#117 · Primary category: MLOps & Evaluation

CLUE

albert benchmark bert chinese chineseglue corpus dataset glue language-model nlu pretrained-models pytorch roberta tensorflow transformers

中文语言理解测评基准 Chinese Language Understanding Evaluation Benchmark: datasets, baselines, pre-trained models, corpus and leaderboard

Project last updated:02/06/26

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Why we included this project

CLUE is the benchmark most people turn to when they need a fixed, comparable footing for Chinese-language NLP models. It bundles a broad set of Chinese understanding tasks, from text classification and sentence-pair similarity to natural language inference, and maintains a public leaderboard so you can see how a candidate model performs before committing to it. The repo also includes baseline implementations and links to pre-trained Chinese models, which gives you a sensible starting point instead of training from scratch. It is a research-community standard, not a product you deploy, but for anyone selecting or sanity-checking Chinese models, the datasets and leaderboard history save real time. Because it spans older and current task families, it also works as a window into how Chinese NLU has progressed.

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