def get_kobert_model(model_file, vocab_file, ctx="cpu"):
bertmodel = BertModel(config=BertConfig.from_dict(bert_config))
bertmodel.load_state_dict(torch.load(model_file))
device = torch.device(ctx)
bertmodel.to(device)
bertmodel.eval()
vocab_b_obj = nlp.vocab.BERTVocab.from_json(open(vocab_file, 'rt').read())
return bertmodel, vocab_b_obj
def get_kobert_model(model_file, vocab_file, ctx="cpu"):
bertmodel = BertModel(config=BertConfig.from_dict(bert_config))
bertmodel.load_state_dict(torch.load(model_file))
device = torch.device(ctx)
bertmodel.to(device)
bertmodel.eval()
vocab_b_obj = nlp.vocab.BERTVocab.from_sentencepiece(vocab_file,
padding_token='[PAD]')
return bertmodel, vocab_b_obj
def get_kobert_model(ctx="cpu"):
model_file = './kobert_model/pytorch_kobert_2439f391a6.params'
vocab_file = './kobert_model/kobertvocab_f38b8a4d6d.json'
bertmodel = BertModel(config=BertConfig.from_dict(bert_config))
bertmodel.load_state_dict(torch.load(model_file))
device = torch.device(ctx)
bertmodel.to(device)
bertmodel.eval()
#print(vocab_file) #./kobertvocab_f38b8a4d6d.json
vocab_b_obj = nlp.vocab.BERTVocab.from_json(
open(vocab_file, 'rt').read())
#print(vocab_b_obj)
return bertmodel, vocab_b_obj
