Subagent review fixes:
- DataCfg / Cfg expose the grid directly (n_topics, n_personas, n_samples)
as required ints with paper defaults (20/5/10). Drops `n_pairs` and the
silent round() that made the count fuzzy. Drops `Optional[int]` smoke
overrides — smoke just sets 2/1/2 = 4 pairs.
- Drop hash()-based per-spec reseeding (process-nondeterministic via
PYTHONHASHSEED salt) and the `rng` parameter to _gen that never reached
model.generate. One torch.manual_seed at start; spec order seeded by rng.
- Delete _judge_filter stub + cfg.judge flag (dead code, paper §3 GPT-4.1-mini
filter not implemented yet — TODO comment instead).
- replicate._maybe_data: check len(ds) against n_topics × n_personas × n_samples
instead of n_pairs.
- justfile: drop --n-pairs 1000.
- Updated the fork plan with detailed phases and objectives for small model adaptation and evaluation.
- Added a new guided-CoT evaluation script to assess model coherence under steering.
- Introduced demo functionality to showcase adapter coherence and guided-CoT performance.
- Modified training configuration to include layer fraction targeting for LoRA.
- Improved evaluation outputs for clarity and added validation checks.
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