few-shot-learning
Few-shot learning enables LLMs to perform tasks by providing a small number of examples (typically 1-10) within the prompt. This technique is highly effective for tasks requiring specific formats, styles, or domain knowledge.
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What it does and how to use it
A skill that teaches Claude Code to do ai research tasks well. It is packaged knowledge the model uses whenever it is relevant.
- Install the skill (command above).
- In Claude Code, describe what you need - the skill turns on by itself when the context fits.
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Install (Claude Code)
mkdir -p .claude/skills/few-shot-learning && curl -fsSL https://doutorai.pt/data/lib/skills__few-shot-learning.md -o .claude/skills/few-shot-learning/SKILL.mdPaste this command into the terminal, in your project folder, and the component installs automatically.
Content
# Few-Shot Learning Guide
## Overview
Few-shot learning enables LLMs to perform tasks by providing a small number of examples (typically 1-10) within the prompt. This technique is highly effective for tasks requiring specific formats, styles, or domain knowledge.
## Example Selection Strategies
### 1. Semantic Similarity
Select examples most similar to the input query using embedding-based retrieval.
```python
from sentence_transformers import SentenceTransformer
import numpy as np
class SemanticExampleSelector:
def __init__(self, examples, model_name='all-MiniLM-L6-v2'):
sel
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