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evaluating-llms-harness

Run standardized LLM evaluations across 60+ academic benchmarks.

Updated Apr 24, 2026
Search Tags:#benchmarking#metrics#benchmark#huggingface#vllm#llm-evaluation#model-comparison
One-click install
npx skills add https://github.com/Harries/hermes-agent --skill evaluating-llms-harness-harries
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: evaluating-llms-harness
Source: https://github.com/Harries/hermes-agent/tree/main/skills/mlops/evaluation/lm-evaluation-harness
Command: npx skills add https://github.com/Harries/hermes-agent --skill evaluating-llms-harness-harries

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Benchmarking and comparing LLMs against standardized benchmarks to quantify capabilities and track progress.

Core Features & Use Cases

  • Cross-benchmark evaluation across 60+ tasks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag, etc.)
  • Supports HuggingFace, vLLM, and API-based models for flexible backends
  • Reproducible results and industry-standard evaluation for research and benchmarking

Quick Start

Install lm-evaluation-harness and run the harness against your model using a standard task list to obtain baseline results.

Frequently Asked Questions about evaluating-llms-harness

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I benchmark LLMs across multiple academic benchmarks?▼

Benchmark LLMs by standardizing evaluation across 60+ academic benchmarks like MMLU and HumanEval, applying a supported evaluation framework to run prompts and collect results for model comparisons.

Can I evaluate models deployed on vLLM or HuggingFace?▼

Yes, you can evaluate models on vLLM, HuggingFace, and custom API-based deployments, as the tool supports flexible backends to run benchmark tasks and collect results.

What is the best way to compare LLM quality and track progress?▼

The best way to compare LLM quality is running industry-standard benchmark evaluations across tasks like GSM8K and TruthfulQA, ensuring reproducible results for tracking model progress.

Do I need a specific evaluation framework to run these benchmarks?▼

Yes, you need a supported evaluation framework, access to benchmark task definitions, and the ability to run prompts and collect results using backends like HuggingFace or vLLM.

What benchmarks are available for LLM evaluation?▼

Available LLM evaluation benchmarks include over 60 academic tasks such as MMLU, HumanEval, GSM8K, TruthfulQA, and HellaSwag, covering diverse capabilities for model comparisons.

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