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evaluating-code-models

Evaluates code generation models across HumanEval, MBPP, MultiPL-E, and 15+ benchmarks with pass@k metrics. Use when benchmarking code models, comparing coding abilities, testing multi-language support, or measuring code generation quality.

  • Skills
  • AI research
  • 2

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/evaluating-code-models && curl -fsSL https://doutorai.pt/data/lib/skills__evaluating-code-models.md -o .claude/skills/evaluating-code-models/SKILL.md

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

Content

---
name: evaluating-code-models
description: Evaluates code generation models across HumanEval, MBPP, MultiPL-E, and 15+ benchmarks with pass@k metrics. Use when benchmarking code models, comparing coding abilities, testing multi-language support, or measuring code generation quality. Industry standard from BigCode Project used by HuggingFace leaderboards.
version: 1.0.0
author: Orchestra Research
license: MIT
tags: [Evaluation, Code Generation, HumanEval, MBPP, MultiPL-E, Pass@k, BigCode, Benchmarking, Code Models]
dependencies: [bigcode-evaluation-harness, transformers>=4.25.1, accelerate>=

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