Practical_NLP_in_PyTorch
Practical_NLP_in_PyTorch copied to clipboard
SciBert embedding
Hi! what if I want to use scibert embedding in my model is it enough just to replace this code : `from allennlp.data.token_indexers import PretrainedBertIndexer
token_indexer = PretrainedBertIndexer( pretrained_model="bert-base-uncased", max_pieces=config.max_seq_len, do_lowercase=True, )
def tokenizer(s: str): return token_indexer.wordpiece_tokenizer(s)[:config.max_seq_len - 2]`
by this code
` from allennlp.data.token_indexers import PretrainedBertIndexer
token_indexer = PretrainedBertIndexer( pretrained_model="scibert-scivocab-uncased", max_pieces=config.max_seq_len, do_lowercase=True, )
def tokenizer(s: str): return token_indexer.wordpiece_tokenizer(s)[:config.max_seq_len - 2]`