setfit-few-shot

# 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 1. **Few Examples**: 8-16 examples per class 2. **No Prompts**: No prompt engineering needed 3. **Fast Training**: Minutes vs hours 4. **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