decy-preview

Ask a question with fixed answers. Get one answer back, and how likely each answer is.

decy turns a model call into a decision. Instead of generating text you then have to parse, it reads your input once and returns a probability for every allowed answer. Questions can be about plain text, JSON records, chat logs or agent traces, in English or Vietnamese.

Preview release: weights and interface may still change.

Try it

import sys
from huggingface_hub import snapshot_download

sys.path.insert(0, snapshot_download("PNPM244/decy-preview"))
from decy import Decy

decy = Decy(model="PNPM244/decy-preview", device="cuda:0")

order = {"item": "running shoes", "status": "delivered", "days_since_delivery": 41,
         "message": "They hurt my feet, I want my money back."}
result, _ = decy(order, {
    "refund": {"type": "choice", "instructions": "How should this refund request be handled?",
               "criteria": {"approve": "Within the return window and policy allows it",
                            "escalate": "Needs a human agent to decide",
                            "decline": "Outside the 30-day return window"}},
    "upset": {"type": "noul", "instructions": "The customer sounds upset."},
})
print(result["answers"])

Several questions about the same input go in one call. choice questions pick one of the listed answers; noul questions are yes/no and return the probability of yes.

Why use it

• One pass, fixed cost. No sampling, no output parsing, no retries for malformed answers.
• Probabilities you can threshold. Route low-confidence cases to a person instead of guessing.
• Judges the answers on their merits. Catch-all answers like "None of the other options is correct" are picked only when the specific answers are actually wrong.

Hardware

BF16 weights take about 62 GB, so a single 80 GB GPU (A100/H100/H200) runs it. decy.py loads the model with transformers; bidir.py switches the global attention layers to read the input in both directions, which is how the model was trained and evaluated. Keep the defaults (noncausal=True, layout="state").

Benchmarks

Decision Index, public 0.3 suite: 68.03 (complete run, 140,620 requests, all answered; scored with the leaderboard's code). Results: PNPM244/decy-preview-decision-index. Official Full scores (private tests run by the maintainers) will be added when available.

Public index	Knowledge	Language	Retrieval	Tools	Arts
68.03	56.9	72.2	68.8	83.0	56.9

Latency on one H200, one request at a time: median 63 ms, mean 286 ms, p80 214 ms.

Reproduce the public suite with:

PYTHONPATH=<snapshot> python -m decision_index pipeline --engine decy:Decy \
  --option model=<snapshot> --option device=cuda:0 --out runs/decy-preview

License

Released under CC BY-NC 4.0 (weights, code and card). Non-commercial use only, with attribution; ask the author for commercial terms. Derived from Gemma 4, Apache 2.0: see NOTICE and LICENSE-APACHE-2.0.

Author: Tran Minh Duc (PNPM244), 2026.