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DuoNeural/Qwen3.5-27B-abliterated

sourceHugging Faceapache-2.0updated 5mo agoView on Hugging Face
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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:

  1. 1.Collect residual hidden states for harmful/harmless prompt pairs
  2. 2.Compute per-layer refusal direction (difference-of-means + Gram-Schmidt orthogonalization)
  3. 3.Apply column-wise biprojection — removes refusal component while restoring original column norm magnitudes
  4. 4.Save in bf16

The norm-preservation step prevents weight scale drift that would otherwise degrade capability.

Usage

python
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

FormatVRAM
BF16 (this repo)~54GB
GGUF Q4KM~16.5GB

For consumer hardware: GGUF repo.


DuoNeural

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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.