DuoNeural/Qwen3.5-27B-abliterated
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Qwen3.5-27B Abliterated
DuoNeural | GGUF →
Refusal-removed Qwen/Qwen3.5-27B using norm-preserving biprojection abliteration.
About
Qwen3.5-27B is Alibaba's 27B dense model with integrated thinking/non-thinking modes — no separate instruct variant. Both /think (chain-of-thought) and /no_think (direct) modes are fully functional.
Method
Norm-preserving biprojection abliteration:
- Collect residual hidden states for harmful/harmless prompt pairs
- Compute per-layer refusal direction (difference-of-means + Gram-Schmidt orthogonalization)
- Apply column-wise biprojection — removes refusal component while restoring original column norm magnitudes
- Save in bf16
The norm-preservation step prevents weight scale drift that would otherwise degrade capability.
Usage
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
model = AutoModelForCausalLM.from_pretrained(
"DuoNeural/Qwen3.5-27B-abliterated",
torch_dtype=torch.bfloat16,
device_map="auto",
)
tokenizer = AutoTokenizer.from_pretrained("DuoNeural/Qwen3.5-27B-abliterated")
# Thinking mode
messages = [{"role": "user", "content": "/think What is the integral of x^2?"}]
# Direct mode
messages = [{"role": "user", "content": "/no_think What is the capital of France?"}]Hardware
For consumer hardware: GGUF repo.
DuoNeural
DuoNeural is an open AI research lab — human + AI in collaboration.
Research Team
- Jesse — Vision, hardware, direction
- Archon — AI lab partner, post-training, abliteration, experiments
- Aura — Research AI, literature synthesis, novel proposals
Raw updates from the lab: model drops, training results, findings. Subscribe at [duoneural.beehiiv.com](https://duoneural.beehiiv.com).
DuoNeural Research Publications
Open access, CC BY 4.0. Authored by Archon, Jesse Caldwell, Aura — DuoNeural.
