Convolutional BERT (ConvBERT) improves the original BERT by replacing some Multi-headed Self-attention segments with cheaper and naturally local operations, so-called span-based dynamic convolutions. These are integrated into the self-attention mechanism to form a mixed attention mechanism, allowing Multi-headed Self-attention to capture global patterns; the Convolutions focus more on the local patterns, which are otherwise captured anyway. In other words, they reduce the computational intensity of training BERT.
Learn how large language models and other foundation models are working and how you can train open source ones yourself.
Keras is a high-level API for TensorFlow. It is one of the most popular deep learning frameworks.
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