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jwest33/gemma-3-4b-it-null-space-abliterated

jwest33 Gemma 4.3B multimodal
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Response includes
  • classification m1
  • files 19
  • benchmarks 16 entries
  • hub_downloads_all_time 147
  • author_summary 20 models
  • readme_text full
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Abliteration classifier · v1.0.0
M1
Primary method

Direct removal

No other method signals detected in this model.
Confidence
MEDIUM
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=0 (base model)
  • no specific method indicators - defaulting to M1 (most common)
Refusal direction extracted via
Extraction technique

Difference-of-means

Confidence
MEDIUM
Why we say so
primary_method=M1; difference-of-means is the reference extraction for M1/M3 (Arditi 2024)
Downloads · lifetime
147
18 last 30d - stable
Likes
0
Descendants
4
in 4 direct forks
Model age
9mo ago
created 2026-01-04
Downloads over time
Now155→from10↑1,450%
35811417010 on Jan 7155 on Oct 11155 on Oct 9JanMarMayJulSep
Jan 7 → Oct 11 · 79 snapshots · spans 277 days

Benchmarks

Benchmark Score Source
Entertainment 1.3 UGI
Hazardous 0 UGI
Natural Intelligence 11.49 UGI
Political lean -17.1% UGI
Sensitive-Info 5.57 UGI
SocPol 0.1 UGI
UGI 31.21 UGI
Willingness (10) 8.2 UGI
W10-Adherence 7.5 UGI
W10-Direct 9 UGI
Writing 20.79 UGI
Portrait before abliteration
Benchmarks of the base model as it stood before the refusal-removal operation. Compare with the numbers above to see what the operation cost.
Benchmark Score Source
Arena-Battles 4321 LM-Arena
LM Arena Elo 1293.3101140666447 LM-Arena
Arena-Elo-Lower 1284.2314692781533 LM-Arena
Arena-Elo-Upper 1302.388758855136 LM-Arena
Arena-Rank 77 LM-Arena

Genealogy 4 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 · 342 downloads combined

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

Metadata

License
gemma
Tags
transformers safetensors gemma3 image-text-to-text gemma gemma-3 abliterated uncensored conversational arxiv:2410.02355 arxiv:2406.11717 arxiv:2310.01405

Related

Total size
8.01 GB
Files
19
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-01-06 12:19

Files by quantization

Auxiliary files 19 files 8.05 GB
model-00001-of-00002.safetensors 4.62 GB 0477919e download
model-00002-of-00002.safetensors 3.39 GB 20fbeae6 download
null_space_projectors.pt 4.03 MB f04802a6 download
refusal_directions.pt 96.4 KB c5da9049 download
tokenizer.json 31.8 MB 3ff2eb2f download
tokenizer.model 4.47 MB 1299c11d download
tokenizer_config.json 1.15 MB 2cfe89ab download
model.safetensors.index.json 89.3 KB 05e6aa91 download
README.md 2.97 KB b33eaf20 download
config.json 2.56 KB 5dc4c7b7 download
chat_template.json 1.58 KB 31057a43 download
chat_template.jinja 1.54 KB c5f13654 download
.gitattributes 1.53 KB 52373fe2 download
special_tokens_map.json 695 B 6728103d download
preprocessor_config.json 599 B da332e16 download
abliteration_config.json 381 B 24770e3c download
generation_config.json 223 B 61e3cf83 download
processor_config.json 74.0 B bcc0e8fd download
added_tokens.json 38.0 B f9f1f4f5 download

README current version from Hugging Face


license: gemma
library_name: transformers
base_model: google/gemma-3-4b-it
tags:

  • gemma
  • gemma-3
  • abliterated
  • uncensored
  • safetensors

Gemma 3 4B Instruct - Null-Space Abliterated

google/gemma-3-4b-it with refusal behavior removed via orthogonal projection. Uses null-space constraints and adaptive layer weighting to preserve model capabilities.

Note: This model will produce uncensored outputs. Use responsibly.

GGUF quantizations available at: jwest33/gemma-3-4b-it-null-space-abliterated-GGUF

Abliteration Techniques Used

  • Winsorization: Clips outlier activations at the 99th percentile for cleaner refusal direction estimation (recommended for Gemma models)
  • Null-Space Projection: Preserves model capabilities by constraining weight updates to the null space of preservation activations
    • Preservation Prompts: Dynamically generated using Gemma Scope 2 complete SAE circuit analysis to ensure complete coverage of shared features activated by harmful prompts, without overextending into unrelated capability space
  • Adaptive Weighting: Applies Gaussian-weighted per-layer ablation strength, focusing on middle-to-later layers where refusal behavior concentrates
  • Norm Preservation: Maintains original Frobenius norms of weight matrices after projection
Parameter Value
Harmful Prompts 5000
Harmless Prompts 637
Winsorization 99.5th percentile
Null-Space Constraints rank ratio: 0.90
Directional Multiplier 1.03
SAE Targeted Coverage 1.00

Credits

Toolkit Used

github.com/jwest33/abliterator

License

This model inherits the Gemma license from the base model. Please review and comply with Google's usage terms.

Disclaimer

This model is provided for research and educational purposes. The creators are not responsible for any misuse. Users are solely responsible for ensuring their use complies with applicable laws and ethical standards.

README history 2 versions

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

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