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feat(distill): tiny client tier — byte-vocab students + microkimi bridge KD - #23
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August 21, 2026 23:58
…imi bridge KD Reconstruction after an accidental reset --hard wiped the uncommitted work (running containers kept their snapshots; this restores source). - student_config: custom T5Config byte-vocab students (33M/70M rungs) - distill_microkimi: calibration -> ridge-solved frozen projectors -> CE + hidden-MSE (rescues the from-scratch collapse: 75.8 -> 71.12 PER at 33M; 70M rung in flight) - out_volume: outputs on the secryst volume (rababa volume serves torn reads cross-container) - labels_complete / labels_file / torn guard; hardened Step-2 - r6 canonical Arabic teacher; persian datasets volume + data_volume override (six-mount shadowing workaround); jsonl corpus limits
Measured quantization deltas on khm: fp16 ~0.43pp, int8 ~0.84pp against the flat 0.2pp bar, so quantized client zips could never pass strict. Limits keyed on metadata.precision; unknown precision falls back to the fp32 bar.
…ation Re-measured run-003 on the beam-4 harness (12.06% PER, EM 87.94%, +7.63pp over the 4.43% teacher, n=1219). Capacity-limited but the smallest non-collapsing rung; exported at int8 (~300MB) per the frontier table. Frontier row updated 12.63 -> 12.06 (full-label run).
ml-models -> interscript/interscript-ml everywhere (index URLs, metric sources, workflow provenance subject, script defaults, Modal container paths); interscript-ml-train app renamed; root tooling package renamed interscript-ml-tools (runtime keeps the interscript-ml pip name); npm manifest package marked deprecated, never published, license BSD-3; TODO.distribution names mechanically updated + historical banner. Old names survive only inside deprecation notes explaining them.
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Aug 22, 2026
metrics-sources pins this section at ref release/tha-g2p-small-1.0 until it lands on main via PR #23 (fas-g2p release-branch pattern).
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Summary
student_config: custom byte-vocab T5 students (33M/70M rungs) — byte vocab makes embeddings negligible, so small transformers are almost all compute (~30MB int8 artifacts)distill_microkimi: calibration → ridge-solved frozen projectors → CE + hidden-MSE training; measured effect on the from-scratch collapse: 75.8 → 71.12 PER (Thai, 33M)out_volume: student outputs on the secryst volume — the rababa volume serves torn reads to subsequent containerslabels_complete/labels_file/torn-view guard; hardened Step-2 label loadingdata_volumeoverride (six-mount shadowing workaround); jsonl corpus limitsTest plan