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Try a local AI model on a small task

Compare a local model with a known-answer task and document its limits.

About 45 minutesSome experienceRead free · No sign-up

Before you start

A computer, the current official Ollama setup instructions and a small model compatible with your hardware. Use sample text first.

Why this lesson exists

Patrick’s local-model posts explored access and control. Running a model on your own machine changes the data path, but it does not automatically remove every network dependency.

Do the exercise

  1. Check the machine and download source

    Read the current official installation guide and model requirements. Confirm disk space and memory before downloading. Choose a small supported model rather than the largest name.

  2. Run a harmless baseline

    Ask the model to extract a deadline and owner from a fictional paragraph. Keep an answer key. Measure whether the response is correct and fast enough to use.

  3. Inspect the data path

    Identify what stays on the device and which features still contact remote services. Do not paste private records merely because the interface says local.

  4. Test the limit

    Give it a longer paragraph, ambiguous ownership and a missing deadline. It should report unknown information instead of inventing it. Record hardware and model details with results.

A prompt to adapt

Replace the bracketed parts with your own practice details.

From this fictional note extract task, owner and deadline. Use null for missing facts and list ambiguity separately. Do not infer dates. Note: [sample]. After answering, show the exact supporting phrase for each value.

What this looks like

“Maya will draft the outline; timing is undecided” should produce a known owner and an unknown deadline. A plausible Friday date is still fabricated.

Check your result

Use evidence from your output. A confident explanation from the AI is not enough.

  • The install came from official documentation.
  • The answer is compared with a known key.
  • Local and remote dependencies are explicitly understood.

If it isn’t working

If generation is unusably slow or memory runs out, stop and try a smaller model. Local availability is a hardware constraint, not evidence that a particular model is a good fit.

Where this came from

Adapted from the archived LinkedIn theme “My First Technology Empire Sold Illegal Nintendo Games to Ten-Year-Olds.” See the post coverage and editorial method.

Prepared September 2026. Tools and interfaces change; use current official setup instructions. Session lengths are estimates.

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