README.md

metadata

license: apache-2.0
library_name: pytorch
tags:
  - decision-model
  - multimodal

WeMM-JEV

WeMM-JEV is a 27B multimodal decision model based on Qwen3.8-27B. It supports choice, noul (yes/no) and score questions over text and multiple images, returning probabilities in a single forward pass per question.

• Choice: select among supplied options.
• Noul: estimate the probability of a yes/no proposition.
• Score: return a probability distribution over ordered levels.

Public Decision Index 0.3

Panel	Public index
Text	69.37
Vision	77.97

Detailed evaluation results

Usage

Install the dependencies in inference/README.md, then run from your local model directory:

cd /path/to/WeMM-JEV
python - <<'PY'
from inference import D3Engine

engine = D3Engine(model=".", device="cuda:0")
response, _ = engine(state="The light is red.", questions={
    "color": {"type": "choice", "instructions": "What color is the light?",
              "criteria": {"A": "Red", "B": "Blue"}}
})
print(response)
engine.close()
PY

See text and image examples, the HTTP server and Decision Index integration.