This is a BERT-large model pre-trained on lower-cased English text using Whole-Word-Masking and fine-tuned on the SQuAD v1.1 training set. The model performs question answering for English language; the input is a concatenated premise and question for the premise, and the output is the location of the answer to the question inside the premise. For details about the original floating-point model, check out
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.
The model has been further quantized to INT8 precision using quantization-aware fine-tuning with
NNCF.
