Vons model card
Status: research source preview. This package contains no pretrained weights, tokenizer files or benchmark datasets.
Intended use
Vons studies bounded candidate selection and abstention in agent workflows. A host supplies the state and candidates. The host alone enforces permission, consent and execution policy. KASI is a separate compatibility adapter.
Architecture and target
The research implementation offers a Direct scorer and a conditional Diffusion
scorer. Pilot configurations pin google/bert_uncased_L-4_H-256_A-4 at revision
387825ce42dbb39b87911cdf8e383ee3b25184f8. This identifies a research dependency;
its assets are not included or relicensed here.
English-first input and a model asset budget below 64 MiB are design targets. Runtime libraries, complete download size and memory use are distinct quantities.
Evaluation and limitations
Historical local experiments include synthetic pilots and an evaluation-only external benchmark diagnostic. A separately labelled post-freeze v2 handoff records dynamic per-request padding, balanced four-class synthetic runs, vector-scaling calibration, a token-conditioned Diffusion head and label-free Mind2Web context compression. Those bounded synthetic, local-CPU and conditional-selection results do not establish general task quality, production readiness, calibrated safety or a Direct/Diffusion superiority claim. Reviewed numerical claims belong to the versioned paper and Tech Report, with exact evidence references. Unreviewed historical tables are not distributed as current results.
The ONNX candidate head does not support general score questions. Python and TypeScript now both pad to the longest live tokenized candidate within the manifest budget, but their broader public contract semantics are not claimed to be identical. Browser smoke, local CPU timing, graph-partition parity and memory evidence remain separate checks.
Do not use model confidence as a permission grant or assume it is calibrated. Vons cannot execute tools or approve high-risk actions.
Data and provenance
Synthetic data can be generated from the source. Restricted data, model-generated raw responses, private prompts, model checkpoints and local manifests are excluded from this distribution. Obtain any external dataset under its own terms. The source release manifest records hashes of the files actually exported.
Author and terms
Kwangseob Ahn — INLEVEL9 / SEJONG UNIV. — oswarld@inlevel9.com.
The Vons-owned source is prepared under Vons Community and Commercial License 1.0: noncommercial community use is free; enterprise/commercial use requires a separate written agreement. The articles and their original figures use CC BY 4.0. Third-party assets retain their own terms, and no model weights are licensed or included by this source-only card. See licensing scope and release preparation.