bert-large-cased-whole-word-masking

BERT large model (cased) whole word masking is a self-supervised model on English language using a masked language modeling (MLM) objective . The training is identical -- each masked WordPiece token is predicted independently . The model is primarily aimed at being fine-tuned on tasks that use the whole sentence (potentially masked)to make decisions, such as sequence classification, token classification or question answering . For tasks such as text-generation you should look at model like GPT2 . The team releasing BERT did not write a model card for this model so this model card has been written by the Hugging Face team . You can use the raw model for either,