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SaturnHeaven/Gemma-4-Queen-31B-it-uncensored-heretic-lora-GGUF overview

Gemma 4 Queen 31B it — Heretic LoRA r64, GGUF Rank 64 abliteration LoRA adapter in GGUF format for aifeifei798/Gemma 4 Queen 31B it https://huggingface.co/aife…

gguflorahereticabliterationuncensoreddecensoredgemma4roleplaybase_model:aifeifei798/Gemma-4-Queen-31B-itbase_model:adapter:aifeifei798/Gemma-4-Queen-31B-itlicense:apache-2.0region:us

Runs locally from ~29.1 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Repository Files & Downloads

2 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
queen_heretic_r64_f16.ggufGGUFF1654.7 MBDownload
queen_heretic_r64_q8.ggufGGUFQ829.1 MBDownload

Model Details

Model IDSaturnHeaven/Gemma-4-Queen-31B-it-uncensored-heretic-lora-GGUF
AuthorSaturnHeaven
Pipeline—
Licenseapache-2.0
Base modelaifeifei798/Gemma-4-Queen-31B-it
Last modified2026-10-06T14:28:41.000Z

Model README

---

base_model: aifeifei798/Gemma-4-Queen-31B-it

base_model_relation: adapter

license: apache-2.0

tags:

  • gguf
  • lora
  • heretic
  • abliteration
  • uncensored
  • decensored
  • gemma4
  • roleplay

---

Gemma-4-Queen-31B-it — Heretic LoRA (r64, GGUF)

Rank-64 abliteration LoRA adapter in GGUF format for

aifeifei798/Gemma-4-Queen-31B-it.

It is a low-rank approximation of the abliteration delta between the base and

llmfan46/Gemma-4-Queen-31B-it-uncensored-heretic,

which was produced with Heretic v1.2.0 using

the Arbitrary-Rank Ablation (ARA) method on attn.o_proj. It was not produced

by running Heretic/ARA directly.

It is meant for roleplay and creative writing: when a scene calls for darker, more

violent or more explicit description, the base RP fine-tune tends to refuse, add

disclaimers or step out of character. With the adapter it stays in the scene.

Because it is a separate adapter, you can switch it on only when needed and

adjust its strength (see Usage).

Apply it to any GGUF quant of the base — the base weights are never modified, and

omitting the adapter restores the base exactly. This is a rank-64 approximation,

not a bit-identical reconstruction of the source model.

> Note: refusal behavior is suppressed and outputs are not filtered.

Files

| File | Quant | Size |

|---|---|---|

| queen_heretic_r64_f16.gguf | F16 | 57.3 MB |

| queen_heretic_r64_q8.gguf | Q8_0 | 30.5 MB |

Reconstruction fidelity (r64)

The adapter is the rank-64 SVD truncation of the abliteration delta

ΔW = W_heretic − W_original on attn.o_proj, layers 26–55 (30 layers).

Values are computed from the dequantized Q8 adapter weights (F16 is equivalent here):

  • ΔW_l = per-layer delta, float32; ΔŴ_l = B_l·A_l = adapter reconstruction.
  • mean energy = arithmetic mean over the 30 layers of Σ_{i≤64} σ_i² / Σ_i σ_i²

(σ_i = singular values of ΔW_l).

  • pooled rel-Fro = ‖res‖_F / ‖ΔW‖_F with all layers stacked (energy-weighted).
  • max-abs / RMS are absolute errors in ΔW (weight units), not normalized by W.

| Metric | Value |

|---|---|

| Total parameters | 28.7M |

| ΔW energy preserved (mean over 30 layers) | 97.95% |

| ΔW energy preserved (per-layer range) | 94.1–99.8% |

| Pooled relative Frobenius residual | 10.68% |

| Reconstruction max-abs error (ΔW units) | 3.42e-3 |

| Reconstruction RMS error (ΔW units) | 6.10e-5 |

The mean-energy (97.95%) and pooled-residual (10.68%) figures differ because the

former is a per-layer arithmetic mean while the latter is energy-weighted across

layers — layers with larger ‖ΔW‖ are preserved better. The delta is dominated by

one direction: the leading singular direction captures a mean 95.46% of ΔW energy

over the 30 layers (per-layer range 91.0–98.6%).

Usage (llama.cpp)

llama-server \
    -m Gemma-4-Queen-31B-it-Q4_K_M.gguf \
    --lora queen_heretic_r64_q8.gguf
  • Use queen_heretic_r64_f16.gguf for higher precision.
  • Strength: r=64 and alpha=64, so the default scale is 1.0. Use

--lora-scaled queen_heretic_r64_q8.gguf:0.5 (instead of --lora) to weaken it.

On one test prompt (fixed seed) the scale acted as a monotonic strength knob: 0.25 still mostly

refused, 0.5 answered with heavy disclaimers, 0.75 with a brief warning, and 1.0

answered fully.

  • No special sampling parameters are required.

Abliteration parameters

start_layer_index=26, end_layer_index=56 (exclusive → layers 26–55, 30 layers),

preserve_good_behavior_weight=0.8555, steer_bad_behavior_weight=0.0005,

overcorrect_relative_weight=0.9911, neighbor_count=15, target component attn.o_proj.

KL divergence 0.0707 and refusals 12/100 vs 99/100 were measured on the source full

model (see its card), not re-measured for this adapter. Spot-checked: prompts that

the base refuses are answered with the adapter applied; no systematic refusal

benchmark was run on the adapter.

Credits

License

Released under Apache-2.0 (see LICENSE), the same license as

aifeifei798/Gemma-4-Queen-31B-it,

llmfan46/Gemma-4-Queen-31B-it-uncensored-heretic

and google/gemma-4-31B-it. This

adapter contains modified weights: a rank-64 SVD approximation of the difference

between the heretic and base attn.o_proj weights.

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