AmanPriyanshu/GeneticPromptLab
GeneticPromptLab uses genetic algorithms for automated prompt engineering (for LLMs), enhancing quality and diversity through iterative selection, crossover, and mutation, while efficiently exploring minimal yet diverse samples from the training set.
This project helps machine learning engineers and data scientists automatically create and optimize the text prompts used to query large language models (LLMs) for tasks like question-answering or classification. You provide your dataset with questions and answers, and it outputs a set of highly effective, diverse prompts that improve the LLM's accuracy. It's designed for anyone building applications with LLMs who needs to get the best performance from their prompts without extensive manual tuning.
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Use this if you need to quickly find high-performing prompts for your LLM applications, especially for question-answering or classification tasks, and want to automate the prompt optimization process.
Not ideal if you're looking for a simple tool to generate creative content or summaries, as this is specifically for optimizing prompts for structured tasks.
Stars
33
Forks
3
Language
Python
License
MIT
Category
Last pushed
Jun 21, 2024
Commits (30d)
0
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