evaluating-code-models

The 'evaluating-code-models' skill is designed to evaluate code generation models across multiple benchmarks, providing insights into model performance with pass@k metrics. It solves the problem of assessing and comparing the performance of code generation models in an industry-standard manner, particularly useful for evaluating models on widely recognized benchmarks like HumanEval, MBPP, MultiPL-E, and other datasets. This skill leverages the BigCode Evaluation Harness to evaluate models across more than 15 benchmarks, allowing researchers and developers to objectively measure and compare model abilities, particularly for tasks involving code generation, multi-language support, and model robustness.