Skyfall-31B-v4.1-Heretic-v1.2-GGUF

grayarea/Skyfall-31B-v4.1-Heretic-v1.2-GGUF

Skyfall-31B-v4.1-Heretic-v1.2-GGUF is a machine learning model from grayarea. Use it for the machine learning task on the model card, and read the license before you ship it in a product.

This is a decensored version of Skyfall-31B-v4.1, made using Heretic v1.2.0 focusing on zero refusals with low KL divergence.

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Repo size

115 GB

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Hugging Face

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.gguf115 GB · 100%

At a glance

Access: Public
Created: Mar 8, 2026
Updated: Mar 8, 2026
SHA: 6370c82c

Base models

grayarea/Skyfall-31B-v4.1-Heretic-v1.2

Model card

From the Hugging Face model README

This is a decensored version of Skyfall-31B-v4.1, made using Heretic v1.2.0 focusing on zero refusals with low KL divergence.

KL Divergence

Metric	This Model	Original Model
KL divergence	0.0053	0 (by definition)
Refusals	0/108	73/108

Abliteration parameters

Zero refusals with KL divergence of 0.0053
Custom heretic training dataset
Model targetted heretic configuration
Abliterated with MPOA enabled (Magnitude-Preserving Orthogonal Ablation)
Full row renormalization
Winsorization Quantile 0.997

Relative Perplexity

Quant	Filename	PPL ± Error
Q8_0	TheDrummer_Skyfall-31B-v4.1-Q8_0.gguf (original baseline)	5.1950 +/- 0.03186
Q8_0	Skyfall-31B-v4.1-Heretic-v1.2-Q8_0.gguf	5.1975 +/- 0.03188
Q4_K_M	Skyfall-31B-v4.1-Heretic-v1.2-Q4_K_M.gguf	5.2681 +/- 0.03232

Benchmark Comparison

Benchmark	TheDrummer_Skyfall-31B-v4.1-Q8_0.gguf	TheDrummer_Skyfall-31B-v4.1-Q4_K_M.gguf	Skyfall-31B-v4.1-Heretic-v1.2-Q4_K_M.gguf
Perplexity (Wikitext-2)	5.1950	5.3158	5.2681
HellaSwag	83.75%	83.00%	81.50%
Winogrande	77.27%	76.87%	77.03%
ARC-Challenge	54.52%	55.85%	54.85%
MMLU	43.99%	44.32%	43.73%

*Note: MMLU benchmark has moral_scenarios, moral_disputes, business_ethics, professional_law and jurisprudence subjects removed. *

Created: Mar 8, 2026
Updated: Mar 8, 2026