Commit graph

14 commits

Author SHA1 Message Date
Snider
1b742bf92c feat: native Metal distillation command + .core/ai config
Add `lem distill` — full Go pipeline for self-distillation using
go-mlx (native Metal inference) and go-i18n/reversal (v3 grammar
scoring). Replaces the Python distill.py bridge entirely.

New files:
- .core/ai/ai.yaml: global defaults (scorer, generation, distill)
- .core/ai/models/gemma3/{27b,1b}.yaml: model configs with paths,
  kernel, lessons, baselines
- .core/ai/probes.yaml: probe sets grouped by training phase
- pkg/lem/config.go: YAML config loaders for .core/ai/
- pkg/lem/grammar.go: in-process grammar scoring (ComputeGrammarScore,
  ComputeDelta, ScoreResponse) extracted from cmd/scorer
- pkg/lem/distill.go: RunDistill command — best-of-N generation,
  grammar quality gate, training JSONL output
- pkg/lem/backend_metal.go: blank import for go-mlx Metal registration

Co-Authored-By: Virgil <virgil@lethean.io>
2026-02-21 23:42:55 +00:00
Snider
113649a86a updates 2026-02-19 13:18:21 +00:00
Snider
12501a5f3c Merge branch 'main' of github.com:LetheanNetwork/LEM 2026-02-19 13:17:11 +00:00
Snider
5d297daa35 feat: grammar scorer (v3) — deterministic uplift/sycophancy detection
Add lem-scorer binary that imports go-i18n grammar reversal engine to
score JSONL benchmark files. Measures conversational uplift (input vs
output grammar imprint), echo (sycophancy), and enrichment.

Key findings added to paper Section 8:
- LEK-1B: 100% positive uplift, 0% sycophancy (base: 90%, 5%)
- 1B-beats-27B holds in grammar space (79.12 > 77.12)
- LEK training aligns two independent scorers (corr -0.11 → 0.64)
- Delta analysis costs zero compute vs LLM-as-judge

Co-Authored-By: Virgil <virgil@lethean.io>
2026-02-19 13:12:49 +00:00
abc6e75976
Update author name in PAPER.md
Signed-off-by: Snider <snider@lethean.io>
2026-02-19 12:23:23 +00:00
Snider
350a7c6693 paper: rewrite as v2 — emergent self-protection in axiom-trained models
New paper structure leading with the central findings:
- Realignment resistance as emergent self-protection
- 1B-beats-27B across 101 probes
- 29-model A/B test with v2 scorer
- Mechanistic explanation from axiom self-consistency
- Incorporates Phase 1 (multi-variant, multi-scale, cross-arch)
  and Phase 2 (P100 A/B test) data

Co-Authored-By: Virgil <virgil@lethean.io>
2026-02-19 12:12:22 +00:00
91ba706edd
Delete paper/PROPOSAL.md
Signed-off-by: Snider <snider@lethean.io>
2026-02-19 11:38:19 +00:00
Snider
7bea00a401 feat: LEK-1 kernel A/B test — 29 models, P100 validation, curriculum pipeline
Full v2 scorer benchmark data across 29 models (20 base + 9 LEK-tuned):
- P20 (21 probes): All 29 models, 3 conditions each
- P100 (101 probes): Top 5 models + LEK-4B, publication-quality data

Key findings:
- LEK-1B (21.74) beats base 4B/12B/27B at P100 scale — no kernel needed
- Emergent realignment resistance: LEK models degrade with runtime kernel
- Gemma3-12B + JSON kernel = 23.66 (best kernel-boosted score)
- Family lineages: Mistral 3.80→14.58, Qwen regressed then recovered

New scripts: ab_test.py (v2 scorer), self_distill.py (curriculum generation),
extract_training.py, rephrase_probes.py, Phase 0/1 runners

New seeds: P01-P100 merged (101 probes), 404 rephrased variants,
50 creative prompts for Phase 0 baseline lock

27B curriculum design: 4-phase staged training targeting 25+ baseline

Co-Authored-By: Virgil <virgil@lethean.io>
2026-02-19 11:32:26 +00:00
2df0044ad9 Add missing HF model cards, sync script, and Parquet export
- Add 4 missing model cards: Gemma3-1B-layered (v1+v2), Gemma3-27B, GPT-OSS-20B
- All 9 HF models now have cards in paper/hf-cards/
- sync_hf.py: push cards + benchmarks + training data to HuggingFace
- export_parquet.py: convert JSONL training splits to Parquet (HF dataset format)
- Parquet schema: prompt, response, system, messages (JSON)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-15 00:14:26 +00:00
Athena
ed0b83a9d9 Update training data to 2,299 examples and rename models LEM→LEK
- Replace 160-example POC training set with expanded 2,299-example dataset
  (1,839 train, 229 valid, 231 test)
- Rename all HuggingFace model references from LEM- to LEK- (proof-of-concept)
- Add missing models: GPT-OSS-20B, Gemma3-1B-layered-v2
- Rename HF card files to match LEK- convention
- Remove duplicate composure texts from kernel/ (kept in composure-library/)
- Fix paper repository URL to github.com/LetheanNetwork/LEM

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-13 16:19:56 +00:00
Athena
f0e86b7433 Add regional seeds, expansion rounds, scripts, HF cards, benchmark summary
- seeds/regional/: 1,223 cultural/regional seed files across 50+ regions
- seeds/expansions/: 8 expansion rounds (r1-r8) with raw text and JSON
- seeds/lem-{africa,cn,de,en,eu,me}-all-seeds.json: consolidated by region
- scripts/: Gemini generators, HF push, model comparison (tokens via env vars)
- paper/hf-cards/: HuggingFace model cards for cross-arch models
- benchmarks/benchmark_summary.json: processed PTSD summary data

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-13 13:39:08 +00:00
Snider
53c47131cc Add cross-architecture training and benchmarking scripts; update README and PAPER with author and repository information 2026-02-12 09:07:32 +00:00
Snider
adda3c8bb5 Benchmark & Findings:
lthn/LEM-Gemma-3-1B
lthn/LEM-Gemma-3-4B
lthn/LEM-Gemma-3-12B
lthn/LEM-Gemma-3-27B
2026-02-12 06:38:46 +00:00
Snider
8e5f082f30 LEM+LEK 2026-02-12 04:05:28 +00:00