编写模型卡片
记录预期用途、限制和伦理风险
编写模型卡片 是 CoddyKit 上的免费 MLOps Academy 课时。 这是第 2 节课，共 4 节。 你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。 这是 MLOps Academy 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 MLOps Academy 课程共包含 4 节课。
本课时的部分内容尚未翻译，以英文显示。
What a Model Card Is
A model card is a short document that explains what a model does, who it is for, and where it should not be used. 📇
Why Cards Matter
Without a card, knowledge lives only in someone's head. A card makes a model's intended use and limits readable by anyone.
Intended Use Comes First
State the intended use plainly: what problem the model solves and the kind of inputs it expects in production.
Spell Out the Limits
List out-of-scope uses too. A fraud model trained on one country may fail elsewhere, so name those limitations clearly.
Describe the Training Data
Summarize the training data: its source, time range, and any known gaps. Readers must know what the model has actually seen.
Report Performance Honestly
Give metrics, but also break them down by subgroup so a strong overall score does not hide weak spots for some users.
Name the Ethical Risks
Call out ethical risks like bias or misuse up front. Naming a risk is the first step to managing it responsibly.
Keep It Short and Living
A card is a one-page summary, not a thesis. Treat it as a living document you update every time the model changes.
Store It With the Model
Keep the card next to the model in version control or the registry so the right card always travels with the right version.
A Tiny Card in Code
You can attach a card as a structured artifact, here a simple dict logged alongside the model.
card = {
"name": "fraud_v3",
"intended_use": "flag risky transactions",
"limitations": "trained on EU data only",
}
mlflow.log_dict(card, "model_card.json")Tools That Help
Google's Model Card Toolkit and Hugging Face card templates give you a ready structure so you fill blanks instead of inventing one.
Quick Check
Pick what belongs at the heart of a good model card.
Recap
You now know a model card records intended use, data, performance by group, and risks, stored with the model and kept current. ✅
常见问题解答
「编写模型卡片」课时是免费的吗？
是的 — 「编写模型卡片」的完整文本可在网页上免费阅读。要进行交互式练习（内置代码编辑器和全天候 AI 导师）并解锁 MLOps Academy 课程的其余内容，请升级到 CoddyKit PRO。 MLOps Academy 课程共包含 4 节课。
「编写模型卡片」这节课中我会学到什么？
记录预期用途、限制和伦理风险 你通过在浏览器中直接运行的动手代码来练习 MLOps Academy，全天候 AI 导师会在你学习这节课的过程中回答你的问题。
学习 MLOps Academy 需要有经验吗？
无需任何先前经验。CoddyKit 上的 MLOps Academy 课程适合初学者到高级学习者，你可以从这里开始或从头开始，按照自己的节奏学习。 这是第 2 节课，共 4 节。
「编写模型卡片」课时需要多长时间？
大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动，所以你能稳步进步，并在网页和应用中从离开的地方继续。
我能在这节 MLOps Academy 课中编写并运行代码吗？
能。每节 MLOps Academy 课都包含内置代码编辑器，你可以在浏览器中直接编写并运行真实代码，并获得即时 AI 反馈 — 无需本地设置。