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

BERT is a transformers model pretrained on a large corpus of English data in a self-supervised fashion . This model is cased: it makes a difference between english and English . It was trained with a new technique: Whole Word Masking . The training is identical -- each masked WordPiece token is predicted independently . After pre-training, this model was fine-tuned on the SQuAD dataset . It should be used as a question-answering model. You may use it in a question answering pipeline, or use it to output raw results given a query and a context . You may see other use cases in the task summary of the transformers documentation .,