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NanoJev

TianyuCodings/NanoJev

A 0.6B parallel decision model returning full probability distributions.

Game & Simulation76%Runner-up: Agent Decisions

What it is

NanoJev is an open replica of Jev: a 0.6B parallel decision model that takes states and questions and returns complete probability distributions without output-token decoding, shipped with its training pipeline, weights, and dataset for four game tasks.

How it uses Jev

Each request supplies a state, a question, and its candidates. The backbone encodes candidate paths; shared heads produce requested probabilities. Choice uses set attention and softmax, Boolean uses sigmoid, and Score returns a probability-weighted level. Results rank, select, or sample actions without generating answer tokens.

Primitives:choicescorenoul

Technique worth stealing

Batch independent states, questions, and candidate paths in one backbone forward for parallel decisions.

Try it

Clone repo, install requirements-toy.txt and huggingface_hub, download checkpoint and data, run scripts/serve_decisions.py.

View on GitHub

judged by Jevjev-1.13.0

Evidence

Each line is one question put to Jev about the README. ≥ 0.60 reads as yes, ≤ 0.40 as no; in between Jev is not making a call.

  • Jev-centricyes0.82
  • Shows a System One patternunclear0.60
  • Handles uncertaintyno0.04
  • Measuredno0.15
  • Runnableunclear0.43
  • Worth recommendingno0.36
  • Model replicayes0.97
  • Problem scopescore on a 0–2 scale0.05
  • About Jevyes0.97

Signals by Jev jev-1.13.0, card written by DeepSeek V4.1 Flash from the README on 20 Sept 2026.