bert-large-uncased-whole-word-masking-finetuned-squad

BERT large model (uncased) whole word masking finetuned on SQuAD dataset . It was introduced in a paper and first released in this repository . This model is uncased: it does not make a difference between English and English . 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 . The training is identical -- each masked WordPiece token is predicted independently . This way, the model learns an inner representation of the English language that can then be used to extract features that can be used for downstream tasks . The only constrain is that the result with the two "sentence"sent,