Dataset · Hugging Face

Fsoft-AIC/CodeMMLU

Name: CodeMMLU
Creator: Fsoft-AIC
License: mit
Keywords: task_categories:question-answering, task_ids:multiple-choice-qa, annotations_creators:no-annotation, multilinguality:monolingual, language:en, license:mit, size_categories:10K<n<100K, format:parquet, modality:text, library:datasets, library:pandas, library:mlcroissant, library:polars, arxiv:2410.01999, region:us

CodeMMLU: A Multi-Task Benchmark for Assessing Code Understanding Capabilities 📌 CodeMMLU CodeMMLU is a comprehensive benchmark designed to evaluate the capabilities of large language models (LLMs) in coding and software knowledge. It builds upon the structure of multiple-choice question answering (MCQA) to cover a wide range of programming tasks and domains, including code generation, defect detection, software engineering principles, and much more.… See the full description on the dataset page: https://huggingface.co/datasets/Fsoft-AIC/CodeMMLU.

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Author / organization	Fsoft-AIC
License (as declared)	mit
Downloads	759 (as reported by Hugging Face)
Likes	7
Created	14 October 2024
Last updated at source	12 May 2025

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16 Oct 2026 Description: CodeMMLU: A Multi-Task Benchmark for Assessing Code Understanding Capabilities 📌 CodeMMLU CodeMMLU is a comprehensive benchmark designed to evaluate the capabilities of large language models (LLMs) in coding and software knowledge. It buil → CodeMMLU: A Multi-Task Benchmark for Assessing Code Understanding Capabilities 📌 CodeMMLU CodeMMLU is a comprehensive benchmark designed to evaluate the capabilities of large language models (LLMs) in coding and software knowledge. It buil

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