How the Transformer Model Works – Explained Simply

## Definition
The Transformer model is a neural network architecture that processes data in parallel using self-attention mechanisms.

## How It Works
It evaluates relationships between tokens simultaneously rather than sequentially, enhancing efficiency.

## Examples or Use Cases
Used in models like GPT, BERT, and T5 for NLP and vision applications.

## Related Terms
– [LLM](#)
– [Tokenization](#)
– [Embedding](#)

## Summary
Transformers are the backbone of modern AI, enabling scalable understanding and text generation.