rUv
ace0b276d2
fix(training): use torch 2.5.1+cu124 (2.3.1 unavailable on cu124 index)
...
Co-Authored-By: claude-flow <ruv@ruv.net>
2026-03-28 14:26:28 +00:00
rUv
dc53af1640
fix(training): add libgomp1, optimize Dockerfile for cache + CUDA wheels
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- Add libgomp1 (required by llama-cpp-python OpenMP)
- Use PyTorch cu124 index for proper CUDA wheel
- Set default CMD with --model-id for Cloud Run execution
- Consolidate pip installs for Docker layer cache efficiency
Co-Authored-By: claude-flow <ruv@ruv.net>
2026-03-28 14:20:54 +00:00
rUv
7f3e0ea1dd
fix(training): use prebuilt llama-cpp-python CUDA wheel
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The pip install of llama-cpp-python from source requires ninja + cmake
for CUDA compilation. Use the prebuilt wheel from the cu124 index instead.
Falls back to source install, then transformers-only mode.
Co-Authored-By: claude-flow <ruv@ruv.net>
2026-03-28 13:44:48 +00:00
rUv
7407f78230
refactor(training): use ruvllm-native tooling instead of llama.cpp
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- Rewrite run_calibration.py to use gguf Python package + llama-cpp-python
prebuilt wheels instead of compiling llama.cpp from source
- Simplify Dockerfile: single-stage, pip install only, no CUDA compilation
(build time: ~5min vs 20+min)
- Update ADR-129 with tooling decision section explaining ruvllm-native choice
- Remove llama-imatrix and llama-quantize binary dependencies
Co-Authored-By: claude-flow <ruv@ruv.net>
2026-03-28 13:40:14 +00:00
rUv
f12e6c1584
feat: implement ADR-129 training pipeline and TurboQuant sidecar infra
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Training tooling:
- release_gate.py: Automated 7-gate ship/no-ship checker (G1-G7)
- export_training_data.py: Dataset export with governance (schema,
dedup, quality scoring, contamination check)
- contamination_check.py: 13-gram eval contamination detection
- run_calibration.py: Phase 1 imatrix + TurboQuant profiling
- run_sft.py: Phase 2 LoRA SFT + DPO training
- deploy_training.sh: Cloud Run job creation + Vertex AI setup
- Dockerfile: GPU training image (transformers + peft + trl)
Rust infrastructure:
- turboquant_profile.rs: .turboquant.json sidecar config loading,
per-layer TQ config discovery, default profiles
Ref: ADR-129, #310
Co-Authored-By: claude-flow <ruv@ruv.net>
2026-03-28 02:27:32 +00:00
