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hongnono/gemma-4-31b-abliterated-mlx-8bit

hongnono Gemma 31B
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Response includes
  • classification m1
  • files 18
  • hub_downloads_all_time 724
  • author_summary 1 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
724
21 last 30d - cooling
Likes
0
Model age
5mo ago
created 2026-04-17
Downloads over time
Now732→from50↑1,364%
1627753980050 on Apr 15732 on Oct 12AprMayJunJulAugSepOct
Apr 15 → Oct 12 · 66 snapshots · spans 180 days

Metadata

License
other
Tags
mlx safetensors gemma4 abliteration uncensored experimental license:other 8-bit region:us
Total size
31.6 GB
Files
18
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-04-17 17:17

Files by quantization

Auxiliary files 18 files 31.6 GB
model-00005-of-00007.safetensors 5.00 GB 81488510 download
model-00004-of-00007.safetensors 4.98 GB 84e6fdcf download
model-00002-of-00007.safetensors 4.98 GB afcdb0a3 download
model-00006-of-00007.safetensors 4.92 GB d0b0b7f2 download
model-00003-of-00007.safetensors 4.92 GB 52d91cf7 download
model-00001-of-00007.safetensors 4.91 GB 69646aa7 download
model-00007-of-00007.safetensors 1.84 GB 9c32576c download
tokenizer.json 30.7 MB cc8d3a0c download
model.safetensors.index.json 201 KB cc261a77 download
chat_template.jinja 16.1 KB 98da08eb download
config.json 5.51 KB 072403e4 download
USAGE.md 5.19 KB 22ebe17a download
tokenizer_config.json 2.68 KB ed25f751 download
README.md 2.12 KB fbffaee4 download
.gitattributes 1.53 KB 52373fe2 download
abliteration_log.json 657 B 512fde99 download
processor_config.json 627 B 09dfe230 download
generation_config.json 208 B e605bb45 download

README current version from Hugging Face


tags:

  • mlx
  • abliteration
  • uncensored
  • experimental
    license: other

gemma-4-31b-it-8bit-abliterated

This model was created using the mlx-abliteration toolkit,
which is based on the FiditeNemini/mlx-abliteration project.

Base Model

Original model: /Users/hong/mlx-convert/models/gemma-4-31b-it-8bit (local path)

What is Abliteration?

Abliteration is a mechanistic interpretability technique that identifies and orthogonalizes the
"refusal direction" in a model's activation space, surgically removing refusal behavior without
full fine-tuning.

Abliteration Parameters

Parameter Value
Base model /Users/hong/mlx-convert/models/gemma-4-31b-it-8bit
Ablation method projection
Refusal vector policy per-layer
Refusal direction method difference
Ablation strength 2.0
Probed layers 5,11,17,23,29,35,41,47,53,59
PCA components (ablate-k) 1
Attention only True
Excluded modules none
Timestamp 2026-04-17T13:10:40 UTC

This model uses a Mixture-of-Experts (MoE) architecture. Abliteration targets only the attention projection weights (q/k/v/o_proj) to preserve expert routing quality.

⚠️ Disclaimer

This model is intended for research, experimentation, and testing purposes only.

  • This model may produce harmful, offensive, inappropriate, or otherwise objectionable content.
  • The abliteration process removes safety guardrails that were intentionally built into the original model.
  • Do not use this model in production systems, consumer-facing applications, or any context
    where harmful outputs could cause real-world harm.
  • The authors and contributors of this toolkit bear no responsibility for any misuse of this model
    or any harm caused by outputs generated by this model.
  • By using this model, you agree that you are solely responsible for ensuring its use complies
    with all applicable laws and ethical guidelines.

This model is shared purely for academic and technical exploration of model internals.

README history 1 version

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

  1. 2026-04-17Upload Gemma-4-31B abliterated MLX 8bit (cs2764 recipe, layers 5-59 attention...17e593b2.1 KB
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