kev-finetune

Name: kev-finetune
Author: jaredpalmer/kev

About kev-finetune

Fine-tune a Kev decision model (open Jev-style System One model) on a user's own workload and serve it with calibrated probabilities. Interviews the user, finds existing Jev/TypeSafe questions or labelled data in their codebase, generates enough synthetic training data to measure a gain, trains and calibrates on Modal, scores against the released checkpoint, deploys a TypeSafe-compatible endpoint, and tears everything down. Use when someone wants noul/choice/score questions answered on their own domain (routing, triage, moderation, classification, scoring), wants calibrated confidence for automation thresholds, mentions Jev, TypeSafe, System One or Kev, or asks to fine-tune, evaluate, deploy or clean up Kev.

Install

Copy the command and run it in a terminal.

$npx skills add https://jaredpalmer/kev --skill kev-finetune

After installing, type/kev-finetunein Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

README.md

assets/

workload.example.json

references/

hill-climbing.md

data-format.md

deploy.md

data-generation.md

scripts/

convert_data.py

extract_workload.py

kev_modal.py

generate_data.py

split_data.py

plan_size.py

Comments

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Details

Author: jaredpalmer/kev
Category: Data & databases
Installs: 72

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