tokenizer = BertTokenizer.from_pretrained("bert-base-chinese")</br>
config = BertConfig.from_pretrained('Leonardolin/NTCIR_none_and_s_with_a', num_labels=2)</br>
model = BertForSequenceClassification.from_pretrained("Leonardolin/NTCIR_none_and_s_with_a",config=config)
{"language": ["zh"]}
transformers pytorch bert text-classification zh autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #zh #autotrain_compatible #endpoints_compatible #region-us 

tokenizer = BertTokenizer.from_pretrained("bert-base-chinese")</br>
config = BertConfig.from_pretrained('Leonardolin/NTCIR_none_and_s_with_a', num_labels=2)</br>
model = BertForSequenceClassification.from_pretrained("Leonardolin/NTCIR_none_and_s_with_a",config=config)
TAGS
#transformers #pytorch #bert #text-classification #zh #autotrain_compatible #endpoints_compatible #region-us 
