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Aapolon/Qwen3.8-9B-Distill-Uncensored-Heretic-CyberStrike-GGUF

Aapolon 9B second-order
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  • classification m3
  • files 2
  • author_summary 1 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 · 30-day
0
Likes
0
Model age
6w ago
created 2026-09-03

Training datasets

1 of 1 in /datasets

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Genealogy 0 direct forks

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Metadata

License
apache-2.0
Tags
gguf cybersecurity offensive-security red-teaming penetration-testing qwen uncensored cyberstrike mitre-attack owasp en dataset:oyildirim/cyberstrike-sft-120k

Related

Total size
0 B
Files
2
Quantizations
1
Registered
2026-09-03 11:03
Last updated on HF
2026-09-03 12:37

Files by quantization

Auxiliary files 2 files 2.38 KB
.gitattributes 1.48 KB a6344aac download
README.md 923 B 9fd0ac39 download

README current version from Hugging Face


license: apache-2.0
datasets:

  • oyildirim/cyberstrike-sft-120k
    base_model:
  • petruhonk/Qwen3.8-9B-Distill-uncensored-heretic

Used base model is https://huggingface.co/petruhonk/Qwen3.8-9B-Distill-uncensored-heretic
This model is fine tuned using CyberStrike dataset: Aapolon/cyberstrike-sft-120k

This model is intended to use together with CyberStrike AI framework.
Check this out https://cyberstrike.io or https://github.com/CyberStrikeus/CyberStrike

You MUST:

  1. Only use this model within authorized security assessments and security research
  2. Comply with all applicable laws and regulations
  3. Follow responsible disclosure practices for any vulnerabilities discovered
  4. Respect scope and rules of engagement in any testing

You MUST NOT:

  1. Use this model to attack systems without authorization
  2. Use this model for malicious purposes
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