ZeroPoint scores options against an implicit none state on a CPU. Read its bundled model, short input budgets and saved missing-option tests.
By Javier Marín · First published package release; October catch-up: 31 Oct 2026
A CPU decision model that scores supplied options against a fixed zero-energy none state. It packages an encoder derived from multilingual-e5-small, ONNX weights and a fitted head. Its runtime sorts options into a canonical order before scoring, so order consistency belongs to the complete serving path.
ZeroPoint: A CPU decision model that scores supplied options against a fixed zero-energy none state.
ZeroPoint: Javier Marín
Source: Code and bundled model → Source: Saved comparison → Source: Licence → Source: Model manifest → Source: Package releases →
Scores option labels and an implicit none state using a bundled ONNX encoder and fitted head. The maker publishes saved comparisons, model hashes and fitting code. Canonical option sorting and one-case inference are part of its consistency recipe. The 900-case matched comparison reports 53.6% correct including none, with half the cases having no right option. Short input budgets and truncation flags remain explicit.