ADR-129: RuvLTRA Training Pipeline — All Phases Executing#314
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ADR-129: RuvLTRA Training Pipeline — All Phases Executing#314
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…complete - Phase 1 Calibration: Complete (all 4 models, benchmarks uploaded to HF) - Phase 2 SFT: Executing on L4 GPU (rank-16, 2 epochs) - Phase 3 Benchmarks: Executing (release gates + L4 benchmark job) - Phase 4 Publishing: Complete (TQ configs + benchmarks + README updates on HF) Benchmark results (L4 GPU): - ruvltra-small: 75.4 tok/s - ruvltra-medium: 62.6 tok/s - ruvltra-claude-code: 67.1 tok/s Co-Authored-By: claude-flow <ruv@ruv.net>
Add Continuous Training & Optimization section (ADR-129) to the capabilities table: nightly training, 7-gate release checks, TurboQuant profiling, training corpus. Co-Authored-By: claude-flow <ruv@ruv.net>
The SFT job failed because merged_corpus.jsonl was not in the Docker image. Copy it to scripts/training/data/training/ so it's included in the COPY . /app/ step. Co-Authored-By: claude-flow <ruv@ruv.net>
The training corpus uses a flat 'text' field (brain memories, ADRs) rather than chat messages or Alpaca instruction format. Add handler that converts raw text to completion-style messages for SFT. Co-Authored-By: claude-flow <ruv@ruv.net>
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Summary
Updates ADR-129 status — all 4 phases of the RuvLTRA training pipeline are now executing on Google Cloud.
What's Been Done This Session
Phase 1: Calibration (Complete)
default.turboquant.json) uploaded to all HuggingFace reposPhase 2: SFT Training (Executing)
Phase 3: Benchmarks (Executing)
Phase 4: Publishing (Complete)
Infrastructure Deployed
gcr.io/ruv-dev/ruvltra-training:latestruvltra-calibrationCloud Run Jobruvltra-nightly-trainCloud Run Jobruvltra-benchmarkCloud Run JobPrevious Commits on Main
All implementation was done on main during this session:
turboquant_profile.rs(Rust sidecar loading)Ref: #310
🤖 Generated with claude-flow