Introduction
LightEval is Hugging Face’s lightweight toolkit for fast and flexible LLM evaluation. It supports multiple backends (Accelerate, VLLM, Nanotron, endpoints) and saves sample-by-sample results to help debug and compare model behavior.
Key Features
- Supports 7,000+ evaluation tasks spanning knowledge, math, chat, multilingual and more.
- Multi-backend compatibility: run evaluations with in-memory models, Accelerate, VLLM, Nanotron or inference endpoints.
- Extensible tasks and metrics: documentation and examples for adding custom tasks and metrics.
- Sample-level outputs: save detailed results for inspection and visualization.
Use Cases
- Model comparison: perform sample-wise comparisons to find model weaknesses.
- Benchmarking: run comprehensive baselines before model release.
- Research & debugging: investigate model failure modes using sample-level diagnostics.
Technical Highlights
- Modular architecture to plug in new backends and task sets easily.
- CLI and Python API for scripted and interactive workflows.
- Active maintenance and community contributions; rich docs and examples.