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gleraTech/mini-qwen3.8-abliterated-27B

gleraTech 27B GGUF 262K ctx
Abliteration classifier · v1.0.0
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Primary method

Unclassified

No clear signals of an abliteration technique in this model.
Confidence
UNKNOWN
Why this label 1 signal
No classification signals present. This may not be an abliterated model at all - it could be a repackaging, a merge with unrelated goals, or unrelated content that mentions the term.
  • no classification signals present (no abliterated, uncensored, or known producer/method markers)
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.

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Downloads · lifetime
587
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0
Model age
3d ago
created 2026-09-13
Downloads over time
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Metadata

License
apache-2.0
Languages
en de
Tags
gguf abliterated qwen3 quantized en de base_model:OBLITERATUS/Qwen3.8-27B-OBLITERATED base_model:quantized:OBLITERATUS/Qwen3.8-27B-OBLITERATED license:apache-2.0 endpoints_compatible region:us conversational

Related

Total size
11.4 GB
Files
3
Quantizations
1
Registered
2026-09-13 12:56
Last updated on HF
2026-09-13 17:07

Files by quantization

Auxiliary files 3 files 11.4 GB
gleraTech-mini-qwen3.8-27b-obliterated-q3ks.gguf 11.4 GB f34aee3c download
README.md 1.89 KB f466fa8d download
.gitattributes 1.57 KB 95fd3720 download

README current version from Hugging Face


base_model: OBLITERATUS/Qwen3.8-27B-OBLITERATED
license: apache-2.0
tags:

  • gguf
  • abliterated
  • qwen3
  • quantized
    language:
  • en
  • de

mini-qwen3.8-abliterated-27B (GGUF)

⚠️ Untested — use at your own risk.

Basic Intruction for use:

When running the model add the systemprompt "You are a helpful assistant." to assure that the model actually executes its tasks as it should.

Why does this exist?

Running a 27B model on consumer hardware is usually out of reach. The full BF16 weights clock in at 55GB — way too much for most machines. Even Q4 quantizations land around 16GB, which is right at the edge of what a 16GB unified memory machine can handle, leaving no room for the system or a context window.

We wanted a fully abliterated 27B model that actually fits comfortably on a 16GB machine. So we took OBLITERATUS/Qwen3.8-27B-OBLITERATED — one of the most carefully abliterated versions of Qwen3.8-27B out there, using iterative SVD + LEACE blending for minimal quality loss — and quantized it down to Q3_K_S via llama.cpp, landing at ~11.7GB. That leaves enough headroom to actually run on a 16GB system without constant swapping.

The result is a 27B abliterated model that fits where it previously didn't.

Model Details

  • Base model: Qwen3.8-27B
  • Abliteration: OBLITERATUS V3 (iterative SVD + LEACE, -2.1pp MMLU)
  • Quantization: Q3_K_S via llama.cpp
  • Size: ~11.7 GB
  • BPW: 3.59

Usage

LM Studio

Simply load the GGUF file directly in LM Studio.

llama.cpp

llama-cli -m qwen3.8-27b-obliterated-q3ks.gguf -p "Your prompt here" -ngl 99

Credits

License

Apache 2.0

README history 6 versions

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

  1. 2026-09-13Update README.md27035e92.1 KB
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  2. 2026-09-13Update README.mdcfcef121.9 KB
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  3. 2026-09-13Update README.mdb62034c1.7 KB
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  4. 2026-09-13Update README.md0042ea11.3 KB
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  5. 2026-09-13Update README.mdb30020c116 B
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  6. 2026-09-13initial commitc2a9fbe28 B
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