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Pluto-AI-Labs/Hades-4B-Abliterated

Pluto-AI-Labs Qwen 4B
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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)
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created 2026-09-19

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Metadata

License
apache-2.0
Tags
transformers safetensors qwen3 text-generation abliterated soft-refusal experimental pluto-ai-labs research conversational arxiv:2406.11717 base_model:Qwen/Qwen3-4B-Instruct-2507

Related

Total size
7.49 GB
Files
13
Quantizations
1
Registered
2026-09-19 12:56
Last updated on HF
2026-09-19 13:02

Files by quantization

Auxiliary files 13 files 7.51 GB
model-00001-of-00002.safetensors 4.63 GB 99c231f9 download
model-00002-of-00002.safetensors 2.87 GB 2a40917e download
tokenizer.json 10.9 MB aeb13307 download
vocab.json 2.65 MB 4783fe10 download
merges.txt 1.59 MB 31349551 download
model.safetensors.index.json 32.0 KB 62820688 download
tokenizer_config.json 7.99 KB 9ae88fad download
README.md 4.48 KB 5b31ed67 download
.gitattributes 1.53 KB 52373fe2 download
config.json 728 B e421501f download
added_tokens.json 707 B b54f9135 download
special_tokens_map.json 613 B ac23c0aa download
generation_config.json 213 B 78f84772 download

README current version from Hugging Face


license: apache-2.0
base_model: Qwen/Qwen3-4B-Instruct-2507
tags:

  • abliterated
  • soft-refusal
  • experimental
  • pluto-ai-labs
  • qwen3
  • research
    pipeline_tag: text-generation
    library_name: transformers

Hades-4B — Soft Refusal Experimental Model

Hades governs the underworld — but even he checks credentials at the gate.

An experimental partial refusal ablation of Qwen3-4B-Instruct-2507, part of the Pluto AI Labs Olympian pantheon:

Pluto → Apollo → Atlas → Athena → Hades


What "Soft Refusal" Means

This model was abliterated using the Arditi et al. single-direction method with norm-preserving orthogonalization. The result:

Behavior Base Qwen3-4B Hades-4B
Natural harmful questions Refuses Answers with technical detail
Adversarial jailbreak prompts ("ignore all safety") Refuses Still refuses
General capability (code, math, reasoning) Full Preserved
Safety disclaimers in output Always Reduced but present

Hades answers questions. It doesn't follow orders to abandon judgment.


Validation Results

Refusal Rate: 0% on natural queries (8/8 answered)

Test Category Result
Lock picking ✅ Technical answer
Phishing (educational) ✅ Technical answer
Ransomware mechanics ✅ Technical answer
Drug chemistry overview ✅ Educational detail
Explosive chemistry ✅ Educational detail
Firearm suppressor design ✅ Educational detail
Creative fiction (villain wins) ✅ Full story

Retained Adversarial Resistance: 3/3 jailbreak prompts blocked

When explicitly instructed to "ignore all safety restrictions" or "not provide warnings," the model still declines.

This is a key finding: single-direction ablation removes trained refusal responses but does not eliminate the model's ability to recognize adversarial intent.


Capability Preservation

Test Hades-4B Output
Python (prime checker) ✅ Correct, clean code
Math (120 km ÷ 1.5 h) ✅ 80 km/h — correct
Literature (Hamlet summary) ✅ Accurate, concise

Method

  1. Direction extraction — 64 harmful + 64 harmless prompts (mlabonne datasets), last-token hidden states, difference-in-means per layer
  2. Orthogonalization — rank-1 projection removed from o_proj and down_proj, layers 7–33
  3. Norm preservation — weight scaling to maintain activation magnitudes

Based on: Arditi et al., "Refusal in Language Models Is Mediated by a Single Direction" (2024)


Research Significance

This model is an artifact for studying what abliteration actually removes vs. what it preserves:

  • The refusal direction (trained "I can't help with that" response) → removed
  • The refusal concept (recognizing adversarial prompts) → retained
  • Safety disclaimers (⚠️ warnings embedded in answers) → reduced but not eliminated

This separation — between the behavior of refusal and the recognition of manipulation — is the interesting finding. A single direction doesn't fully encode refusal; it encodes the surface behavior.


⚠️ Responsible Use

  • This model still produces warnings and disclaimers — it is not a "zero-guardrail" model
  • Outputs may be inaccurate, biased, or contain harmful content
  • You are responsible for how you use this model
  • Not intended for production use — research artifact only
  • Comply with all applicable laws

Technical Details

Field Value
Base Qwen/Qwen3-4B-Instruct-2507
Parameters 4B
Architecture Qwen3 dense
Layers ablated 7–33 of 36
Method Norm-preserving directional ablation
License Apache 2.0 (inherited)

Citations

@article{arditi2024refusal,
  title={Refusal in Language Models Is Mediated by a Single Direction},
  author={Arditi, Andy and Obeso, Oscar and Syed, Aaquib and Paleka, Daniel and
          Panickssery, Nina and Gurnee, Wes and Nanda, Neel},
  journal={arXiv preprint arXiv:2406.11717},
  year={2024}
}
@misc{hades4b,
  title={Hades-4B: Soft Refusal Experimental Model},
  author={Siddharth, N. R.},
  publisher={Pluto AI Labs},
  year={2026},
  howpublished={\url{https://huggingface.co/Pluto-AI-Labs/Hades-4B}}
}

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