mrm8488/squeezebert-finetuned-squadv2

SqueezeBERT is a pretrained model for the English language using a masked language modeling (MLM) and Sentence Order Prediction (SOP) objective . The model architecture is similar to BERT-base, but with the pointwise fully-connected layers replaced with grouped convolutions . This model is case-insensitive and is 4.3x faster than bert-base-uncased on a Google Pixel 3 smartphone . To do well on SQuAD2.0, systems must not only answer questions when possible, but also determine when no answer is supported by the paragraph and abstain from answering . The models were trained on a Tesla P100 GPU and 25GB,