Xiezhi (獬豸) is a comprehensive evaluation suite for Language Models (LMs). It consists of 249587 multi-choice questions spanning 516 diverse disciplines and four difficulty levels, as shown below. Please check our paper for more details, and our website will be open later on.
The main features of mikegu721/xiezhibenchmark are: Model Evaluation, Evaluation Benchmarks.
Open-source alternatives to mikegu721/xiezhibenchmark include: sjtu-lit/ceval — Official github repo for C-Eval, a Chinese evaluation suite for foundation models [NeurIPS 2023]. michael-wzhu/promptcblue — PromptCBLUE: a large-scale instruction-tuning dataset for multi-task and few-shot learning in the medical domain in… flagopen/flageval — FlagEval, launched by BAAI in 2023, is a comprehensive large model evaluation system that encompasses over 800… cluebenchmark/supercluelyb — SuperCLUE琅琊榜：中文通用大模型匿名对战评价基准. haonan-li/cmmlu — CMMLU: Measuring massive multitask language understanding in Chinese. open-compass/opencompass — OpenCompass is an open-source framework for standardized benchmarking of large language models. It provides a…
Official github repo for C-Eval, a Chinese evaluation suite for foundation models NeurIPS 2023
FlagEval, launched by BAAI in 2023, is a comprehensive large model evaluation system that encompasses over 800 open-source and closed-source models from around the globe. It features more than 40 capability dimensions, including reasoning, mathematical skills, and task-solving abilities, along…
CMMLU: Measuring massive multitask language understanding in Chinese
