---

name: model-zoo description: "Select and instantiate CIFAR-100 CNN architectures for this repo." disable-model-invocation: true metadata: disco-role: operating license: NO_LICENSE

Model Zoo

Use this sub-skill to choose a supported CIFAR-100 architecture, map the exact -net token to the right factory, and sanity-check that a checkout still returns 100-class logits from 32×32 inputs.

Quick route

• Need the token → module/factory map? Read references/model-catalog.md.
• Need the utils.get_network contract, shapes, or size hints? Read references/api-reference.md.
• Need to diagnose unsupported names or import failures? Read references/troubleshooting.md.
• Need a fast checkout smoke test? Run scripts/model_smoke.py.
• Need training commands, warmup, TensorBoard, or checkpoints? Go to ../training/.
• Need checkpoint loading, top-1/top-5 error reporting, or weight validation? Go to ../evaluation/.

Typical flow

1. Pick a token from the catalog.
2. Smoke the checkout with scripts/model_smoke.py --repo-root <checkout> --net <name>.
3. If the model passes, hand off to ../training/ or ../evaluation/ as needed.

What stays here

• architecture selection
• token-to-factory routing
• input/output shape validation
• model import troubleshooting
• parameter-count guidance