Transformer
A neural network architecture that uses self-attention mechanisms to process sequential data in parallel, enabling efficient processing of long sequences.
In more detail
Transformers revolutionized NLP and AI by introducing the attention mechanism, allowing models to focus on relevant parts of input. Unlike RNNs that process sequences one element at a time, Transformers process entire sequences in parallel. They form the basis of modern large language models like GPT, BERT, and Claude.
Examples
- GPT models
- BERT for text understanding
- Vision Transformers for images
- Multi-modal models like CLIP
Related terms
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