bert——预训练模型下载
google的bert预训练模型:(前两个2019-05-30更新的,后面2018-10-18更新的)BERT-Large, Uncased (Whole Word Masking): 24-layer, 1024-hidden, 16-heads, 340M parametersBERT-Large, Cased (Whole Word Masking): 24-layer, 1024-hidd
google的bert预训练模型:(前两个2019-05-30更新的,后面2018-10-18更新的)
BERT-Large, Uncased (Whole Word Masking): 24-layer, 1024-hidden, 16-heads, 340M parameters
BERT-Large, Cased (Whole Word Masking): 24-layer, 1024-hidden, 16-heads, 340M parameters
BERT-Base, Uncased: 12-layer, 768-hidden, 12-heads, 110M parameters
BERT-Large, Uncased: 24-layer, 1024-hidden, 16-heads, 340M parameters
BERT-Base, Cased: 12-layer, 768-hidden, 12-heads , 110M parameters
BERT-Large, Cased: 24-layer, 1024-hidden, 16-heads, 340M parameters
BERT-Base, Multilingual Cased (New, recommended): 104 languages, 12-layer, 768-hidden, 12-heads, 110M parameters
BERT-Base, Multilingual Uncased (Orig, not recommended) (Not recommended, use Multilingual Casedinstead): 102 languages, 12-layer, 768-hidden, 12-heads, 110M parameters
BERT-Base, Chinese: Chinese Simplified and Traditional, 12-layer, 768-hidden, 12-heads, 110M parameters
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