---
title: JEV-9B Decision API
emoji: ⚖️
colorFrom: blue
colorTo: gray
sdk: gradio
sdk_version: 6.28.0
app_file: app.py
python_version: "3.12"
startup_duration_timeout: 1h
pinned: false
---

# JEV-9B Decision API

A minimal, machine-friendly wrapper over **System 1** of
[`autotrust/JEV-9B`](https://huggingface.co/autotrust/JEV-9B) — AutoTrust AI's open
*decision* model (Apache-2.0), built with the Blocks-of-Experts recipe on a frozen
Qwen3.5-9B backbone.

System 1 answers a **typed question** in a *single prefill pass* (nothing is generated)
and returns a **calibrated probability distribution**:

- `noul` — "Is this true?" → `[P(false), P(true)]`
- `choice` — which of 2–16 options → one probability per option
- `score` — where on an ordered 0–5 scale → distribution over six levels

## API

A single Gradio endpoint, `/decide`, taking `kind`, `state`, `question`, `options`
(comma-separated, `choice` only) and returning JSON:

```json
{"kind":"choice","distribution":{"a":0.53,"b":0.33,"c":0.14},"best":"a",
 "confidence":0.53,"state_tokens":18,"truncated":false}
```

This Space exists to give local agents (Hermes) one clean JSON call, rather than the
multi-question HTML UI of the upstream demo. Inference core (`jev_core.py`) is the
model authors' documented `transformers` + `peft` path, reused verbatim.

### Provenance & limits

`jev_core.py` is reused unmodified from the authors' official demo Space
([`autotrust/jev-9b-decision-demo`](https://huggingface.co/spaces/autotrust/jev-9b-decision-demo)),
which is Apache-2.0. Model card caveats still apply: System 1 mirrors its teacher
**including its mistakes** (multi-hop reasoning, arithmetic, dates, counting, adversarial
inputs), reads English best, uses the first 1,024 tokens of state, and is **not for
high-stakes decisions** — use confidence gating and route low-confidence decisions
elsewhere. Runs on ZeroGPU (`zero-a10g`).