AI / LLM Basics Interview Questions
What is a Decoder-Only model?
A Decoder-only model is a Transformer variant built entirely from decoder blocks, generating text one token at a time based only on the tokens that came before it.
- Uses causal masking so each token can only attend to earlier tokens, never later ones
- Well suited to open-ended text generation, since that's exactly the pattern it was trained on
- Is the architecture behind most modern general-purpose LLMs, including GPT-style models
This architecture's straightforward "predict the next token" design is a big part of why it scales so well and has become the dominant approach for large-scale language models.
What technique does a decoder-only model use to restrict attention?
What is decoder-only architecture especially well suited to?
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