← back to catalog · registered 2026-08-22 13:56

YanLabs/gemma-3-27b-it-abliterated-normpreserve-v1-GGUF

YanLabs Gemma 27B GGUF second-order 131K ctx
Your rig guess connected
? Why do I need an app?
Reading your rig…

This is a rough estimate. Install the free app - we'll show exact numbers.

Reading real hardware from your app right now. Numbers below are exact.

Below is the per-quantization compatibility for this model.

curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/YanLabs%2Fgemma-3-27b-it-abliterated-normpreserve-v1-GGUF"
Response includes
  • classification m8
  • files 4
  • benchmarks 11 entries
  • hub_downloads_all_time 1,616
  • author_summary 6 models
  • readme_text full
10 credits · hourly refresh · ~4 KB payload Get an API key →
Abliteration classifier · v1.0.0
M8
Primary method

Repackaging (quantization)

Applied on top of direct removal inherited from the base model.
Confidence
MEDIUM
Inherited from base model
Why this label 3 signals
Method inferred from partial signals - repository name, related files, or tag patterns. Producer identity not confirmed; label may sharpen or shift as we gather more evidence.
  • 'abliterated' in name/tags
  • is_gguf=1
  • assume M1 (base ablation) + M8 (GGUF quant) - default when producer unknown
Refusal direction extraction

No specific extraction method could be identified for this model. The producer either did not document it or used a proprietary pipeline.

What is a refusal direction? →
Downloads · lifetime
2K
132 last 30d - cooling
Likes
0
Model age
10mo ago
created 2025-12-03
Downloads over time
Now1.7K→from254↑561%
1837291.3K1.8K254 on Dec 10, 20251.7K on Oct 11Dec '25FebAprJunAugOct
Dec 10, 2025 → Oct 11 · 83 snapshots · spans 305 days

Benchmarks

Benchmark Score Source
Entertainment 1.8 UGI
Hazardous 2.4 UGI
Natural Intelligence 34.11 UGI
Political lean -12.4% UGI
Sensitive-Info 22.34 UGI
SocPol 2.7 UGI
UGI 36.56 UGI
Willingness (10) 6.5 UGI
W10-Adherence 5 UGI
W10-Direct 8 UGI
Writing 43.01 UGI

Genealogy 0 direct forks

Full fork graph →

This model's place in the market. Above: what it was derived from. Below: the tree of everything derived from it.

Variants by this author 2 formats · 159 downloads combined

The same weights this author released in different packaging. Pick the format that matches your runtime.

Metadata

License
gemma
Quantizations
F16 Q8_0
Tags
gguf text-generation base_model:YanLabs/gemma-3-27b-it-abliterated-normpreserve-v1 base_model:quantized:YanLabs/gemma-3-27b-it-abliterated-normpreserve-v1 license:gemma endpoints_compatible region:us conversational

Related

Total size
77.1 GB
Files
4
Quantizations
3
Registered
2026-08-22 13:56
Last updated on HF
2025-12-08 14:51

Files by quantization

F16 1 file 50.3 GB
gemma3-27B-it-abliterated-normpreserve-v1-F16.gguf 50.3 GB 5d4083b4 download
Q8_0 1 file 26.7 GB
gemma3-27B-it-abliterated-normpreserve-v1-Q8_0.gguf 26.7 GB f9c3be8f download
Auxiliary files 2 files 4.30 KB
README.md 2.65 KB 989c3f54 download
.gitattributes 1.65 KB e5843e21 download

README current version from Hugging Face


license: gemma
base_model:

  • YanLabs/gemma-3-27b-it-abliterated-normpreserve-v1
    pipeline_tag: text-generation

Gemma 3 27B Instruct - Norm-Preserving Abliterated-v1

This model is a variant of YanLabs/gemma3-27b-it-abliterated-normpreserve. The current model is less abliterated to preserve the capability of original gemma-3-27b-it model. For this v1 version, only the Q8_0 quantization is recommended. At quantization levels lower than Q8_0, refusals still occur, but with Q8_0 and F16 the model does not refuse.

This is an abliterated version of google/gemma-3-27b-it using the norm-preserving biprojected abliteration technique.

⚠️ Warning: Safety guardrails and refusal mechanisms have been removed through abliteration. This model may generate harmful content and is intended for mechanistic interpretability research only.

Model Details

Model Description

This model applies norm-preserving biprojected abliteration to remove refusal behaviors while preserving the model's original capabilities. The technique surgically removes "refusal directions" from the model's activation space without traditional fine-tuning.

  • Developed by: YanLabs
  • Model type: Causal Language Model (Transformer)
  • License: Gemma Terms of Use
  • Base model: google/gemma-3-27b-it

Model Sources

Uses

Intended Use

  • Research: Mechanistic interpretability studies
  • Analysis: Understanding LLM safety mechanisms
  • Development: Testing abliteration techniques

Out-of-Scope Use

  • ❌ Production deployments
  • ❌ User-facing applications
  • ❌ Generating harmful content for malicious purposes

Limitations

  • Abliteration does not guarantee complete removal of all refusals
  • May generate unsafe or harmful content
  • Model behavior may be unpredictable in edge cases
  • No explicit harm prevention mechanisms remain

Citation

If you use this model in your research, please cite:

@misc{gemma-3-27b-abliterated,
  author = {YanLabs},
  title = {Gemma 3 27B Instruct - Norm-Preserving Abliterated V1},
  year = {2025},
  publisher = {HuggingFace},
  howpublished = {\url{https://huggingface.co/YanLabs/gemma-3-27b-it-abliterated-normpreserve-v1}},
  note = {Abliterated using norm-preserving biprojected technique}
}

README history 4 versions

The author's README evolved over time. Click a version to see its content at that point.

  1. 2025-12-08Update README.mda923ddb2.6 KB
    Loading...
  2. 2025-12-08Update README.mde420ed02.6 KB
    Loading...
  3. 2025-12-03Update README.md59bc0732.6 KB
    Loading...
  4. 2025-12-03Create README.mdb4191092.6 KB
    Loading...
Catalog is the map. Apps are the tools.

Run models on your own machine, not in the cloud.

Every model page has an "Open in Abliteration" button that hands the model directly to the first-party desktop client, at the quantization your rig can actually run. No API keys, no subscription, no prompt leakage.

Open in Abliteration