UnpicklingError: invalid load key, '4'

How to fix this? I already train the model.

Code:

#embedding
import gensim
from gensim.models import Word2Vec
from gensim.utils import simple_preprocess
import gensim.models.keyedvectors as word2vec

from gensim.models.keyedvectors import KeyedVectors

word_vectors = gensim.models.Word2Vec.load("w2v02_wiki_sg.model")

EMBEDDING_DIM = 300
vocabulary_size= jumlah_index
embedding_matrix = np.zeros((vocabulary_size, EMBEDDING_DIM))
for word, i in t.word_index.items():
  try:
    embedding_vector = word_vectors[word]
    embedding_matrix[i] = embedding_vector
  except KeyError:
    embedding_matrix[i]=np.random.normal(0,np.sqrt(0.25),EMBEDDING_DIM)

del(word_vectors)
from keras.layers import Embedding
embedding_layer = Embedding(vocabulary_size,
                            EMBEDDING_DIM,
                            weights=[embedding_matrix],
                            trainable=True)

Error:

INFO:gensim.utils:loading Word2Vec object from w2v02_wiki_sg.model
---------------------------------------------------------------------------
UnpicklingError                           Traceback (most recent call last)
<ipython-input-35-84edc08f9bfb> in <module>
      7 from gensim.models.keyedvectors import KeyedVectors
      8 
----> 9 word_vectors = gensim.models.Word2Vec.load("w2v02_wiki_sg.model")
     10 
     11 EMBEDDING_DIM = 300

4 frames
/usr/local/lib/python3.7/dist-packages/gensim/utils.py in unpickle(fname)
   1359         # Because of loading from S3 load can't be used (missing readline in smart_open)
   1360         if sys.version_info > (3, 0):
-> 1361             return _pickle.load(f, encoding='latin1')
   1362         else:
   1363             return _pickle.loads(f.read())

UnpicklingError: invalid load key, '4'.