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Jev project · Benchmarks & research

jev-on-a-laptop

rorshopping/jev-on-a-laptop

Unofficial study: Jev-style parallel typed decisions on stock 1.5B-8B models on an Apple Silicon laptop. Benchmarks, research notes, and a Hugging Face Space demo.

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GitHub stars
23 as of 2026-09-22
Forks
1
Language
Python
License
Check upstream
Created
2026-09-16
Last updated on GitHub
2026-09-17
Added to AionEdge
2026-09-19
Built by this developer
Richard Bäcker

What Jev does in jev-on-a-laptop

The project describes itself this way: Unofficial study: Jev-style parallel typed decisions on stock 1.5B-8B models on an Apple Silicon laptop. Benchmarks, research notes, and a Hugging Face Space demo. In the Benchmarks & research category, Jev typically decides labels and probabilities on fixed test sets, so accuracy, calibration and latency can be measured.

Verification

Verified. We confirmed this repository and its Jev relevance through the GitHub API and the source lists below. A specific file link has not been recorded yet.

How Benchmarks & research projects use Jev

Benchmarks and research projects test Jev rather than just use it. They compare it with language models and other classifiers, check whether its probabilities are well calibrated, and explore where the decision-model approach breaks down.

Related Jev projects in Benchmarks & research

  1. jevifyaltryne/jevifyAn Agent Skill for finding suitable Jev decision points and designing questions and comparison experiments.★ 24
    Python
  2. jev-curateAkashPriyadarshii/jev-curateA Rust dataset-filtering experiment using Jev scores to keep or reject text records.★ 26
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  3. jev-benchmarksAbdelStark/jev-benchmarksA benchmark comparing Jev and GLiNER on text classification, probability calibration and selective automation.★ 17
    Python
  4. jevcalabhixhek/jevcalA toolkit for evaluating Jev probabilities on labeled data, selecting confidence thresholds and checking model drift.★ 10
    Python
  5. typesafe-ai-benchmarkiammrduncan/typesafe-ai-benchmarkCompares Jev with other structured-output models on shared application tasks, recording errors, latency, Tokens, and estimated cost.★ 38
    TypeScript
  6. jev-lmy0usaf/jev-lmA word-level generation experiment that asks Jev to select words or verify locally drafted continuations.★ 6
    TypeScript

See all 107 Benchmarks & research projects →

Where we found it