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

Base Model: google/gemma-3-4b-it by Google
SAE Analysis: GemmaScope sparse autoencoders by Google DeepMind
Norm-Preserving Biprojected Abliteration — Jim Lai (grimjim) (2025)
AlphaEdit: Null-Space Constrained Knowledge Editing — Fang et al. (ICLR 2025)
Refusal in Language Models Is Mediated by a Single Direction — Arditi et al. (2024)
Representation Engineering — Zou et al. (2023)

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.

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.

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