What is the self-attention mechanism in neural networks?

What is the self-attention mechanism in neural networks?

The self-attention mechanism allows a model to weigh the importance of different words in a sequence when processing them.

How does it differ from traditional attention mechanisms?

Unlike traditional attention, which focuses on external inputs, self-attention evaluates the relationships within the same input sequence.

Can you give me an example of how it's used in transformers?

Sure! In transformers, self-attention helps the model understand context by relating each word to every other word in the input.

What are the benefits of using self-attention?

Self-attention improves parallelization, captures long-range dependencies, and enhances the model's ability to understand context.