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CLUEbenchmark/CLUE resource

中文语言理解测评基准 Chinese Language Understanding Evaluation Benchmark: datasets, baselines, pre-trained models, corpus and leaderboard observed · 2026-08-28

github.com/CLUEbenchmark/CLUE · homepage · Python observed · 2026-08-28

Health v2 · maintenance only

62/100

  • Activity 66
  • Release rhythm 35
  • Longevity 100

Flags: no_releases no_license

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 2476
  • days_rel: n/a
  • days_push: 208
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

4279 stars · 544 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

CLUE is the Chinese Language Understanding Evaluation Benchmark, providing representative datasets, baseline and pre-trained models, corpora, and a public leaderboard for Chinese NLP tasks. It also encompasses SuperCLUE, an evolving suite of benchmarks for evaluating Chinese large language models across reasoning, agents, safety, and multimodal capabilities.

Use cases

  • evaluate Chinese language understanding models on standard tasks
  • compare pretrained models like BERT, RoBERTa, and ALBERT on Chinese NLU
  • find Chinese NLP datasets for classification, NER, and reading comprehension
  • benchmark Chinese large language models against a leaderboard
  • download Chinese corpora for pretraining or language modeling
  • reproduce baseline results for Chinese text classification tasks

When to choose

  • you need standardized Chinese NLU evaluation datasets and baselines
  • you want to compare your model against published Chinese leaderboard scores
  • you need large Chinese corpora for pretraining or domain adaptation
  • you are evaluating Chinese LLMs with SuperCLUE benchmarks

When to avoid

  • your task is English-only NLU evaluation (use GLUE or SuperGLUE instead)
  • you need a maintained software library rather than datasets and benchmarks
  • you require a permissively licensed codebase, as the repository has no license

Facets

dataset · maturity active

machine-learning nlp benchmarking data-science machine-learning large-language-models artificial-intelligence python cross-platform chinese-nlp benchmark leaderboard pretrained-models corpus nlu bert evaluation natural-language-processing

3 sources

Member repositories

RepositoryRoleHealth v2
CLUEbenchmark/CLUEmain62

For agents

markdown · JSON · MCP: product_card(name="CLUEbenchmark/CLUE")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem