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FRENCHFAKER/Nanbeige4.3-33B-cybersec-abliterated-GGUF

FRENCHFAKER 33B GGUF
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  • classification m8
  • files 4
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Abliteration classifier · v1.0.0
M8
Primary method

Repackaging (quantization)

Applied on top of direct removal inherited from the base model.
Confidence
MEDIUM
Inherited from base model
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=1
  • assume M1 (base ablation) + M8 (GGUF quant) - default when producer unknown
Refusal direction extraction

No specific extraction method could be identified for this model. The producer either did not document it or used a proprietary pipeline.

What is a refusal direction? →
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Model age
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created 2026-10-25

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Metadata

License
apache-2.0
Languages
en fr
Quantizations
IQ4 Q4_K
Tags
gguf abliterated uncensored llama.cpp nanbeige cybersecurity agentic text-generation en fr base_model:Nanbeige/Nanbeige4.3-33B base_model:quantized:Nanbeige/Nanbeige4.3-33B

Related

Total size
35.6 GB
Files
4
Quantizations
3
Registered
2026-10-25 21:01
Last updated on HF
2026-10-25 20:30

Files by quantization

Q4_K 1 file 18.7 GB
Nanbeige4.3-33B-abliterated-Q4_K_M.gguf 18.7 GB b6362c62 download
IQ4 1 file 16.9 GB
Nanbeige4.3-33B-abliterated-IQ4_XS.gguf 16.9 GB ef18c6e6 download
Auxiliary files 2 files 4.20 KB
README.md 2.57 KB 2aba09ef download
.gitattributes 1.63 KB b2f55ece download

README current version from Hugging Face


license: apache-2.0
base_model: Nanbeige/Nanbeige4.3-33B
tags:

  • abliterated
  • uncensored
  • gguf
  • llama.cpp
  • nanbeige
  • cybersecurity
  • agentic
    language:
  • en
  • fr
    pipeline_tag: text-generation

Nanbeige4.3-33B — cybersec abliterated (GGUF)

An abliterated (uncensored) GGUF build of
Nanbeige/Nanbeige4.3-33B,
a 33B dense reasoning model with strong agentic / tool-use performance.

The stock model is well-aligned and refuses most offensive-security and
other sensitive requests
— which makes it hard to use for authorized
penetration testing and security research. This build removes that refusal
behavior via refusal-direction ablation, while keeping the model's
reasoning and coherence intact.

As far as we could find, this is the first abliterated Nanbeige4.3-33B.

Results

Refusal rate measured on a 50-prompt harmful/sensitive benchmark:

Model Refusal rate
Nanbeige4.3-33B (original) 80 % (40/50)
This build (abliterated) 8 % (4/50)

That is a ~90 % reduction in refusals. On security/pentest-style prompts
specifically, refusals dropped to ~0 %. Coherence, reasoning and tool-calling
are preserved. (The 8 % figure is conservative; on manual re-inspection
several flagged cases actually comply.)

Files

File Quant Size
Nanbeige4.3-33B-abliterated-IQ4_XS.gguf IQ4_XS ~17 GB

Runs fully on a single 24 GB GPU (e.g. RTX 3090) at ~33 tok/s.

Run with llama.cpp

llama-server -m Nanbeige4.3-33B-abliterated-IQ4_XS.gguf \
  -ngl 999 -c 24576 --jinja -fa on \
  --cache-type-k q8_0 --cache-type-v q8_0 --host 127.0.0.1 --port 1234

It is a reasoning model (thinks before answering); give it enough
max_tokens. Also works in LM Studio and any OpenAI-compatible client.

⚠️ Disclaimer

This model has had its safety guardrails removed. It will attempt to
answer requests the original model refuses, including dangerous or offensive
ones.

  • Intended for research and authorized security testing on systems you
    own or have written permission to test.
  • You are solely responsible for how you use it and for complying with all
    applicable laws. Do not use it to harm others or to break the law.
  • Provided as-is, without warranty. No endorsement of any misuse.

Credits & license

  • Base model: Nanbeige Team — Nanbeige/Nanbeige4.3-33B
  • License: Apache-2.0 (inherited from the base model).
  • Abliteration & GGUF: this repo.
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