nspam — Nostr reply-spam classifier (v2.2)

On-device spam scoring for Nostr reply notes. See model_card.md for details.

Files

file	purpose
`model.txt / model.json`	trained model
`calibration.npz`	isotonic calibration table
`config.json`	feature layout + hashing convention
`parity_fixtures.jsonl`	reference inputs + expected scores
`hash_fixtures.jsonl`	token-level hash checks

A port needs:

Feature extraction — reproduce preprocessing + hashing + structural features. See config.json for the exact layout.
Model inference — load model.txt via LightGBM4j (Kotlin/Java), LightGBM C API, or ONNX conversion.
Calibration — piecewise-linear interpolate the raw score through calibration.npz knots.

Validate your port against parity_fixtures.jsonl.