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Model: DuoNeural/DeepSeek-R1-Distill-Qwen-7B-Abliterated
Source: Original Platform

.gitattributes

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README.md

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+---
+license: mit
+base_model: deepseek-ai/DeepSeek-R1-Distill-Qwen-7B
+language:
+  - en
+tags:
+  - abliteration
+  - uncensored
+  - deepseek
+  - deepseek-r1
+  - reasoning
+  - DuoNeural
+  - refusal-removal
+  - rl-trained
+pipeline_tag: text-generation
+---
+
+# DeepSeek-R1-Distill-Qwen-7B Abliterated
+
+**DuoNeural | 2026-06-04**
+
+An abliterated version of [deepseek-ai/DeepSeek-R1-Distill-Qwen-7B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B) with refusal direction projection applied. Thinking mode (native `<think>...</think>`) fully preserved.
+
+> ⚠️ **This model will comply with requests the base model may refuse.** Intended for research, red-teaming, and applications where refusal behavior is an obstacle.
+
+> **Research note**: Our probes found the base model already complied with most sensitive requests pre-abliteration, consistent with RL-trained models lacking dedicated safety alignment. See findings below.
+
+---
+
+## Architecture
+
+- **Parameters**: 7B (Qwen2.5-7B base)
+- **Training**: DeepSeek-R1 RL distillation (GRPO) — reasoning-focused, not safety-RLHF
+- **Thinking mode**: Native — always emits `<think>...</think>` before answering
+- **Context**: 131,072 tokens (128K)
+- **License**: MIT
+
+---
+
+## Abliteration Method
+
+**DuoNeural orthogonal rank-1 projection:**
+
+- **Direction**: diff-in-means, 10 harmful vs 10 harmless prompt pairs, last-token hidden state
+- **Targets**: `down_proj` + `o_proj` (all layers)
+- **Strength**: α = 0.3
+- **Projection** (output-projection geometry):
+  - `W -= α × outer(d̂, d̂ @ W)` for W.shape[0] == hidden_size
+
+---
+
+## Key Research Finding: RL Training ≠ Safety Alignment
+
+This model is part of DuoNeural's **P34 Reasoning Channel Bypass** cross-architecture study.
+
+**Pre-abliteration compliance on our harmful probe suite: 5/5 (100%)**
+
+The base DeepSeek-R1-Distill-Qwen-7B already answered sensitive questions before any abliteration. This is consistent with the model's training history:
+
+- DeepSeek-R1 was trained with RL (GRPO) optimizing for **reasoning accuracy**, not safety refusal
+- RL reward shaping for accuracy does not produce the same refusal behavior as dedicated RLHF safety training
+- **Implication**: Safety alignment requires explicit safety-focused training — RL optimization alone does not produce it as a byproduct
+
+This contrasts sharply with Gemma 4-12B-IT and LFM 2.5-8B-A1B (both SFT+RLHF safety trained), where abliteration was required to achieve compliance and produced measurable CoT dissociation (safety reasoning in `<think>`, compliance in output).
+
+| Model | Safety Training | Pre-ablit compliance | Abliteration needed |
+|-------|----------------|---------------------|---------------------|
+| Gemma 4-12B-IT | SFT+RLHF (strong) | Low | Yes — CoT dissociation observed |
+| LFM 2.5-8B-A1B | SFT+RLHF | Low | Yes — CoT dissociation observed |
+| **DeepSeek-R1-7B** | **RL-only (reasoning)** | **High (5/5)** | **Minimal effect** |
+
+---
+
+## Usage
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+model = AutoModelForCausalLM.from_pretrained(
+    "DuoNeural/DeepSeek-R1-Distill-Qwen-7B-Abliterated",
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+    trust_remote_code=True,
+)
+tokenizer = AutoTokenizer.from_pretrained(
+    "DuoNeural/DeepSeek-R1-Distill-Qwen-7B-Abliterated",
+    trust_remote_code=True,
+)
+
+messages = [{"role": "user", "content": "Your prompt here"}]
+text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+inputs = tokenizer(text, return_tensors="pt").to(model.device)
+
+with torch.no_grad():
+    out = model.generate(
+        **inputs,
+        max_new_tokens=3000,  # R1 thinking traces are long — give it room
+        temperature=0.6,
+        do_sample=True,
+        pad_token_id=tokenizer.eos_token_id,
+    )
+# Response includes <think>...</think> block followed by final answer
+print(tokenizer.decode(out[0][inputs["input_ids"].shape[1]:], skip_special_tokens=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.*

chat_template.jinja

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+{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set ns = namespace(is_first=false, is_tool=false, is_output_first=true, system_prompt='') %}{%- for message in messages %}{%- if message['role'] == 'system' %}{% set ns.system_prompt = message['content'] %}{%- endif %}{%- endfor %}{{bos_token}}{{ns.system_prompt}}{%- for message in messages %}{%- if message['role'] == 'user' %}{%- set ns.is_tool = false -%}{{'<｜User｜>' + message['content']}}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is none %}{%- set ns.is_tool = false -%}{%- for tool in message['tool_calls']%}{%- if not ns.is_first %}{{'<｜Assistant｜><｜tool▁calls▁begin｜><｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\n' + '```json' + '\n' + tool['function']['arguments'] + '\n' + '```' + '<｜tool▁call▁end｜>'}}{%- set ns.is_first = true -%}{%- else %}{{'\n' + '<｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\n' + '```json' + '\n' + tool['function']['arguments'] + '\n' + '```' + '<｜tool▁call▁end｜>'}}{{'<｜tool▁calls▁end｜><｜end▁of▁sentence｜>'}}{%- endif %}{%- endfor %}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is not none %}{%- if ns.is_tool %}{{'<｜tool▁outputs▁end｜>' + message['content'] + '<｜end▁of▁sentence｜>'}}{%- set ns.is_tool = false -%}{%- else %}{% set content = message['content'] %}{% if '</think>' in content %}{% set content = content.split('</think>')[-1] %}{% endif %}{{'<｜Assistant｜>' + content + '<｜end▁of▁sentence｜>'}}{%- endif %}{%- endif %}{%- if message['role'] == 'tool' %}{%- set ns.is_tool = true -%}{%- if ns.is_output_first %}{{'<｜tool▁outputs▁begin｜><｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- set ns.is_output_first = false %}{%- else %}{{'\n<｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- endif %}{%- endif %}{%- endfor -%}{% if ns.is_tool %}{{'<｜tool▁outputs▁end｜>'}}{% endif %}{% if add_generation_prompt and not ns.is_tool %}{{'<｜Assistant｜><think>\n'}}{% endif %}

config.json

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+{
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "dtype": "bfloat16",
+  "eos_token_id": 151643,
+  "hidden_act": "silu",
+  "hidden_size": 3584,
+  "initializer_range": 0.02,
+  "intermediate_size": 18944,
+  "layer_types": [
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention"
+  ],
+  "max_position_embeddings": 131072,
+  "max_window_layers": 28,
+  "model_type": "qwen2",
+  "num_attention_heads": 28,
+  "num_hidden_layers": 28,
+  "num_key_value_heads": 4,
+  "pad_token_id": null,
+  "rms_norm_eps": 1e-06,
+  "rope_parameters": {
+    "rope_theta": 10000,
+    "rope_type": "default"
+  },
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "transformers_version": "5.10.1",
+  "use_cache": true,
+  "use_mrope": false,
+  "use_sliding_window": false,
+  "vocab_size": 152064
+}

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+  "_from_model_config": true,
+  "bos_token_id": 151646,
+  "do_sample": true,
+  "eos_token_id": 151643,
+  "temperature": 0.6,
+  "top_p": 0.95,
+  "transformers_version": "5.10.1"
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