Historical Nanochat
Time-locked language models trained on pre-cutoff historical texts using Karpathy's nanochat pipeline. Exploring whether small models trained exclusively on period texts can reproduce the linguistic patterns of their era.
- 65GB historical text corpus across multiple eras
- Time-locked training methodology (no future-leaked text)
- RTX 3090 local training pipeline
- Parquet-based shard management
Activity Timeline
1.27TB / 3.1M files analyzed. Audit target holds only 93.8MB transcripts + 7.4GB uncovered user files. 715GB nanochat dataset confirmed on root disk.
nanochat main scrubbed via sanctioned publish path and released to historical archive. Secret scanning enabled and verified via gh API on 5 repos. psyche-public SECURITY.md/README contradiction and ETHICS-PROTOCOL staleness resolved.
Root partition reduced from 94% to 91% full (114G → 169G free). Live service dependencies verified before deletion including uv-cached venvs and Maya1 voice model; all services confirmed healthy post-cleanup.
npm, HuggingFace strike-list, Docker, pip, pnpm, and Trash caches verified and purged. maya1 voice model held due to live config and service code dependencies.
Disk audit identified largest consumers: 715G dataset (execution blocked), 362G workspace, 171G cache. Post-incident CUDA toolchain drift (13.1→13.3, driver 590→595) means original training run is no longer reproducible bit-identical.
mSBC Bluetooth codec confirmed as primary STT quality degradation source (7 kHz vs 8 kHz effective bandwidth). LibriSpeech harness built for WER measurement against 354 voice clips. Three VRM/avatar repos identified for image-to-3D pipeline feasibility.
Plaintext API key and live staging IP removed from 6 published files (23 substitutions). Key rotation required before containment. Dependabot sequence complete, total vulnerabilities 94→11.
Torch bumped 2.9.1 → 2.13.0 with smoke tests. fastapi 0.140 / starlette 1.3 compatibility confirmed across 73 tests. Chat web server hardened to bind localhost-only by default.
Empirical verification via code inspection and pytest confirmed every fix. Checkpoint timing defect (P0-1) resolved by consumed_loader_state tracking across base_train.py. Smoke test parameters scoped: SAVE_EVERY=250, MAX_STEPS=300.
Checkpoint-ahead-of-consumption fixed via separate consumed_loader_state tracking (base_train.py:517-523). Sol proxy stalled; pivoted to direct CPU-side verification with test suite tripwires confirming each defect empirically. Moves to tier-2a: GPU canary assertions and CUDA behavior verification remain.
Fleet monitoring operational with continuous heartbeat. ns-r7: 3 locked items closed, 17 test failures resolved to passes. Hub M2: 41-pass baseline established, F1/F4-F9/F11/F13 defects closed in plan.
Final P0 (checkpoint prefetch tracking via consumed_loader_state) validated by passing test suite. CPU-side work complete. GPU-side canary run pending with capped params (SAVE_EVERY=250, MAX_STEPS=300).
Independent sol-reverify-d26 session confirmed all SOL-PLAN-REVIEW P0 findings closed via direct code inspection. P0-1 checkpoint prefetch race covered by new test parametrizations in base_train.py. Tier-2a smoke test phase cleared for launch at SAVE_EVERY=250, MAX_STEPS=300.
Nine commits across checkpoint consumed-cursor fix, launcher hardening (5 defects), and training guards. RED/GREEN verification confirmed per defect. Remediation phase officially closed.
Cache validation passed, owner actions documented in NEEDS-OWNER file, systemd monitoring timer installed. Launch gated on Hyperbolic account email verification and payment method.
Bake script and CPU-only traversal simulator gating specified. GPT-Pro brainstorming on cloud run efficiency optimization from contemporary literature queued.
Blind Fable follow-up review found trust_remote_code RCE vector and Windows username leak missed by initial pass — both fixed. SECURITY.md created documenting sandbox design boundary. Git history rewrite still pending.
8 commits correcting talkie-conversion and post-1930 fracture claims. Affective divergence (providence/duty vs. therapeutic) and era-based Family F clustering confirmed robust. Phase 2 direction crystallized: pre-1914 vs. modern characterology.
Multi-agent review (Opus, GPT Max, GPT Council, GPT Pro, Opus 4.7) of nanochat training results. Key output: cost-tiered skill selection framework distinguishing GPT Max (13×, high-stakes disagreement) from codex-council (5×, initial lookups).
Orphaned tab memory leak and missing transport retry logic identified. Stepped timeout architecture designed (30–120 min). Fixes specified, pending implementation.
Three-layer completion detection with timeout polling implemented. Architecture validated clean by code review. Blocking issues: page leak from orphaned Chromium tabs, no retry on transport failure.
MCP server enables GPT-5.4 Pro via browser automation. Code review identified page leak (Chromium tabs never closed) and missing retry logic for dropped responses. Training data migrated from Windows NTFS to native Linux ext4.