---

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 with vLLM/lighteval. Works with the model-index metadata format. metadata: aas-risk: critical aas-source: community aas-date-added: '2026-09-04'

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 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.