UltraEval: A Lightweight Platform for Flexible and Comprehensive Evaluation for LLMs

TL;DR

UltraEval is a lightweight, modular, and comprehensive evaluation platform for LLMs that simplifies and accelerates the process of testing models across various tasks and metrics.

Contribution

The paper introduces UltraEval, a new evaluation framework that is lightweight, modular, and supports diverse models and tasks with efficient inference capabilities.

Findings

UltraEval enables seamless combination of models, data, and metrics.

It offers efficient inference acceleration for large-scale evaluations.

The platform is publicly available for research use.

Abstract

Evaluation is pivotal for refining Large Language Models (LLMs), pinpointing their capabilities, and guiding enhancements. The rapid development of LLMs calls for a lightweight and easy-to-use framework for swift evaluation deployment. However, considering various implementation details, developing a comprehensive evaluation platform is never easy. Existing platforms are often complex and poorly modularized, hindering seamless incorporation into research workflows. This paper introduces UltraEval, a user-friendly evaluation framework characterized by its lightweight nature, comprehensiveness, modularity, and efficiency. We identify and reimplement three core components of model evaluation (models, data, and metrics). The resulting composability allows for the free combination of different models, tasks, prompts, benchmarks, and metrics within a unified evaluation workflow. Additionally, UltraEval supports diverse models owing to a unified HTTP service and provides sufficient inference acceleration. UltraEval is now available for researchers publicly.