The memory and computational demands of the original attention mechanism increase quadratically as sequence length grows, rendering it impractical for longer sequences.
However, various methods have been developed to streamline the attention mechanism's complexity. In this video, we'll explore some of the most prominent models that address this challenge.
#transformers
Link to the activation function video:
A Review of 10 Most Popular Activation Functions in Neural Networks
• A Review of 10 Most Po...
Негізгі бет Efficient Self-Attention for Transformers
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