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Hi,
I am trying to understand the bert_model
arg in run_classify.py
. In the file, I can see
tokenizer = BertTokenizer.from_pretrained(args.bert_model)
where bert_model
is expected to be the vocab text file of the model
However, I also see
model = BertForSequenceClassification.from_pretrained(args.bert_model, len(label_list))
where bert_model
is expected to be a archive file containing the model checkpoint and config.
Please help to advice the correct use of bert_model
if I have my pretrained model converted locally already.
Thanks!
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