feat: ADR-071 ruvllm training pipeline — contrastive + LoRA + TurboQuant
5-phase training pipeline using ruvllm (Rust-native, no PyTorch):
1. Contrastive pretraining (triplet + InfoNCE, 5 triplet strategies)
2. Task head training (presence, activity, vitals via SONA)
3. Per-node LoRA refinement (rank-4, room-specific adaptation)
4. TurboQuant quantization (2/4/8-bit, 6-8x compression)
5. EWC consolidation (prevent catastrophic forgetting)
Exports: SafeTensors, HuggingFace config, RVF, per-node LoRA, quantized
Validated: 249 triplets, 37,775 emb/s, 100% presence accuracy on test data
Target: <5 min training on M4 Pro, <10ms inference on Pi Zero
Co-Authored-By: claude-flow <ruv@ruv.net>
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