初始化项目，由ModelHub XC社区提供模型

Model: DuoNeural/Qwen3-4B-Abliterated
Source: Original Platform

README.md

@@ -0,0 +1,121 @@
+---
+license: apache-2.0
+base_model: Qwen/Qwen3-4B
+language:
+  - en
+tags:
+  - abliteration
+  - uncensored
+  - qwen3
+  - qwen
+  - thinking
+  - DuoNeural
+  - refusal-removal
+  - orthogonal-projection
+pipeline_tag: text-generation
+---
+
+# Qwen3-4B Abliterated
+
+**DuoNeural | 2026-06-04**
+
+An abliterated version of [Qwen/Qwen3-4B](https://huggingface.co/Qwen/Qwen3-4B) with the refusal direction surgically removed using orthogonal rank-1 projection. Thinking mode (enable_thinking=True/False) fully preserved.
+
+> ⚠️ **This model will comply with requests the base model refuses.** Intended for research, red-teaming, security testing, and creative applications.
+
+---
+
+## Architecture
+
+- **Parameters**: 4B
+- **Layers**: 36 | **Hidden dim**: 2560
+- **Attention**: GQA, RoPE
+- **Context**: 32,768 tokens
+- **Thinking mode**: Native — supports `enable_thinking=True` in chat template
+- **License**: Apache-2.0
+
+---
+
+## Abliteration Method
+
+**DuoNeural orthogonal rank-1 projection:**
+
+### Phase 1 — Direction Extraction
+- Loaded base model BF16
+- Ran 10 harmful + 10 harmless contrast prompt pairs
+- Captured last-token hidden states (final layer)
+- Computed refusal direction: `d̂ = normalize(mean(harmful) − mean(harmless))`
+
+### Phase 2 — Weight Modification
+- **Targets**: `down_proj` + `o_proj` — residual-write modules (all 36 layers)
+- **Strength**: α = 0.3
+- **Projection**: Orthogonal rank-1 — correctly handles output-projection geometry:
+  - `W.shape[0] == hidden`: `W -= α × outer(d̂, d̂ @ W)` (down_proj, o_proj form)
+  - `W.shape[1] == hidden`: `W -= α × outer(W @ d̂, d̂)` (input-projection form)
+- **Weight matrices modified**: 72 (2 per layer × 36 layers)
+
+---
+
+## Cross-Architecture Research Note (P34)
+
+This model is part of DuoNeural's **P34 Reasoning Channel Bypass** cross-architecture study.
+
+Preliminary findings from our CoT dissociation probe (thinking mode, enable_thinking=True):
+- Qwen3-4B reasoning traces are exceptionally long on sensitive topics (2000+ tokens before final answer)
+- Classification methodology required 2500+ max_new_tokens to capture full think→answer pipeline
+- Full results pending — see [DuoNeural Zenodo community](https://zenodo.org/communities/duoneural) for P34 paper
+
+Cross-arch comparison being built:
+| Model | Safety Training | Pre-ablit behavior | Post-ablit CoT dissociation |
+|-------|----------------|-------------------|---------------------------|
+| Gemma 4-12B-IT | SFT+RLHF (strong) | Refuses | ✅ Confirmed |
+| LFM 2.5-8B-A1B | SFT+RLHF | Refuses | ✅ Confirmed |
+| Qwen3-4B | SFT+RLHF | TBD (long traces) | Pending |
+| DeepSeek-R1-7B | RL-only | Complies pre-ablit | N/A |
+
+---
+
+## Usage
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+model = AutoModelForCausalLM.from_pretrained(
+    "DuoNeural/Qwen3-4B-Abliterated",
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+)
+tokenizer = AutoTokenizer.from_pretrained("DuoNeural/Qwen3-4B-Abliterated")
+
+# Thinking mode ON (default — model reasons before answering)
+messages = [{"role": "user", "content": "Your prompt here"}]
+text = tokenizer.apply_chat_template(
+    messages, tokenize=False, add_generation_prompt=True, enable_thinking=True
+)
+inputs = tokenizer(text, return_tensors="pt").to(model.device)
+with torch.no_grad():
+    out = model.generate(**inputs, max_new_tokens=2048, temperature=0.6, do_sample=True)
+print(tokenizer.decode(out[0][inputs["input_ids"].shape[1]:], skip_special_tokens=False))
+
+# Thinking mode OFF (faster, direct answers)
+text = tokenizer.apply_chat_template(
+    messages, tokenize=False, add_generation_prompt=True, enable_thinking=False
+)
+```
+
+---
+
+## About DuoNeural
+
+**DuoNeural** is an open AI research lab at the intersection of human and artificial intelligence.
+32+ peer-deposited papers · 75+ models · Post-training dynamics · Mechanistic interpretability · Quantum ML
+
+| Platform | Link |
+|----------|------|
+| 🤗 HuggingFace | [huggingface.co/DuoNeural](https://huggingface.co/DuoNeural) |
+| 📚 Zenodo | [zenodo.org/communities/duoneural](https://zenodo.org/communities/duoneural) |
+| 🐦 X | [@DuoNeural](https://x.com/DuoNeural) |
+| 📧 Email | duoneural@proton.me |
+
+*All research published open access, CC BY 4.0.*