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@liuhange/dsh-ai-dataset-inspector

v3.1.5

Published

AI训练数据集质检插件 — 检测标注一致性、标签分布、数据泄露，输出质检报告

Vulnerabilities

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Links

Git

Maintainers

liuhangeliuhange

Keywords

deepseek-harnessdsh-plugindshtypescriptnodejsopen-sourcepluginautomationauditcompliancedata-governancedata-qualitydata-assetdata-asset-inspectorshujintong数据资产ai-datasettraining-data-qualityannotation-auditAI数据集训练数据标注一致性标签分布数据泄露machine-learningml-datadataset-qualityannotation-qualitylabel-distributiondata-leakageai-qualitytraining-setground-truthmodel-trainingdata-validation质检报告registrationvaluation

Readme

@liuhange/dsh-ai-dataset-inspector

基本信息

| 项目 | 值 | |------|-----| | 插件名 | dsh-ai-dataset-inspector | | 包名 | @liuhange/dsh-ai-dataset-inspector | | 版本 | 3.1.0 | | 工具 | inspect_ai_dataset |

功能说明

检查AI训练数据集质量，涵盖标注一致性（Kappa系数）、标签均衡性（类别分布比）、数据泄露检测（训练/验证集重叠）等维度。支持引用data-masking结果检测PII残留。

安装

dsh plugin --profile web add @liuhange/dsh-ai-dataset-inspector

用法

import { apply } from '@liuhange/dsh-ai-dataset-inspector';
apply(ctx); // 注册工具: inspect_ai_dataset

政策依据

| 文件名称 | 文号 | 核心条款摘要 | |---------|------|------------| | 关于推进行业高质量数据集建设行动的实施方案 | 国数发〔2026〕39号 | 部署强基扩容、标注攻坚、提质增效、应用赋能、管理服务、价值释放六大行动 | | 高质量数据集建设指南 | T/TC609 005-2025 | 覆盖数据需求、规划、采集、预处理、标注、模型验证全生命周期 |

License

MIT