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laya-self-train-prime

archaeus-ai/laya-self-train-prime

Self-tuning Laya: typed decision to calibrated System One model.

Classification & Routing0.56Runner-up: Infra / SDKs / IntegrationsTraffic lightCheck-up
Automated README summary

Automatically summarized from the README on 13 Oct 2026; not a run by jevbooks. Run instructions and author-reported outcomes still need verification.

What it is

A CLI plus Claude Code skill that turns one typed decision (route a ticket, score a lead, flag a message) into a fine-tuned, calibrated, evaluated Laya checkpoint served on the Jev-compatible wire protocol, on your own hardware.

How it uses Jev

Jev is used as a comparison baseline: `laya-prime compare --url` scores the held-out test split through Jev with the project's exact question, fits a refit (logistic layer on Jev's probabilities) on the train split, and adds both rows to the eval card next to fine-tuned Laya and TF-IDF, with a verdict.

Primitives:choicescorenoul

Technique worth stealing

Feasibility gate with option budget and two blind labelling passes refuses when classes are not separable from the text.

Try it

pip install -e ".[serve]" then laya-prime init, add, check, train, eval, serve.

View on GitHub

Start using Jev: API key and your first request →

Model judgments from README excerpts

Project signals use repository metadata, an existing summary and the first 700 README characters, not the full project. “Not found” means not detected in that material; it does not establish absence. These are the original judgments with recorded models and dates, not source audits or run results.

Models & evaluation dates

Inclusion gate
jev-1.13.0
Project signals
jev-1.13.0
Category
jev-1.13.0
Pattern tags
jev-1.13.0

Evidence

These signals use repository metadata, an existing summary and at most 700 cleaned README characters. ≥ 0.60 means reported in that excerpt; ≤ 0.40 means not found there. The middle band is inconclusive. None is a source-code audit or a test result. The runnable-tool question excludes research experiments; the recommendation question asks for a learning shortlist, not a quality verdict.

  • Jev is core to the projectFound in material0.66
  • Shows a System One patternunclear0.42
  • Describes handling uncertaintynot found in the excerpt0.05
  • Reports measured numbersnot found in the excerpt0.07
  • Is a runnable toolFound in material0.90
  • Top-10 learning shortlist signalnot found in the excerpt0.25
  • Is a replica of the modelFound in material0.84
  • Solves a common problem (0–2)score on a 0–2 scale1.25 / 2
  • About JevFound in material0.91
Signals
Jev is core to the project0.66Shows a System One pattern0.42Describes handling uncertainty0.05Reports measured numbers0.07Is a runnable tool0.90Top-10 learning shortlist signal0.25Is a replica of the model0.8400.51Solves a common problem (0–2)1.25 / 2012

no-judgment band (0.40–0.60)

Design patterns
Check-up0.85Traffic light0.81Questionnaire0.36Viewfinder0.30Funnel0.2800.51

no-judgment band (0.40–0.60)

The Jev model and date for each judgment stage are listed above. Card written by DeepSeek V4.1 Flash from the README on 13 Oct 2026.