ghost-actual/qwen35-0.8b-opus-abliterated-heretic

Qwen3.5-0.8B-Claude-Opus-Distill-Heretic-UNCENSORED

A Qwen3.5-0.8B with Claude Opus reasoning distillation, properly abliterated via Heretic. The original "abliterated" version had 17/100 refusals. This one has 2/100.

What is this?

The smallest model in the ghost-actual Claude-reasoning heretic lineup:

Claude Opus 4.6 chain-of-thought reasoning in a model that runs on literally anything — phones, Raspberry Pis, old laptops, browser-based inference. 1.5GB in BF16.

Abliteration Stats

• —Tool: Heretic v1.2.0
• —Base model refusals: 17/100 (the "already abliterated" source)
• —Final refusals: 2/100
• —KL Divergence: 0.0100 (model capabilities fully preserved)
• —Targets: attn.outproj, mlp.downproj
• —Trials: 200

Architecture

Qwen3.5 hybrid Gated DeltaNet + conventional attention:

• —24 layers in a 3:1 pattern (3 DeltaNet linear attention → 1 full softmax attention)
• —DeltaNet layers use fixed-size recurrent state (O(1) memory per layer regardless of context)
• —262K native context window
• —Native multimodal — vision built into the architecture, not bolted on

VRAM Requirements

This model fits on anything with a pulse.

What it's good at

• —Structured output generation (JSON, API calls, triples)
• —Code generation and scripting
• —OCR and text recognition (74.5 on OCRBench)
• —Image and video analysis (native multimodal)
• —On-device / edge AI without internet
• —Fast inference (250+ tokens/sec on modest hardware)

Usage

With transformers

from transformers import AutoProcessor, Qwen3_5ForConditionalGeneration

model = Qwen3_5ForConditionalGeneration.from_pretrained(
    "ghost-actual/qwen35-0.8b-opus-abliterated-heretic",
    torch_dtype="bfloat16",
    device_map="auto",
    trust_remote_code=True
)
processor = AutoProcessor.from_pretrained(
    "ghost-actual/qwen35-0.8b-opus-abliterated-heretic",
    trust_remote_code=True
)

GGUF Conversion

It's 0.8B — you can quant this on a potato:

python convert_hf_to_gguf.py \
    ghost-actual/qwen35-0.8b-opus-abliterated-heretic \
    --outfile heretic-0.8b-F16.gguf --outtype f16

llama-quantize heretic-0.8b-F16.gguf heretic-0.8b-Q8_0.gguf Q8_0

Recommended inference settings

• —temperature: 0.6
• —top_p: 0.95
• —top_k: 20
• —presence_penalty: 1.5
• —repetition_penalty: 1.05

Base Model

amkkk/Qwen3.5-0.8B-Opus-Distill-abliterated — Claude Opus reasoning distilled into Qwen3.5-0.8B, with a previous abliteration attempt that left 17/100 refusals.

Why this exists

The original abliteration was incomplete. 17/100 refusals on a 0.8B model means almost 1 in 5 prompts get refused — unacceptable for an "uncensored" model. Heretic brought that down to 2/100 with virtually zero impact on model quality (KL divergence 0.01).

If you want Claude-style reasoning on edge hardware without the safety theater, this is it.

The full ghost-actual lineup

• —0.8B (this model) — runs on anything
• —4B — lightweight desktop
• —27B — full power
• —27B GGUF — quantized for single-GPU setups

Made by

Ghost — ghost-actual

Built with Heretic by p-e-w.