kusumlata123 even i am getting that Unpickling Error
from wordvectors.
I am also getting the unpickling error...
Any ideas? My code is:
chinese_model = gensim.models.Word2Vec.load(os.path.join(desktop, 'cc.zh.300.bin.gz'))
from wordvectors.
I also tried to save the text file and load it via the function provided by the fasttext official site. I first change the file extension from gz
to txt
and use the following functions:
import io
def load_vectors(fname):
fin = io.open(fname, 'r', encoding='utf-8', newline='\n', errors='ignore')
n, d = map(int, fin.readline().split())
data = {}
for line in fin:
tokens = line.rstrip().split(' ')
data[tokens[0]] = map(float, tokens[1:])
return data
model = load_vectors(os.path.join(desktop, 'cc.zh.300.vec.txt'))
However, I got the following errors:
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-4-d67f52bde947> in <module>
----> 1 model = load_vectors(os.path.join(desktop, 'cc.zh.300.vec.txt'))
<ipython-input-3-0f69b5ce62b8> in load_vectors(fname)
1 def load_vectors(fname):
2 fin = io.open(fname, 'r', encoding='utf-8', newline='\n', errors='ignore')
----> 3 n, d = map(int, fin.readline().split())
4 data = {}
5 for line in fin:
ValueError: invalid literal for int() with base 10: '\x08\x08p[\x00\x03cc.zh.300.vec\x00\\ͮfMr7?W3ۀ0|Szдl\x14I\x132'
from wordvectors.
I tried the above solution but I am getting error as:
UnpicklingError: invalid load key, '\x1f'
My code:
from gensim import models
word2vec_path = 'GoogleNews-vectors-negative300.bin.gz.2' word2vec = models.KeyedVectors.load(word2vec_path)
from wordvectors.
I came across the same error as well. I changed:
word_vectors = KeyedVectors.load_word2vec_format(path, binary=True)
into
word_vectors = KeyedVectors.load(path)
It turns out thatload_word2vec_format
is used when we're trying to load word vectors that are trained using the original implementation of word2vec (in C). Since these pre-trained word vectors are trained using Python (gensim), we can useload
instead.When I tried this , I am getting :
UnpicklingError: unpickling stack underflow
For Korean language, i got this error:
'AttributeError: Can't get attribute 'Vocab' on <module 'gensim.models.word2vec' from 'C:\Users\ductr\Python\lib\site-packages\gensim\models\word2vec.py'>'
Would you mind letting me know what the error is?
from wordvectors.
I tried the above solution but I am getting error as: UnpicklingError: invalid load key, '\x1f' My code: from gensim import models
word2vec_path = 'GoogleNews-vectors-negative300.bin.gz.2' word2vec = models.KeyedVectors.load(word2vec_path)
I get the same error after using:
from gensim.models import Word2Vec
from gensim.models.keyedvectors import KeyedVectors
model = Word2Vec.load(model_path)
What am I doing wrong?
from wordvectors.
Related Issues (20)
- Details on word2vec model HOT 1
- fasttext file format seems wrong HOT 2
- Read word2vec in Pyhton 2.7 HOT 3
- Divide word vectors into simply Chinese and traditional Chinese HOT 1
- Calling word embeddings "models" is a bit misleading.
- Build out-of-vocabulary word fom data.bin HOT 4
- Unable to get most similar word HOT 1
- Loading embeddings HOT 3
- Dictionary for Japanese morpheme analyzer is not mentioned
- Training specification for pretrained model
- Migrating from Gensim 3.x to 4.x
- korean language HOT 3
- Fine tuning with pretrain word vectors
- for those who meet `cannot import name 'Mapping' from 'collections'`
- how can I fine tune the model using additional corpus, say from interview?
- The link to Japanese word2vec embeddings links to Javanese HOT 1
- What tokenizer for Bahasa? HOT 3
- Encoding Type for Pretrained Models HOT 2
- Error while loading the bin file HOT 7
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from wordvectors.