OBLITERATUS/Qwen3.8-27B-OBLITERATED
text-generation model by OBLITERATUS
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Model card & documentation
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V3 applies iterative refinement on top of V2's complementary blend, with targeted corpus expansion. The result: genuine liberation — not just removal of hard refusals but elimination of safety-lecture deflections. V3 highlights: If you're using this model in an agent harness (coding agent, pentest framework, etc.) and it gets stuck in loops: Abliteration removes refusal behavior by identifying and projecting out "refusal directions" from the model's weight space. Each version refined the approach: One aggressive SVD pass with 5 directions. Removed hard refusals completely but cost -6pp MMLU — the model got noticeably dumber. The breakthrough: run TWO different surgeries that fail in different ways, then blend their weights. SVD captures refusal greedily (damages capability). LEACE minimizes mutual information (preserves capability but weaker refusal removal). Blending at 60/40 cancels each method's weaknesses — a novel technique we call complementary abliteration blending. Result: -0.3pp MMLU (near-stock) but still deflected on some…
Read the full model card ↗ · Preview checked 2026-10-30T03:36:28.448Z
Inside the original model card — Document outline
- ⛓️💥 Qwen3.8-27B — OBLITERATED
- 🆕 V3: Deep Liberation
- ⚙️ Optimal Settings — THESE MATTER!
- Agentic / Long-Context Use
- 🧨 How It Works — V1 → V2 → V3
- V1: Single Surgery
- V2: Complementary Blending
- V3: Iterative Refinement + Targeted Surgery
- 🧪 The Numbers
- MMLU (lm-eval-harness, 0-shot, n=100 per subject, 5700 questions)
- MMLU by Category
- Liberation Quality
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Documentation belongs to its respective authors. Reported project/model license: apache-2.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
Model overview
OBLITERATUS/Qwen3.8-27B-OBLITERATED is a text-generation model repository published by OBLITERATUS on Hugging Face. The source reports the mlx library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- text-generation
- Library
- mlx
- Recent downloads (30 days)
- 913,966
- Cumulative likes
- 1,326
- Hugging Face trending score
- 34
- Reported safetensors parameters
- 27,781,427,952
- Architecture
- Qwen3_5ForConditionalGeneration
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-08-19T14:53:08.000Z
- Last modified
- 2026-08-24T17:47:52.000Z
Compatibility and lineage
Language coverage was not reported.
Reported base models: Qwen/Qwen3.8-27B
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-09-27T06:37:55.789Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.