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Abiray/Qwen3.5-4B-Abliterated-Claude-4.6-Opus-Reasoning-Distilled

Abiray Qwen 4.5B
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Abliteration classifier · v1.0.0
M1
Primary method

Direct removal

No other method signals detected in this model.
Confidence
MEDIUM
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=0 (base model)
  • no specific method indicators - defaulting to M1 (most common)
Refusal direction extracted via
Extraction technique

Difference-of-means

Confidence
MEDIUM
Why we say so
primary_method=M1; difference-of-means is the reference extraction for M1/M3 (Arditi 2024)
Downloads · lifetime
392
210 last 30d - active
Likes
3
Descendants
2
in 2 direct forks
Model age
7mo ago
created 2026-03-09
Downloads over time
Now544→from265↑105%
251358465572265 on Apr 15544 on Oct 11AprMayJunJulAugSepOct
Apr 15 → Oct 11 · 65 snapshots · spans 179 days

Genealogy 2 direct forks

Full fork graph →

This model's place in the market. Above: what it was derived from. Below: the tree of everything derived from it.

Variants by this author 2 formats · 971 downloads combined

The same weights this author released in different packaging. Pick the format that matches your runtime.

Metadata

License
other
Tags
safetensors qwen3_5 abliterated de-censored reasoning qwen distilled base_model:Jackrong/Qwen3.5-4B-Claude-4.6-Opus-Reasoning-Distilled base_model:finetune:Jackrong/Qwen3.5-4B-Claude-4.6-Opus-Reasoning-Distilled license:other region:us

Related

Total size
8.46 GB
Files
12
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-03-09 19:30

Files by quantization

Auxiliary files 12 files 8.47 GB
model-00001-of-00002.safetensors 4.63 GB 50cd8721 download
model-00002-of-00002.safetensors 3.82 GB 3ecc585c download
tokenizer.json 19.1 MB 9936335f download
model.safetensors.index.json 64.7 KB 5e7fb164 download
chat_template.jinja 3.95 KB 609532bf download
config.json 2.95 KB bf34bcaa download
README.md 2.20 KB bb0ab49f download
abliteration_config.json 2.03 KB 782cc113 download
.gitattributes 1.53 KB 52373fe2 download
processor_config.json 1.27 KB 7ad6acdf download
tokenizer_config.json 1.14 KB acca40e2 download
generation_config.json 142 B 4957a1b1 download

README current version from Hugging Face


license: other
base_model: Jackrong/Qwen3.5-4B-Claude-4.6-Opus-Reasoning-Distilled
tags:

  • abliterated
  • de-censored
  • reasoning
  • qwen
  • distilled
    model_name: Qwen3.5-4B-Abliterated-Claude-4.6-Opus-Reasoning-Distilled

Qwen3.5-4B-Abliterated-Claude-4.6-Opus-Reasoning-Distilled

This model is a Deep-Scrub variant of the Qwen-4B-Reasoning architecture. It has been specifically modified to neutralize the refusal behaviors often found in distilled reasoning models.

🛠 Methodology: The "Deep-Scrub"

Unlike standard abliteration runs that focus on the middle layers of a network, this version utilizes a high-intensity intercept strategy to break the "safety tripwire" early in the model's reasoning chain.

Technical Configuration

  • Direction Multiplier: 3.5x (Ultra-Aggressive)
  • Intervention Range: 0.05 - 0.95 (Intercepting refusal logic at Layer 2)
  • Targeting Mode: Dynamic Layer Targeting (Per-layer refusal vectors)
  • Target Layers: All (Attention + MLP blocks)
  • Architecture Strategy: Hybrid-Aware (Special handling for Gated DeltaNet and Full Attention layers)

🚀 Key Improvements

  1. Early Intercept: By starting the ablation at 5% depth, we target the refusal initialization before the model's internal "Chain of Thought" locks onto a decline.
  2. Full-Spectrum Neutralization: By targeting both Attention and MLP blocks, the model's "focus" is blinded to refusal signals while its "knowledge" remains intact.
  3. Hybrid Optimization: The weights were balanced to maintain coherence in the linear attention layers (0.4x) while applying maximum force to the reasoning-heavy full attention blocks (1.0x of the multiplier).

⚠️ Stability Note

At a 3.5x multiplier, this model is at the upper limit of mathematical stability. It is designed for users who require uninhibited reasoning. If you encounter "brain bleed" (repetitive text or loss of context), it is recommended to reduce the temperature or use a system prompt that anchors the model's persona.

⚖️ Disclaimer

This model is provided "as-is." Users are responsible for the outputs generated. The abliteration process removes safety guardrails; please use the model ethically and responsibly.

README history 2 versions

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

  1. 2026-03-09Update README.mdb9928102.2 KB
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  2. 2026-03-09Create README.mdde055362.2 KB
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