WeMM-JEV

WeMM-JEV is a multimodal decision model for text and images. It answers typed questions, returning probabilities in one 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.

Downloads last month
-
Safetensors
Model size
26B params
Tensor type
BF16
·
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support