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Lighteval - AI Model Libraries & Training Tool

Overview

Lighteval is an all-in-one toolkit for evaluating large language models across multiple backends. It provides detailed, sample-by-sample performance metrics and supports customizable evaluation tasks. The toolkit centralizes evaluation workflows to help developers and researchers compare model behavior, inspect individual outputs, and adapt tasks to specific benchmarks or experiments.

Key Features

  • Evaluate LLMs across multiple backends
  • Detailed sample-by-sample performance metrics
  • Customizable task definitions and evaluation settings
  • All-in-one toolkit consolidating evaluation workflows
  • GitHub repository for source code and examples

Ideal Use Cases

  • Compare model outputs across different backends
  • Analyze per-sample model failures and errors
  • Customize benchmark tasks for research experiments
  • Integrate automated evaluations into development pipelines

Getting Started

  • Visit the GitHub repository page
  • Clone or download the repository
  • Install dependencies listed in repository documentation
  • Configure evaluation backends and task settings
  • Run provided evaluation scripts or notebooks
  • Review sample-by-sample metrics and exported reports

Pricing

No pricing information provided; repository available at https://github.com/huggingface/lighteval.

Key Information

  • Category: Model Libraries & Training
  • Type: AI Model Libraries & Training Tool
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