README.md

metadata

title: decider-4b systemone
emoji: ⚖️
colorFrom: indigo
colorTo: gray
sdk: gradio
sdk_version: 5.49.1
app_file: app.py
pinned: false
license: apache-2.0
short_description: Jev-shaped choice/score/noul decisions on decider-4b

decider-4b, in Jev's shape

A typed-decision service wrapping Mapika/decider-4b (4B dense, Qwen3.5-4B-Base, Apache 2.0) on ZeroGPU.

Give it a state and typed questions; get probabilities and confidence back. No text generation, so nothing to parse and nothing to hallucinate.

type	question	answer
choice	which of these options?	the option, a probability per option, confidence
score	where on this rubric?	a position along your levels, distribution
noul	is this true?	noul: the probability that it is

Why this Space exists

decider-4b is one of the open "System One" models benchmarked against Jev. This wrapper adds the pieces the raw checkpoint leaves to the caller, so it can be scored on the same harness as everything else:

• the endpoint signature mirrors dkappe/IDU's systemone (state, questions, three temperature overrides) and returns the same (table, raw-json) tuple, so one harness drives both without a special case;
• per-answer-type temperature is honoured. decider_config.json carries temperature_by_type {choice: 1.11, noul: 1.56, score: 1.287}; serving everything at the single fitted 1.099 flattens the yes/no and Score probabilities. Pass 0 for a temperature to keep the checkpoint's value.
• the TypeSafe response shape (choice / confidence / probabilities, score + legend, noul as a probability) is produced by the authors' own systemone.py.

Endpoints

• systemone — (state_text, q_text, tc, ts, tn) -> (answers_table, raw_json)
• health — device, checkpoint version, temperatures in force

Capacity

max_options 255, max_state_tokens 32768. This model has no small option-count cap: the 16-option ceiling that stops Plumb 4B and SemIf does not apply here, and neither does Nimble's 8K input limit.

Notes

• Scoring path is the authors' reference implementation, vendored verbatim in decider/ from the model repository (Apache-2.0). Deviations are documented in app.py.
• The checkpoint is loaded once at module scope and moved to CUDA eagerly, which is the pattern the official decider demos use on ZeroGPU.
• Apache 2.0, weights and wrapper both.