Few-Shot Learning
Few-Shot Learning is a machine learning paradigm where a model is trained or prompted to perform a task using only a small number of training examples. In LLMs, this is achieved by including a few demonstration inputs and outputs directly in the prompt context window.
Frequently Asked Questions
What is zero-shot learning?▼
Zero-shot learning is when the model is asked to perform a task without being shown any prior examples in the prompt.
Why is few-shot learning valuable?▼
It allows rapid task specialization without the massive compute cost or time required for fine-tuning.
Quick Facts
- CategoryPrompt Engineering
- Key ApplicationDynamic classification, prompt engineering, and low-resource data modeling
Coverage Trend12 Weeks
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Few-Shot Learning Media Coverage & Intelligence
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