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from gensim.models import KeyedVectors # model_file = r"fan_word2vec_binary.bin" model_file = r"D:\code\python\MachineLearning\word2evc\test\ppmi.baidubaike.word" #导入模型 model = KeyedVectors.load_word2vec_format(model_file, binary=True)
--------------------------------------------------------------------------- MemoryError Traceback (most recent call last) ~\AppData\Local\Temp\ipykernel_7920\2878082268.py in <module> 4 model_file = r"D:\code\python\MachineLearning\word2evc\test\ppmi.baidubaike.word" 5 #导入模型 ----> 6 model = KeyedVectors.load_word2vec_format(model_file, binary=True) D:\Anaconda3\lib\site-packages\gensim\models\keyedvectors.py in load_word2vec_format(cls, fname, fvocab, binary, encoding, unicode_errors, limit, datatype, no_header) 1627 1628 """ -> 1629 return _load_word2vec_format( 1630 cls, fname, fvocab=fvocab, binary=binary, encoding=encoding, unicode_errors=unicode_errors, 1631 limit=limit, datatype=datatype, no_header=no_header, D:\Anaconda3\lib\site-packages\gensim\models\keyedvectors.py in _load_word2vec_format(cls, fname, fvocab, binary, encoding, unicode_errors, limit, datatype, no_header, binary_chunk_size) 1967 if limit: 1968 vocab_size = min(vocab_size, limit) -> 1969 kv = cls(vector_size, vocab_size, dtype=datatype) 1970 1971 if binary: D:\Anaconda3\lib\site-packages\gensim\models\keyedvectors.py in __init__(self, vector_size, count, dtype, mapfile_path) 241 self.key_to_index = {} 242 --> 243 self.vectors = zeros((count, vector_size), dtype=dtype) # formerly known as syn0 244 self.norms = None 245 MemoryError: Unable to allocate 1.47 TiB for an array with shape (635969, 635970) and data type float32
用错了吗??
The text was updated successfully, but these errors were encountered:
内存不够,ppmi是稀疏向量,你加载的这个要1.47TiB=1470GB内存
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用错了吗??
The text was updated successfully, but these errors were encountered: