dspy-labeled-few-shot

Name: dspy-labeled-few-shot
Rating: 5 (6 reviews)
Author: lebsral

Use when you have hand-picked high-quality examples and want to use them directly as few-shot demonstrations — no bootstrapping, just your curated demos. Common scenarios - you have expert-curated examples that you trust more than bootstrapped ones, hand-picked demonstrations for high-stakes tasks, using existing labeled data directly without bootstrapping, or when you want full control over which

6stars

Updated 13 days ago

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How to add

/plugin marketplace add lebsral/DSPy-Programming-not-prompting-LMs-skills

The exact command may vary by repository. Check the README on GitHub.

For the skill author

Drop this on your repo README

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Hand-Picked Demonstrations with dspy.LabeledFewShot

Guide the user through using dspy.LabeledFewShot -- the simplest DSPy optimizer. It takes labeled examples you provide and attaches them as few-shot demonstrations to your program's predictors. No bootstrapping, no metric, no LM calls during optimization.

What is LabeledFewShot

dspy.LabeledFewShot is an optimizer that takes a set of labeled training examples and injects them directly as few-shot demonstrations into every predictor i

[Description truncada. Veja o README completo no GitHub.]

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