huret-digit-classifiers

Fifteen October digit classifiers: identity, parity and magnitude, five seeds each. The trained arrays are retained from the CP02 replay. Architecture: 64 -> 32 ReLU -> 16 ReLU -> task head. This is the October HuReT audit, not an MRI model and not the missing July model archive.

Local use

python -m pip install -r requirements.txt
python validate.py

Import predict from inference.py; see config.json for input semantics. Inputs are not automatically normalized except as specified. Loaders reject wrong shapes, nonfinite values and invalid model selectors. Weight files are NumPy archives or JSON; no pickle/custom remote execution is required.

Evidence and limitations

The validation is loader parity and input-contract testing, not independent external predictive validation. No clinical deployment, universal physics, foundation-model quality or new biological evidence is claimed. These are individual finite model families, not repackaged third-party LLMs.

Licensing and provenance

Private staging. Author approval and redistribution rights must be confirmed before public upload. No new blanket license, completed HF upload or DOI is asserted. PROVENANCE.json records exact source file hashes and transformations.

Verified packaging revision — 2026-10-20

Preserved model weights reloaded; saved or synthetic example checks passed. No training, held-out evaluation, clinical or hosted verification.

Runtime state: PASS. Rights and release approval are separate. See RELEASE_VERIFICATION.json. No paper or conference submission is included as a new software result.