Few-Shot
NLP/dictionary/few-shot
Definition
Showing the LLM a handful of input/output examples in the prompt before the real query, so it picks up the pattern. Cheap and effective; usually the next thing to try after a plain prompt.
Posts that use this term
- Troubleshooting local LLMs and keeping up
The catalog of common local-LLM failures: OOM, slow tok/s, garbage output, instruction drift, RAG miss, tool-call hallucination. Plus where to follow the field as it moves.
- LLM APIs and the economics of tokens
How input vs output tokens are priced, why output is 5-6x more, what prompt caching saves you (10x), and the hidden costs (tokenizer drift, reasoning tokens, tool-call loops) that surprise people.
- Prompt, RAG, fine-tune: three ways to shape a model
Three levers for shaping what an LLM does: prompting (ask better), RAG (give it the right context), fine-tuning (change the weights). What each costs, what each fixes, and how to pick.