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custom-benchmarks

NeMo Evaluator supports adding custom benchmarks through Framework Definition Files (FDFs) and custom containers.

  • Skills
  • AI research
  • 1

What it does and how to use it

A skill that teaches Claude Code to do ai research tasks well. It is packaged knowledge the model uses whenever it is relevant.

  1. Install the skill (command above).
  2. In Claude Code, describe what you need - the skill turns on by itself when the context fits.
  3. No commands to memorize: you talk in plain language and the skill does the rest.

Install (Claude Code)

mkdir -p .claude/skills/custom-benchmarks && curl -fsSL https://doutorai.pt/data/lib/skills__custom-benchmarks.md -o .claude/skills/custom-benchmarks/SKILL.md

Paste this command into the terminal, in your project folder, and the component installs automatically.

Content

# Custom Benchmark Integration

NeMo Evaluator supports adding custom benchmarks through Framework Definition Files (FDFs) and custom containers.

## Overview

Custom benchmarks are added by:

1. **Framework Definition Files (FDFs)**: YAML files that define evaluation tasks, commands, and output parsing
2. **Custom Containers**: Package your framework with nemo-evaluator for reproducible execution

> **Note**: NeMo Evaluator does not currently support programmatic harness APIs or custom metric implementations via Python classes. Customization is done through FDFs and containers.

## Framework 

- 🔒 Full content on the Pro plan (€7.99/month) -

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