Recently, researchers from DeepMind, UC Berkeley and the University of Oxford introduced a knowledge distillation strategy for injecting syntactic biases into BERT pre-training in order to benchmark natural language understanding.
Bidirectional Encoder Representation from Transformers or BERT is one of the most popular neural network-based techniques for natural language processing (NLP) while pre-training. At the current scenario, while we search for anything on Google search engine, BERT provides us with the answers to our queries.
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