by Heman10x-NGU · Agent Tool · ★ 110
OpenJev (Verdict): Non-Autoregressive Decision Engine (151M) OpenJev (Verdict) is an open-source, post-trained foundational decision model designed for structured software workflows, inspired by TypeSafe AI\'s Jev and Reinforcement Learning for Calibrated Decisions (RLCD). Instead of generating free-form conversational text that software must parse and validate, OpenJev accepts unstructured input context and evaluates multiple typed questions in a single non-autoregressive forward pass.
| Stars | 110 |
| Forks | 14 |
| Language | Python |
| Category | Agent Tool |
| Quality Score | 60.3011799567112/100 |
| Open Issues | 7 |
| Last Updated | 2026-09-28 |
| Created | 2026-09-17 |
| Platforms | browser, python |
| Est. Tokens | ~20k |
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Verdict-open-jev is Non-autoregressive decision engine on ModernBERT (151M) with calibrated uncertainty (RLCD), TypeSafe AI Jev benchmark audit, and in-browser WebGPU playground. It is categorized as a Agent Tool with 110 GitHub stars.
Verdict-open-jev is primarily written in Python. It covers topics such as brier-score, calibration, decision-engine.
You can find installation instructions and usage details in the Verdict-open-jev GitHub repository at github.com/Heman10x-NGU/Verdict-open-jev. The project has 110 stars and 14 forks, indicating an active community.