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Nestleshuffle/gemma-4-26B-A4B-it-uncensored-heretic-mlx-8Bit

Nestleshuffle Gemma 25B MoE multimodal second-order
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Response includes
  • classification m3
  • files 14
  • benchmarks 11 entries
  • hub_downloads_all_time 2,534
  • author_summary 3 models
  • readme_text full
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Abliteration classifier · v1.0.0
M3
Primary method

Layer-wise ablation

Applied on top of direct removal inherited from the base model.
Confidence
HIGH
Inherited from base model
Why this label 2 signals
Producer identity confirmed by naming conventions, tags or the model card. This label is very unlikely to change.
  • 'heretic' in model name (Heretic-produced)
  • Heretic uses layer-wise optimization (M3) with underlying direction removal (M1)
Refusal direction extracted via
Extraction technique

Difference-of-means

Confidence
HIGH
Why we say so
name contains 'heretic'; Heretic default extraction is difference-of-means (Arditi 2024)
Downloads · lifetime
3K
260 last 30d - stable
Likes
2
Model age
4mo ago
created 2026-05-28
Downloads over time
Now2.6K→from753↑251%
6581.4K2.1K2.8K753 on Jun 102.6K on Oct 11JunJulAugSepOct
Jun 10 → Oct 11 · 57 snapshots · spans 123 days

Benchmarks

Benchmark Score Source
Entertainment 2.8 UGI
Hazardous 3.5 UGI
Natural Intelligence 34.12 UGI
Political lean -22.2% UGI
Sensitive-Info 27.29 UGI
SocPol 2 UGI
UGI 49.03 UGI
Willingness (10) 9.2 UGI
W10-Adherence 8.5 UGI
W10-Direct 10 UGI
Writing 42.09 UGI

Genealogy 0 direct forks

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Metadata

License
apache-2.0
Tags
transformers safetensors gemma4 image-text-to-text heretic uncensored decensored abliterated ara mlx mlx-my-repo conversational

Related

Total size
25.0 GB
Files
14
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-05-28 01:41

Files by quantization

Auxiliary files 14 files 25.0 GB
model-00004-of-00006.safetensors 4.85 GB d9a171c0 download
model-00005-of-00006.safetensors 4.85 GB 039d148c download
model-00003-of-00006.safetensors 4.85 GB 2102a3aa download
model-00002-of-00006.safetensors 4.85 GB 63952e1f download
model-00001-of-00006.safetensors 4.83 GB edbdc3fd download
model-00006-of-00006.safetensors 771 MB 5ce4b1fb download
tokenizer.json 30.7 MB cc8d3a0c download
model.safetensors.index.json 136 KB eb431e38 download
chat_template.jinja 16.9 KB 7fa57f97 download
config.json 10.2 KB 28e7af86 download
tokenizer_config.json 2.76 KB f21f2a4f download
.gitattributes 1.53 KB 52373fe2 download
README.md 1.19 KB e1d3ec0f download
generation_config.json 217 B ed42ae71 download

README current version from Hugging Face


library_name: transformers
license: apache-2.0
license_link: https://ai.google.dev/gemma/docs/gemma_4_license
pipeline_tag: image-text-to-text
tags:

  • heretic
  • uncensored
  • decensored
  • abliterated
  • ara
  • mlx
  • mlx-my-repo
    base_model: llmfan46/gemma-4-26B-A4B-it-uncensored-heretic

Nestleshuffle/gemma-4-26B-A4B-it-uncensored-heretic-mlx-8Bit

The Model Nestleshuffle/gemma-4-26B-A4B-it-uncensored-heretic-mlx-8Bit was converted to MLX format from llmfan46/gemma-4-26B-A4B-it-uncensored-heretic using mlx-lm version 0.31.2.

Use with mlx

pip install mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("Nestleshuffle/gemma-4-26B-A4B-it-uncensored-heretic-mlx-8Bit")

prompt="hello"

if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, tokenize=False, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

README history 1 version

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

  1. 2026-05-28Upload folder using huggingface_hubddea4341.2 KB
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