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I want to use a new model, and I have no idea what it was trained on or where it breaks.
What you'll have at the end
A one-page note on a real model: its training data, known limits, and your go or no-go call
You need
A specific candidate model you're evaluating, meaning a name and a link to its own model card, plus a specific way you plan to put it to work in your own project.
Not covered
Running your own benchmark suite or a red-teaming exercise against the model is a separate, bigger project; this only reads and interprets what the model's own card discloses, plus what its maker states elsewhere.
Leans on
Get a helpful answer from a model that over-refuses a harmless request
go there once the card's own limitations section turns out to be heavy safety tuning that blocks harmless requests instead of a missing guardrail
Your budget model keeps matching the flagship on real tasks
go there once trust is settled and the open question shifts from risk to cost
Checked 15 Aug 2026
Part of the Large Language Models (LLMs) cookbook