Models, artifacts, and runtimes · Lesson 6 of 16 · 7 min

Match model and runtime

A runtime must support the model architecture and storage format. Insufficient memory and unsupported architecture are different failures and need different responses.

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Your objectives

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1
Read the case evidence
Read /opt/ai-lab/cases/aiops-models-runtimes-006.json. Separate the recorded facts from your assumptions.
Hint & worked example
A runtime must support the model architecture and storage format. Insufficient memory and unsupported architecture are different failures and need different responses.
The complete case JSON is read successfully.
```
cat /opt/ai-lab/cases/aiops-models-runtimes-006.json
```
Common mistake to avoid: Reduce batch size to add unsupported architecture support.
2
Isolate the deciding signal
Select the error field from the case JSON. What does it establish—and what does it not establish?
Hint & worked example
Choose a runtime supporting decoder-b instead of treating this as a memory shortage.
A successful JSON query isolates error.
```
jq .error /opt/ai-lab/cases/aiops-models-runtimes-006.json
```
Common mistake to avoid: Using a different case or an unrelated signal as the justification.
3
Record your operational decision
Choose the justified code: choose-compatible-runtime, change-without-evidence, or ignore-the-signal. Save that one code followed by a newline in /home/learner/lab/aiops-models-runtimes-006-decision.txt.
Hint & worked example
Choose a runtime supporting decoder-b instead of treating this as a memory shortage.
The decision artifact contains the correct code, not just a matching command in history.
```
printf '%s\n' 'choose-compatible-runtime' > /home/learner/lab/aiops-models-runtimes-006-decision.txt
```
Common mistake to avoid: Reduce batch size to add unsupported architecture support.

Understand the pattern

A runtime must support the model architecture and storage format. Insufficient memory and unsupported architecture are different failures and need different responses.

Interpret the evidence

Choose a runtime supporting decoder-b instead of treating this as a memory shortage.

A tempting mistake

Reduce batch size to add unsupported architecture support.

All names, measurements, prices, versions, and thresholds in this exercise are fictional training data. The evidence supports this bounded scenario, not a claim about a live provider.

Worked example and expected result

$ cat /opt/ai-lab/cases/aiops-models-runtimes-006.json

{
  "fixture": "Fictional training data; not a live measurement.",
  "model_architecture": "decoder-b",
  "runtime_supports": [
    "decoder-a"
  ],
  "error": "unsupported architecture"
}

Exit status: 0. The command completed successfully in the training fixture.

$ jq .error /opt/ai-lab/cases/aiops-models-runtimes-006.json

"unsupported architecture"

Exit status: 0. The command completed successfully in the training fixture.

$ printf '%s\n' 'choose-compatible-runtime' > /home/learner/lab/aiops-models-runtimes-006-decision.txt

(no output; exit 0)

Exit status: 0. The command completed successfully in the training fixture.

Try a variation

Name the assumption that would have to change for “choose-compatible-runtime” to stop being the justified action. Do not silently replace missing evidence with a guess.

Explain it

What does the evidence in “Match model and runtime” justify?Reduce batch size to add unsupported architecture support.Make the change now and gather the missing evidence afterward.Choose a runtime supporting decoder-b instead of treating this as a memory shortage.

Apply it elsewhere

A colleague concludes: “Reduce batch size to add unsupported architecture support.” What should you do?Treat this fixture as a live measurement.Reject that conclusion; return to the case evidence and its stated limits.Accept it because the training command completed.

Keep the momentum.

Complete the lab, then explain and apply the pattern.

Next: Read context limits Try an incident drill

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Keep learning

Case methodology: evidence, limits, decision