Transformer Overview
About the Transformer
The Transformer architecture, introduced in "Attention is All You Need" (Vaswani et al., 2017), revolutionized natural language processing by relying entirely on attention mechanisms.
Key Components:
- Embedding Layer: Converts tokens to vectors
- Positional Encoding: Adds position information
- Multi-Head Attention: Parallel attention mechanisms
- Feed-Forward Network: Position-wise transformations
- Layer Normalization: Stabilizes training
- Residual Connections: Enables deep networks
Layers:
6
Attention Heads:
8
Model Dimension:
512
FFN Dimension:
2048