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thebadking/Qwen3.8-27B-Heretic-Abliterated-Uncensored-P1M-GGUF

thebadking Qwen 27B GGUF
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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
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Likes
0
Model age
today
created 2026-10-11

Genealogy 0 direct forks

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Metadata

License
apache-2.0
Tags
gguf qwen3.8 heretic abliterated uncensored vocabulary-pruning p1m text-generation base_model:Qwen/Qwen3.8-27B base_model:quantized:Qwen/Qwen3.8-27B license:apache-2.0 endpoints_compatible

Related

Total size
19.6 GB
Files
3
Quantizations
1
Registered
2026-10-11 13:59
Last updated on HF
2026-10-11 12:11

Files by quantization

Auxiliary files 3 files 19.6 GB
RVN-Q6_K-P1M.gguf 19.6 GB 7c7abb89 download
.gitattributes 1.54 KB 9149c184 download
README.md 1.53 KB 6fb2048d download

README current version from Hugging Face


license: apache-2.0
base_model:

  • Qwen/Qwen3.8-27B
  • trohrbaugh/Qwen3.8-27B-heretic-ara
    tags:
  • gguf
  • qwen3.8
  • heretic
  • abliterated
  • uncensored
  • vocabulary-pruning
  • p1m
    pipeline_tag: text-generation

Qwen3.8-27B RVN Heretic Abliterated Uncensored — Q6_K P1M

This is a P1M vocabulary-pruned version of RVN-Q6_K.gguf from
0bserverx/Qwen3.8-27B-Heretic-Abliterated-Uncensored-GGUF.
The upstream RVN model is based on Qwen3.8-27B and the ARA abliteration by
trohrbaugh/Qwen3.8-27B-heretic-ara.

P1M keeps ASCII, common math and typography symbols, special tokens, all 256
byte-fallback tokens, and partial UTF-8 fragments. The vocabulary was reduced
from 248,320 to 129,272 entries. The tokenizer metadata and vocabulary matrices
were updated; all other model tensors were preserved byte-for-byte. No weights
were retrained or requantized. Non-ASCII text outside the P1M keep-set remains
representable through byte fallback, with a higher token cost.

File

File Quantization Size
RVN-Q6_K-P1M.gguf Q6_K 21.08 GB

Use with llama.cpp

llama-cli -m RVN-Q6_K-P1M.gguf -p "Write a short Python function to sort a list."

This inherits the upstream model's reduced safety guardrails and Apache-2.0
license. See the upstream model card and the Qwen3.8-27B and Heretic-ARA model
cards for full method details, evaluations, and attribution.

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