Beginner score
48/100
Competition workspace
适合能处理中文技术博客文本、构建多标签分类系统的高校学生、个人开发者或企业开发者；个人或2—5人团队均可参加。尤其适合已有NLP或本地部署小型大语言模型经验，并能提交完整可复现代码与模型文件的人。
Suggested next step
Decide whether this contest fits your current stage before you sink time into the leaderboard.
Beginner score
48/100
Learning value
60/100
Estimated effort
12-40 hours
Metric
Official scoring is published on the Op…
适合能处理中文技术博客文本、构建多标签分类系统的高校学生、个人开发者或企业开发者；个人或2—5人团队均可参加。尤其适合已有NLP或本地部署小型大语言模型经验，并能提交完整可复现代码与模型文件的人。
If the items below still feel unfamiliar, you usually get a better result by preparing first instead of rushing in.
中文技术文本处理
多标签文本分类
NLP模型训练
大语言模型本地推理
CSV/XLSX文件处理
Python代码复现与打包
The real friction is usually not library usage. It is validation, time allocation, and task framing.
核心难点是在约300多个限定IT标签中为博文做精准多标签匹配，并兼顾未公开博文数据上的F1表现。提交还必须能以指定表格为输入、产出严格格式的CSV/XLSX，并提供完整执行步骤；使用大语言模型时只能使用10B以下模型，不能调用云端API。
This guide is the best pre-read if you want a cleaner start instead of trial-and-error.
How to learn feature engineering, validation, and competition workflow without heavy hardware.
No GPU? Pick Competitions That Still Teach You Good HabitsUse these fields to make a quick decision before you dive deeper.
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Rules, files, submission details, and the live deadline still come from the official page.
These competitions share a similar domain or difficulty level.
Separate what is confirmed from what still needs review. Official rules and deadlines win — report anything that looks wrong.
Official metric is not published on the OpenAtom competition listing; verify scoring on the competition page.
reward_value_usd is a rough CNY→USD estimate (×0.14) for ranking only; use reward_summary for the official prize text.