Skip to content
Back to skills

Hugging Face Evaluation

ASecurity

Add and manage evaluation results in Hugging Face model cards. Supports extracting eval tables from README content, importing scores from Artificial Analysis API, and running custom model evaluations

  • 6 stars
  • 0 votes
  • 0 copies
  • 2 views
  • Added September 11, 2026
ai-agentsgotestinggitapibackend

Works with

  • api

Security analysis

A100/100

Scanned September 11, 2026

npx -y skills add ranbot-ai/awesome-skills --skill hugging-face-evaluation --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Hugging Face Evaluation?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Hugging Face Evaluation
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/ranbot-ai-hugging-face-evaluation/badge)](https://www.skillsdirectory.com/skills/ranbot-ai-hugging-face-evaluation)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
name: hugging-face-evaluation
description: Add and manage evaluation results in Hugging Face model cards. Supports extracting eval tables from README content, importing scores from Artificial Analysis API, and running custom model evaluations 
category: AI & Agents
source: antigravity
tags: [api, ai, llm]
url: https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/hugging-face-evaluation
---


# Overview
This skill provides tools to add structured evaluation results to Hugging Face model cards. It supports multiple methods for adding evaluation data:
- Extracting existing evaluation tables from README content
- Importing benchmark scores from Artificial Analysis
- Running custom model evaluations with vLLM or accelerate backends (lighteval/inspect-ai)

## Detailed Guide

Read [the detailed guide](references/detailed-guide.md) before executing this skill. It retains the complete procedure and reference material. Treat its safety, prerequisites, and validation requirements as mandatory. For focused work, load the relevant sections; for end-to-end work, read the guide completely.

## When to Use
- You need to add structured evaluation results to a Hugging Face model card.
- You want to import benchmark data or run custom evaluations with vLLM, lighteval, or inspect-ai.
- You are preparing leaderboard-compatible `model-index` metadata for a model release.

## Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments

Loading comments…

Newsletter

Get the weekly list of safe new skills, and the ones we pulled.