Transformer
A neural-network architecture built around attention mechanisms for processing relationships across a sequence.
What Transformer does not show
The architecture explains how information is processed, not what data a deployed model learned.
Terms this definition uses
Related terms in Models and generation
How a model produces text, what its training and decoding controls change, and what none of them can prove about a source.
Autoregressive model · Attention · Self-attention · Parameter · Inference · Pretraining · Fine-tuning · Supervised fine-tuning · Instruction tuning · RLHF · Preference optimization · Knowledge distillation · Quantization · Mixture of experts · Multimodal model · Vision-language model · Small language model · Tokenizer · Temperature · Top-p sampling · Deterministic decoding · System prompt · Developer message · Tool call · Function calling · Structured output · Constrained decoding · Chain of thought · Reasoning trace · Context caching · Context compaction · Model routing · Model drift · Model version
Questions about Transformer
What is Transformer?
A neural-network architecture built around attention mechanisms for processing relationships across a sequence.
What does Transformer not show or guarantee?
The architecture explains how information is processed, not what data a deployed model learned.
Which area of the glossary does Transformer belong to?
Models and generation: How a model produces text, what its training and decoding controls change, and what none of them can prove about a source.
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See it in the full glossary · 751 terms across 19 areas.