Build your own decision model
Tutorial contrasting one-pass option probabilities from a decision model with an LLM that needed 11 passes to emit the same JSON.
This summary is based on how curated lists describe the project; its README was not available to review.
Overview
A tutorial on nishtahir.com explaining how a System One model answers every allowed option with a probability in a single pass. In its worked example, a language model constrained to emit the same JSON needed 11 passes.
It is aimed at developers who want to understand or reproduce the mechanism.
What the decision model decides
| Type | Question | Answers |
|---|---|---|
| Choice | Example classification used to show one-pass option scoring(inferred) | — |
How it works
- Explain constrained decoding with an LLM
- Contrast with scoring all options in one pass
- Build a small decision model
Strengths
- Clear mechanism explanation
Caveats
- Only list summary available
At a glance
- Type
- Article
- Status
- discussion
Use cases and integrations
How curated lists describe it
Tutorial: explains that a System One model answers every allowed option with a calibrated probability in a single pass, where a language model constrained to emit the same JSON took 11 passes in the worked example.
yibie/awesome-jev
Frequently asked questions
What is the key idea?
Scoring every option in one pass instead of decoding JSON token by token.
How many passes did the LLM need?
11 in the worked example.
Where is it?
https://nishtahir.com/build-your-own-decision-model
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