A candidate-scoring head returns distributions for gates, routes and scores without decoding prose or JSON answers. The README compares a benchmark-trained AgentJev specialist with Jev 1.13.0 evaluated zero-shot; these use different training conditions.
luce: a recipe for calibrated decision models
scienthoon/luce
VerifiedResearchDocumented
luce: a recipe for calibrated decision models — a sentence about your task in, a small model that answers typed questions. See Jev references and source code.
Repository description: Luce: a recipe for calibrated decision models — a sentence about your task in, a small model that answers typed questions with honest probabilities out (init → synth → train → eval → serve)
What you can build with it
Get started
Clone the repository and follow its README for install and usage. JevHunt has not run this project.
git clone https://github.com/scienthoon/luce.gitProject facts
- Relationship to Jev
- Research
- Evidence
- Documented
- Language
- Python
- License
- Apache-2.0
- Origin
- Original repository
- Repository status
- Not archived
- Created
- 2026-09-20
- Last code update
- 2026-09-22
- GitHub stars
- 7
- Evidence checked
- Sep 29, 2026
- Metadata checked
- Sep 29, 2026
- Check status
- Up to date
Stars measure the whole repository, including work unrelated to Jev.
Evidence and scope
Documented records the linked documentation or source. JevHunt has not independently run or benchmarked this project.
Three question types, same as TypeSafe's Jev interface: **Choice** (one of N options), **Score** (an ordered scale), **Noul** (a statement is true or false).
Evidence commit: bda3d21cdb537ae99662fdba275adc450e90f455
Discovered through: typesafe-field-guide.
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