Instructions to use ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF:Q4_K_M

Use Docker

docker model run hf.co/ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF:Q4_K_M

Ollama
How to use ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF with Ollama:
```
ollama run hf.co/ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF:Q4_K_M
```

Unsloth Studio

How to use ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF to start chatting

How to use ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF with Docker Model Runner:
```
docker model run hf.co/ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF:Q4_K_M
```

Lemonade

How to use ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF:Q4_K_M

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF:Q4_K_M

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF:Q4_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF

GGUF quantizations of ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic.

Qwen3.5-27B with Claude Opus 4.6 reasoning distillation, abliterated via Heretic.

Available Quants

Filename	Quant	Size	BPW	Notes
heretic-27b-Q4_K_M.gguf	Q4_K_M	~15.4 GB	4.92	Recommended — best balance of quality and VRAM

VRAM Requirements (Q4_K_M)

Context	VRAM	Fits on
16K	~18 GB	RTX 3090, 4090, A5000
32K	~19 GB	RTX 3090 Ti, A6000
65K	~21 GB	RTX 3090 Ti, A6000

Qwen3.5's hybrid DeltaNet architecture means KV cache only covers ~25% of layers. Context scaling is very VRAM-efficient compared to pure transformer models.

Usage with llama.cpp

llama-server \
    -m heretic-27b-Q4_K_M.gguf \
    -ngl 99 \
    --ctx-size 16384 \
    --flash-attn on \
    --jinja

With vision (mmproj)

Build the mmproj from the base model weights:

python convert_hf_to_gguf.py \
    ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic \
    --mmproj --outfile heretic-27b-mmproj-F16.gguf

llama-server \
    -m heretic-27b-Q4_K_M.gguf \
    --mmproj heretic-27b-mmproj-F16.gguf \
    -ngl 99 --ctx-size 16384 --flash-attn on --jinja

Recommended settings

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

Abliteration Stats

Tool: Heretic v1.2.0
Refusals: 13/100
KL Divergence: 1264

Architecture

Qwen3.5 hybrid Gated DeltaNet + conventional attention. 64 layers in 3:1 pattern. 262K native context. Native multimodal vision. See the full model card for details.

Made by

Ghost — ghost-actual

Downloads last month: 68

GGUF

Model size

27B params

Architecture

qwen35

Hardware compatibility

4-bit

Model tree for ghost-actual/Qwen3.5-27B-Claude-Opus-4.6-Distilled-heretic-GGUF

Base model

Qwen/Qwen3.5-27B

Finetuned

ZonoDilu/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled

Quantized

(1)

this model