Quyet

Quyet is a family of decision models. Give it a state (any text, JSON or conversation) and one or more typed questions; it picks one option per question and returns calibrated probabilities. Nothing is generated: every answer is a probability distribution over the options you supplied.

This package is the runtime for all Quyet 1.0 models. The weights are on Hugging Face.

The models are built for English and also tuned for Vietnamese; other languages work, with lower accuracy. Small-EN is trained on English only.

Install

pip install quyet                 # CPU or single GPU
pip install "quyet[multi-gpu]"    # spread Quyet-1.0-Large over several GPUs (device_map="auto")

Python 3.10 or newer. The first quyet.load downloads the weights from Hugging Face.

Use

import quyet

m = quyet.load("chinhnc/Quyet-1.0-Small")
r = m.predict(
    {"message": "Please close my card, I lost it yesterday."},
    {"intent": {"type": "choice", "instructions": "What does the customer want?",
                 "criteria": {"cancel": "close the card", "limit": "change the limit", "other": None}},
     "urgent": {"type": "noul", "instructions": "The request is urgent."},
     "mood": {"type": "score", "instructions": "How upset is the customer?", "criteria": ["calm", "annoyed", "angry"]}},
)
print(r["answers"])

quyet.load(name_or_path, device=None, revision=None, dtype=None, device_map=None) accepts a Hugging Face repo id or a local directory. predict_many answers a list of requests; raw_probabilities returns the uncalibrated distributions.

Question types and answers

Answers follow the TypeSafe /v1/systemone shape:

• choice: pick one label from criteria (a dict of label to description, or a list of labels). Answer: choice, confidence, probabilities.
• score: an ordered scale given as a list of levels. Answer: expected level score, probabilities, legend.
• noul: a statement that is true or false. Answer: noul = P(true).

Probabilities are temperature-calibrated per question type and option count.

Command line

quyet predict chinhnc/Quyet-1.0-Small < requests.jsonl > answers.jsonl

Each input line is {"state": ..., "questions": {...}}; each output line is the response or {"error": ...}. Options: --input FILE, --device cpu|cuda|cuda:1, --strict (fail instead of truncating a long state).

Limits

• At most 10 options per question; more are rejected, not truncated.
• Only the state is ever truncated: conversation lists keep their most recent turns, other states keep their beginning. Encoders read 8,192 tokens; the LLMs keep up to 6,000 state tokens.
• Not evaluated for safety, bias or adversarial robustness; do not use as the only control for high-stakes decisions.

Licence and credit

Apache-2.0 for the code and the weights. Keep the NOTICE file, which starts with "Quyet by Chinh Nguyen", when you redistribute this package, a model, or anything derived from them.

@misc{quyet2026,
  title  = {Quyet 1.0: calibrated decision models},
  author = {Chinh Nguyen},
  year   = {2026},
  url    = {https://github.com/ncchinh/quyet}
}

Questions and issues: GitHub issues or email@chinh.com.