README.md

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title: NorviTech
emoji: 🛡️
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colorTo: blue
sdk: static
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NorviTech — Armiger v3.0 (v3.0-gold-r5) Neural Torrent & DHT Intelligence

NorviTech develops Armiger v3, a 9-head byte-level RoPE Transformer (8.30M parameters) with a modular plugin suite for high-throughput classification, safety gating, and canonical title/year extraction on raw BitTorrent and DHT metadata.

Official Model Repositories

• NorviTech/armiger-ultra (Flagship — 32.7 MB FP32 + 8.3 MB INT8 + 6 plugins): FP32/INT8 ONNX, PyTorch checkpoint, 7-tag Viterbi span extractor, and all 6 plugins (SwarmSurvivalNet, SwarmPriors, ZeroCueCatalog, AudioLanguageGuard, CalibrationAndDHT, ArmigerDHTDBSync) behind ArmigerUltraPipeline. 0.21 ms/item batched GPU; 96.86% 6-dimension LOTO (Suite B LOTO N=1,025), 97.01% 11-class (W5A-Test N=703), 91.27% 9-class (R5-Test N=996).
• NorviTech/armiger (CPU edition — 8.3 MB INT8 ONNX): CPU-only (numpy + onnxruntime). 2.44 ms/item single-item (326 items/s batch-64, M4 Pro CPU); 99.90% parity with FP32 (91.16% on R5-Test N=996; 96.85% on Suite B LOTO N=1,025).
• Components (bundled in NorviTech/armiger-ultra): armiger-swarm-survival · armiger-swarm-priors · armiger-zero-cue-catalog · armiger-audio-guard · armiger-calibration-dht · armiger-dht-db-sync

Connectors & Integrations

• Core model, training & evaluation: spencernorton/armiger · License: Apache-2.0
• Standalone sidecars for unmodified indexers (spencernorton/Armiger-Connectors):
  • Stock Bitmagnet (bitmagnet-io/bitmagnet): bitmagnet/bitmagnet_connector.py — polls untagged torrents via GraphQL, runs vectorized Armiger inference, prunes .exe/.scr/.lnk malware and honeypot traps, writes armiger-* tags.
  • Stock Rats Search (librats/rats-search): rats-search/rats_search_connector.py — drop-in REST/SQLite sidecar classifier and safety filter.
• Turnkey indexer, Torznab & *Arr stacks (examples/ at v2.1.3 · Integration Guide):
  • DH-Waypoint processorapi/v1 plugin (spencernorton/DH-Waypoint): examples/dh-waypoint/ — pre-ingest admission (/v1/admit), batch classification (/v1/classify), 4-tier feedback (/v1/feedback).
  • Bitmagnet pre-ingest & GraphQL bridge: examples/bitmagnet/ (bitmagnet_armiger_bridge.py).
  • Torznab pre-grab proxy (Prowlarr/Sonarr/Radarr/Lidarr/Readarr): armiger_torznab_proxy.py — filters malware lures, dead swarms, and unrequested foreign-audio releases before grab.
  • Post-import *Arr/qBittorrent webhook: armiger_arr_webhook_receiver.py — ffprobe ground truth for local conformal calibration and opt-in anonymous BEP-44/46 updates.