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CodeSignal

How to optimize with DSPy

via CodeSignal

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Overview

Learn DSPy optimization tuning prompts and LM weights via few-shot learning, instruction optimization, and finetuning. You will cover data splits, various optimizers, and saving/loading optimized programs for iterative improvement.

Syllabus

  • Unit 1: Introduction to Optimization with DSPy
    • Splitting Data for Prompt Optimization
    • Loading External Data for Optimization
    • Implementing the DSPy Data Split Ratio
    • Working with Built-in DSPy Datasets
    • DSPy Optimization Basics Quiz
  • Unit 2: Automatic Few-Shot Learning with DSPy
    • Implementing Your First Few-Shot Optimizer
    • Self Generated Examples with BootstrapFewShot
    • Finding Optimal Examples with Random Search
    • Dynamic Example Selection with KNNFewShot
  • Unit 3: Automatic Instruction Optimization with DSPy
    • Tuning COPRO Parameters for Better Instructions
    • Optimizing QA with COPRO Parameters
    • Comparing Few-Shot and Zero-Shot Optimization
    • Balancing Optimization Intensity for Better Results
  • Unit 4: Finishing Optimization: Saving and Loading DSPy Programs
    • Saving Your DSPy Optimization Work
    • Loading Optimized DSPy Programs
    • Quiz on DSPy Optimization Steps

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