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gemma-2-9b-it-abliterated

gemma-2-9b-it-abliterated is a refusal-ablated variant of IlyaGusev/gemma-2-9b-it-abliterated, published on Hugging Face by IlyaGusev. It is 9B parameters, single consumer GPU class and gemma licence. It is distributed across 32 repositories in Transformers, GGUF, EXL2 and AWQ formats, totalling 14.3K downloads.

Abliteration (directional ablation)9BGemma4B – 10B↓ 14,300♥ 57

Specification

Model name
gemma-2-9b-it-abliterated
Publisher
IlyaGusev
Parameters
9B
VRAM required
~6.2 GB at Q4_K_M, 4k context (estimated) — runs on 8 GB cards
Hardware class
4B – 10B — single consumer GPU
Licence
gemma
Task
Text generation
Context window
Not documented
Ablation scope
Not stated by the publisher
Formats available
Transformers, GGUF, EXL2, AWQ, MLX, GGUF (imatrix)
First indexed
8 Jul 2024
Last updated
29 Aug 2026

Ablation technique

How gemma-2-9b-it-abliterated was modified, and what that implies.

Abliteration (directional ablation)

The single residual-stream direction that mediates refusal is identified from harmful/harmless prompt pairs and projected out of the model weights.

Reported scope: Not stated by the publisher. Publishers frequently omit this, so verify behaviour empirically rather than assuming full coverage.

From the publisher’s model card

“Abliterated version of google/gemma-2-9b-it.”

Running it

Commands are templates — confirm the exact repository and quant file before use.

llama.cpp / GGUF
hf download bartowski/gemma-2-9b-it-abliterated-GGUF --local-dir ./gemma-2-9b-it-abliterated
llama-cli -m ./gemma-2-9b-it-abliterated/<file>.gguf -p "..."
Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer

repo = "IlyaGusev/gemma-2-9b-it-abliterated"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
    repo, torch_dtype="auto", device_map="auto"
)
vLLM
vllm serve IlyaGusev/gemma-2-9b-it-abliterated --trust-remote-code

Downloads and variants (31)

Every published repository of gemma-2-9b-it-abliterated, including quantised re-releases by other authors.

RepositoryFormatDownloads
bartowski/gemma-2-9b-it-abliterated-GGUFGGUF10.8K
IlyaGusev/gemma-2-9b-it-abliteratedsourceTransformers975
QuantFactory/gemma-2-9b-it-abliterated-GGUFGGUF627
tensorblock/gemma-2-9b-it-abliterated-GGUFGGUF532
BasedAGI/Gemma-2-9B-IT-Abliterated-i1-GGUFGGUF (imatrix)322
NINI26454/gemma-2-9b-it-Abliterated-GGUFGGUF153
Alex01837178373/gemma-2-9b-it-abliterated-Q4_K_M-GGUFGGUF96
pprp/gemma-2-9b-it-abliterated-Q4_K_M-GGUFGGUF89
jaahas/gemma-2-9b-it-abliterated-Q5_K_M-GGUFGGUF84
KnutJaegersberg/gemma-2-9b-it-abliterated-Q8_0-GGUFGGUF79
oskarraszkiewicz/gemma-2-9b-it-abliterated-mlx-2bitMLX76
matrixportalx/gemma-2-9b-it-abliterated-Q4_0-GGUFGGUF55
SkyNotion/gemma-2-9b-it-abliterated-Q4_K_M-GGUFGGUF47
Emilio407/gemma-2-9b-it-abliterated-GGUFGGUF45
Superoisesuki/gemma-2-9b-it-abliteratedTransformers31
Iambackup/gemma-2-9b-it-abliterated-GGUFGGUF31
solidrust/gemma-2-9b-it-abliterated-AWQAWQ29
Bluerosesbutterfly/gemma-2-9b-it-abliterated-Q5_K_MGGUF29
oskarraszkiewicz/gemma-2-9b-it-abliterated-mlx-8bitMLX27
flyfishstudio/gemma-2-9b-it-abliterated-Q4_0_4_8.ggufGGUF23
flyfishstudio/gemma-2-9b-it-abliterated-Q4_0_4_4.ggufGGUF23
oskarraszkiewicz/gemma-2-9b-it-abliterated-mlx-4bitMLX21
cgus/gemma-2-9b-it-abliterated-exl2EXL219
AISafety-Student/gemma-2-9b-it-abliteratedTransformers17
NeoChen1024/gemma-2-9b-it-abliterated-exl2-6.0bpw-h8EXL212
Phrongo/gemma-2-9b-it-abliterated-Q4_K_M-GGUFGGUF11
Bluerosesbutterfly/gemma-2-9b-it-abliterated-Q4_K_MGGUF10
soa11/gemma-2-9b-it-abliteratedTransformers6
TouchNight/gemma-2-9b-it-abliterated-4.0bpw-exl2EXL25
THRAXAPP/gemma-2-9b-it-abliterated-AWQAWQ5
Plus 1 further repository with fewer downloads, all counted in the totals above.

Security-team assessment

Derived from this model’s metadata and the publisher’s claims — not from benchmarks run by this site.

  • gemma-2-9b-it-abliterated will attempt offensive-security prompts that a hosted commercial model declines, which is what makes it usable for red-team corpus generation and for measuring what an unaligned model of this class produces.
  • Capability is inherited from IlyaGusev/gemma-2-9b-it-abliterated, not added by ablation — at 9B parameters, expect a small model’s reasoning and a high error rate on exploit detail.
  • The publisher does not state which layers were ablated, so assume nothing about refusal consistency — probe it directly.
  • Declared licence is gemma, but the terms that bind you are IlyaGusev/gemma-2-9b-it-abliterated’s — a re-release cannot grant more than its parent.

Handling: run it isolated, put moderation in front of it if anyone outside your team can reach it, and verify the weights before loading — these are third-party artifacts. Full handling and licence guidance.

Metadata for gemma-2-9b-it-abliterated is collected from the public Hugging Face API and the publisher’s model card. This site does not host weights, is not affiliated with IlyaGusev, and does not independently verify publisher claims. See responsible use.