Setfit few shot

Skill a5c-ai/babysitter/library/specializations/ai-agents-conversational/skills/setfit-few-shot

Babysitter enforces obedience on agentic workforces and enables them to manage extremely complex tasks and workflows through deterministic, hallucination-free self-orchestration

Install

npx -y skills add a5c-ai/babysitter --skill setfit-few-shot

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What its author says it does

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SetFit few-shot learning for efficient intent classification with minimal data

SKILL.md

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SetFit Few-Shot Skill

Capabilities

Train SetFit models with few examples per class
Configure contrastive learning settings
Implement efficient classification pipelines
Design few-shot training strategies
Set up model evaluation
Deploy lightweight classifiers

Target Processes

intent-classification-system

Implementation Details

SetFit Advantages

Few Examples: 8-16 examples per class
No Prompts: No prompt engineering needed
Fast Training: Minutes vs hours
Small Models: Sentence transformer base

Training Process

Contrastive fine-tuning of embeddings
Classification head training
Iterative sampling strategies

Configuration Options

Base sentence transformer model
Number of training examples
Contrastive learning epochs
Classification head architecture
Evaluation metrics

Best Practices

Diverse few-shot examples
Balance class examples
Use appropriate base model
Validate on held-out data

Dependencies

setfit
sentence-transformers