Transformers Architecture: A Technical Deep Dive

# Transformers Architecture: A Technical Deep Dive

The transformer architecture has revolutionized natural language processing and continues to be the foundation for state-of-the-art language models.

## The Attention Revolution

At the heart of transformers lies the self-attention mechanism, enabling models to process sequences in parallel while maintaining contextual understanding.

## Architecture Components

We explore each component of the transformer architecture, from multi-head attention to feed-forward networks and layer normalization.

## Conclusion

Understanding transformer architecture is essential for anyone working with modern NLP systems and large language models.