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JevMade field notes / Written guide

Running Decision Models Locally with Ollama

Raccoon Ninja explains how Ollama can run open decision models locally and return scores for supplied answers.

Original by Raccoon NinjaGetting started

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Our summary

Raccoon Ninja's local setup starts with a situation and a list of allowed answers. A decision model scores those answers and estimates how sure its choice looks. That is the idea the guide explains: choosing from supplied answers instead of writing an open-ended reply.

You cannot download Jev itself; it is closed-source. With Ollama version 0.35 or later, the guide instead runs alternatives such as Nimble and Tev1. Once a model is downloaded, a small program sends it situations and questions. The example categorizes an issue's severity.

Those questions stay on your computer rather than going to a hosted service, but larger models need suitable hardware. Local operation does not guarantee good decisions. The author also raises a simpler possibility: ordinary text-matching rules might solve the task without AI.

Key takeaways

  1. These local alternatives are not downloadable copies of TypeSafe's closed Jev model.
  2. Supply the situation and permitted answers, then examine the scores the model returns.
  3. Compare accuracy and hardware requirements with the option of using simple text-matching rules.

This is a setup tutorial, not a new model or independent performance test. Running the model locally keeps the questions on your computer; downloads and any other connected programs remain separate considerations.

raccoon.ninja · Original published

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