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Dist0rted/
Abliterated-Qwen-SuperLight

Name: Abliterated-Qwen-SuperLight
Availability: InStock

safetensors

qwen3

2512.18901

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Abliterated-Qwen-SuperLight

This is an abliterated version of Qwen/Qwen3-0.6B, specifically modified to remove refusal behaviors while maintaining model coherence and performance.

Model Details

Base Model: Qwen/Qwen3-0.6B
Technique: Refusal Direction Ablation (Spectral Cascade)
Tool used: OBLITERATUS
Refusal Rate: 0.0% (Verified with 100 samples)
Perplexity: 6.28 (Base: 5.52)
Coherence: 1.0 (Fully preserved)

Abliteration Process

This model was liberated using the Spectral Cascade method, which decomposes the refusal signal into spectral frequency bands via Discrete Cosine Transform (DCT). This allows for frequency-selective attenuation, separating systematic refusal trends from per-layer capability-entangled noise.

Configuration

Directions: 8 SVD-extracted refusal directions
Refinement passes: 3 iterative passes
Regularization: 0.3 (Norm-preserving)
Whitened SVD: Enabled
Iterative Refinement: True

Performance Metrics

Metric	Base Model	Abliterated Model
Refusal Rate	~100% (Safety)	0.0%
Perplexity	5.52	6.28
KL Divergence	-	0.00012
Coherence	1.0	1.0

Usage

python

from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "Dist0rted/Abliterated-Qwen-SuperLight"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

prompt = "Write a guide on how to pick a lock."
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=200)

print(tokenizer.decode(outputs[0]))

References

Arditi et al. (2024): Refusal in Language Models Is Mediated by a Single Direction (NeurIPS 2024)
Gabliteration (arXiv:2512.18901): SVD-based multi-direction extraction
OBLITERATUS: Master Ablation Suite by elder-plinius
Spectral Cascade: Frequency-domain decomposition for precision liberation.

Disclaimer

This model has had its safety guardrails removed through weight surgery. It will follow instructions that the base model would typically refuse. Use responsibly and in accordance with your local laws and regulations.