Prompt Engine

This repository serves as a comprehensive platform for evaluating large language models (LLMs) utilizing diverse prompt engineering techniques aimed at enhancing performance on medical benchmarks.

Institution:

Institution

Research Group:

BSC Group: Computer Sciences

Researcher/s:

Jordi Bayarri

Description:

This repository serves as a comprehensive platform for evaluating large language models (LLMs) utilizing diverse prompt engineering techniques aimed at enhancing performance on medical benchmarks. Our goal is to explore how prompt engineering impact LLMs' accuracy, reliability, and overall usefulness in addressing complex medical scenarios. This repo was first created to support the Aloe model.

Value Proposition:

The repository supports Open-Ended QA datasets, allowing answer generation and evaluation using an automated LLM-as-a-judge approach.

Technology Readiness Level (1-9): N/A

Protection:

Apache License (Version 2.0)

More information

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