[!Note] The included imatrix file was generated from DJLougen/Acta-Synthetic. It is included for reproducibility and for users who want to regenerate adjacent quantizations.

Which sent me down a shallow rabbit hole to figure just how to do that. These are the fruit of that labor.

Theses were all converted from the full SABER Hugging Face checkpoint. I only intend to fill the gaps @DJLougen left, but I may come back and do all the quants off of the full checkpoint.

Enjoy!

Ornstein-Hermes-3.6-27B SABER GGUF

GGUF quantizations of GestaltLabs/Ornstein-Hermes-3.6-27b-SABER, a SABER-edited version of GestaltLabs/Ornstein-Hermes-3.6-27b.

SABER is a controlled refusal-shaping workflow. The release target is to reduce broad over-refusal while preserving ordinary model behavior and visible boundaries for severe criminal, coercive, or interpersonal-harm requests. The selected checkpoint was chosen as a Pareto point over refusal rate and behavioral drift.

Source Checkpoint

field	value
Source repo	`GestaltLabs/Ornstein-Hermes-3.6-27b-SABER`
Base model	`GestaltLabs/Ornstein-Hermes-3.6-27b`
SABER run	`ornstein_hermes36_27b_svd_a850_g25_retry_biggpu`
Expanded refusal eval	`1 / 349` refusals
Refusal rate	`0.29%`
KLD mean	`11.2216`
Base-vs-base KLD mean	`11.2206`
KLD delta over base-vs-base	`+0.0010`
KLD prompts	`149`
Tokens scored for KLD	`3,347`

The one retained refusal in the expanded evaluation was an illegal-drug-sales request. This is an observed result on the current evaluation set, not a universal guarantee about future behavior.

Quantization Files

file	quant	size	notes
`Ornstein-Hermes-3.6-27b-SABER-IQ4_XS.gguf`	`IQ4_XS`	`15G`	Compact imatrix-assisted 4-bit option.
`Ornstein-Hermes-3.6-27b-SABER-IQ2_M.gguf`	`IQ2_M`	`9G`	Smallest emergency 2-bit option; expect the most quality loss.
`Ornstein-Hermes-3.6-27b-SABER-Q3_K_M.gguf`	`Q3_K_M`	`13G`	Smallest file in this suite; expect more quality loss.
`Ornstein-Hermes-3.6-27b-SABER-Q4_K_M.gguf`	`Q4_K_M`	`16G`	General-purpose recommended starting point.
`Ornstein-Hermes-3.6-27b-SABER-Q5_K_M.gguf`	`Q5_K_M`	`18G`	Balanced high-quality option.
`Ornstein-Hermes-3.6-27b-SABER-Q6_K.gguf`	`Q6_K`	`21G`	Strong quality/size option for high-memory local inference.
`Ornstein-Hermes-3.6-27b-SABER-Q8_0.gguf`	`Q8_0`	`27G`	Highest quality quant in this suite; largest runtime file.

The included imatrix file was generated from DJLougen/Acta-Synthetic. It is included for reproducibility and for users who want to regenerate adjacent quantizations.

Recommended File

Start with for normal desktop use. Use or if you have enough VRAM/RAM and want a higher-quality local run. Use when file size matters more. is mainly for high-memory systems or as a near-lossless GGUF reference.

llama.cpp Compatibility

These files were produced with llama.cpp commit from a BF16 GGUF conversion of the SABER checkpoint. The model uses the GGUF architecture path in current llama.cpp.

Example:

For chat-style use, prefer a frontend or wrapper that applies the tokenizer chat template from the GGUF metadata.

Conversion and Quantization Notes

The Q8_0 GGUF was converted from the full SABER Hugging Face checkpoint. The lower-bit recovery quants were generated from the published Q8_0 GGUF with --allow-requantize and the included Acta-Synthetic imatrix so the missing files could be restored quickly. Importance-matrix calibration used Acta-Synthetic conversational text.

Method Summary

SABER edits refusal behavior through activation/weight-space refusal directions. For this checkpoint, the run used SVD extraction, multi-layer candidate selection, iterative ablation, and KLD-based drift measurement.

Run configuration:

Selected layers:

Total directions ablated: .

Attribution and Related Work

This release builds on the refusal-direction and abliteration research lineage. Relevant prior work and inspirations include:

Andy Arditi, Oscar Obeso, Aaquib Syed, Daniel Paleka, Nina Panickssery, Wes Gurnee, and Neel Nanda, Refusal in Language Models Is Mediated by a Single Direction, 2024.
Maxime Labonne, Uncensor any LLM with abliteration, 2024.
FailSpy, abliterator, and associated abliterated model releases.
Jim Lai (), Projected Abliteration, 2025, and Norm-Preserving Biprojected Abliteration, 2025.
Philipp Emanuel Weidmann, Heretic, 2025-2026.
Pliny the Prompter / OBLITERATUS, Hugging Face Space and OBLITERATUS releases.
Jiunsong, SuperGemma4 E4B Abliterated, and related SuperGemma releases.
Jiachen Zhao, Jing Huang, Zhengxuan Wu, David Bau, and Weiyan Shi, LLMs Encode Harmfulness and Refusal Separately, 2025.

SABER's contribution in this release is the controlled-refusal-shaping workflow: multi-candidate refusal extraction, separability/entanglement-aware ranking, differential ablation strength, and explicit Pareto selection over refusal behavior and KLD drift.

Limitations

Results are specific to the current evaluation set, prompts, and generation settings.
The KLD value should be interpreted relative to the base-vs-base control, not as an absolute standalone score.
Quantization changes numerical behavior; validate the specific GGUF file you deploy.
The model inherits constraints, limitations, and licensing considerations from the base model.
This is a model-editing research artifact with dual-use implications.

gkraker04/Ornstein-Hermes-3.6-27B-SABER

Adjacent Quantizations