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api-evaluation

Guide to evaluating OpenAI, Anthropic, and other API-based language models.

  • 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/api-evaluation && curl -fsSL https://doutorai.pt/data/lib/skills__api-evaluation.md -o .claude/skills/api-evaluation/SKILL.md

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

Content

# API Evaluation

Guide to evaluating OpenAI, Anthropic, and other API-based language models.

## Overview

The lm-evaluation-harness supports evaluating API-based models through a unified `TemplateAPI` interface. This allows benchmarking of:
- OpenAI models (GPT-4, GPT-3.5, etc.)
- Anthropic models (Claude 3, Claude 2, etc.)
- Local OpenAI-compatible APIs
- Custom API endpoints

**Why evaluate API models**:
- Benchmark closed-source models
- Compare API models to open models
- Validate API performance
- Track model updates over time

## Supported API Models

| Provider | Model Type | Request 

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

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