bert-large-uncased

BERT is a transformers model pretrained on a large corpus of English data in a self-supervised fashion . This model is uncased: it does not make a difference between English and English . It was introduced in a paper and first released in the repository of BERT . The model was pretrained with two objectives: Masked language modeling (MLM) and next sentence prediction (NSP) 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 like sequence classification, token classification or question answering . For tasks such as text-generation you should look at model like GPT2. For tasks,