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Evaluating 코드 Models

원문: 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. Industry standard from BigCode Project

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BigCode Evaluation Harness Code Model Benchmarking Quick Start BigCode Evaluation Harness evaluates code generation models across 15+ benchmarks including HumanEval, MBPP, and MultiPL E (18 languages). Installation : Evaluate on HumanEval : View available tasks : Common Workflows Workflow 1: Standard Code Benchmark Evaluation Evaluate model on core code benchmarks (HumanEval, MBPP, HumanEval+). Checklist : Step 1: Choose benchmark suite Python code generation (most common): HumanEval : 164 handwritten problems, function completion HumanEval+ : Same 164 problems with 80× more tests (stricter) MBPP : 500 crowd sourced problems, entry level difficulty MBPP+ : 399 curated problems with 35× more

실행 시 본인 API 키(BYOK)로 동작하며, 모델 비용은 사용자 계정에서 직접 결제됩니다.