Gemma4-Gutenberg-31B
google/gemma-4-31B-it finetuned for literary, novelistic prose — a Gemma 4 entry in the Gutenberg series.
This pushes the (already strong) base toward a literary-fiction register: story and interiority over static description, controlled pacing over relentless adjective-stacking, and an active dispreference for "AI slop" phrasing.
Method
ORPO (Odds Ratio Preference Optimization) on the full
schneewolflabs/Athanorlite-DPO
(14,816 preference pairs) — a superset of the Gutenberg "Encore" recipe that
bundles jondurbin/gutenberg-dpo-v0.1, nbeerbower/gutenberg2-dpo,
gutenberg-moderne-dpo, human-writing-dpo, synthetic-fiction-dpo,
Arkhaios-DPO, Purpura-DPO, Schule-DPO,
sam-paech/gutenberg3, plus truthy / physical-reasoning / theory-of-mind
balance sets.
| Method | ORPO, β = 0.1 |
| Adapter | LoRA r=64 (text decoder only), merged to full |
| LR | 5e-5, cosine, 0.05 warmup |
| Epochs | 1 |
| Effective batch | 32 |
| Max length | 2048 |
| Optimizer | paged_adamw_8bit, bf16, grad-checkpointing |
| Hardware | 1× NVIDIA GB10 (DGX Spark, 128 GB unified) |
| Trainer | Merlina (grimoire ORPO) |
Training trajectory (clean convergence over ~3.5 days, 454 steps):
| start | end | |
|---|---|---|
| eval/loss | 2.4445 | 2.2052 |
| reward_accuracy | 0.175 | 0.9125 |
| reward_margin | −0.076 | +0.455 |
The reward_accuracy arc (0.18 → 0.50 → 0.91) reflects the model learning to
prefer the literary chosen text while actively suppressing the rejected
slop — the intended Gutenberg dynamic.
Notes
- Gemma 4 31B is a unified multimodal model; the vision/audio towers are left frozen and intact, so this remains a drop-in replacement for the base. Only the text decoder was tuned.
- This is a refinement of an already-capable writer, not a rescue — expect a consistent literary lean rather than a night-and-day transformation.
License
Apache-2.0 (matching the Gemma 4 base). Constituent training datasets carry their own licenses (see the Athanorlite-DPO card).