# huggingface/evaluation-guidebook

Sharing both practical insights and theoretical knowledge about LLM evaluation that we gathered while managing the Open LLM Leaderboard and designing lighteval!

Repository: https://github.com/huggingface/evaluation-guidebook
Canonical: https://ross.abutalabs.com/products/evaluation-guidebook
Language: Jupyter Notebook
License: NOASSERTION
License Family: other
Topics: evaluation, evaluation-metrics, guidebook, large-language-models, llm, machine-learning, tutorial
Last push: 2025-12-03T14:45:05+00:00

## Health v2 (maintenance only)
Score: 47/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 55, release rhythm 35, longevity 49
- inputs: {"age_days": 693, "days_push": 273, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2143, forks 125 (observed 2026-08-28T04:06:18.630686+00:00)

## What it is
A guidebook from Hugging Face sharing practical and theoretical knowledge about LLM evaluation, gathered while managing the Open LLM Leaderboard and designing lighteval. It covers automatic benchmarks, human evaluation, and LLM-as-a-judge approaches.

## Use cases
- learn how to evaluate an llm on my specific task
- design my own llm evaluation benchmark
- understand llm-as-a-judge evaluation
- how to run human evaluation of language models
- tips for troubleshooting llm benchmark results
- find evaluation datasets for language models
- learn llm evaluation basics as a beginner

## When to choose
- you are new to LLM evaluation and want a structured introduction
- you need practical tips for designing automatic benchmarks or judge prompts
- you want curated references and evaluation datasets

## When to avoid
- you need a maintained, up-to-date version (the repo is no longer maintained; see the OpenEvals space)
- you want runnable evaluation tooling rather than documentation
- you need evaluation of non-LLM models

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation, machine-learning, llm-inference
- domain: large-language-models, machine-learning, tutorials, education
- platform: -
- tags: llm-evaluation, guidebook, benchmarks, llm-as-a-judge, human-evaluation, open-llm-leaderboard, web-server

## Member repositories
- huggingface/evaluation-guidebook (main) score 47

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:18.630686+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:51:15.134495+00:00, confidence not recorded.
  - readme: https://github.com/huggingface/evaluation-guidebook (fetched 2026-08-28T04:06:18.630686+00:00, sha 9f0965317064)
- Data as of 2026-08-30T08:39:29.467469+00:00.