What is a transformer model?
Transformers changed NLP forever.
How It Works:
Transformers use self-attention layers to weigh relationships between all input tokens simultaneously, enabling efficient, context-rich representations.
Key Benefits:
- Captures long-range dependencies
- Parallelizable training vs. RNNs
- Foundation for large-scale LLMs
Real-World Use Cases:
- Machine translation (e.g., Google Translate)
- Text summarization services
FAQs
Why self-attention?
Are transformers compute-heavy?
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