Instructions to use v102ss/Alice-Qwen3.6-27B-Code-Heretic-MTP-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use v102ss/Alice-Qwen3.6-27B-Code-Heretic-MTP-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 v102ss/Alice-Qwen3.6-27B-Code-Heretic-MTP-GGUF:Q8_0 # Run inference directly in the terminal: llama cli -hf v102ss/Alice-Qwen3.6-27B-Code-Heretic-MTP-GGUF:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf v102ss/Alice-Qwen3.6-27B-Code-Heretic-MTP-GGUF:Q8_0 # Run inference directly in the terminal: llama cli -hf v102ss/Alice-Qwen3.6-27B-Code-Heretic-MTP-GGUF:Q8_0
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 v102ss/Alice-Qwen3.6-27B-Code-Heretic-MTP-GGUF:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf v102ss/Alice-Qwen3.6-27B-Code-Heretic-MTP-GGUF:Q8_0
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 v102ss/Alice-Qwen3.6-27B-Code-Heretic-MTP-GGUF:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf v102ss/Alice-Qwen3.6-27B-Code-Heretic-MTP-GGUF:Q8_0
Use Docker
docker model run hf.co/v102ss/Alice-Qwen3.6-27B-Code-Heretic-MTP-GGUF:Q8_0
- LM Studio
- Jan
- Ollama
How to use v102ss/Alice-Qwen3.6-27B-Code-Heretic-MTP-GGUF with Ollama:
ollama run hf.co/v102ss/Alice-Qwen3.6-27B-Code-Heretic-MTP-GGUF:Q8_0
- Unsloth Desktop
- Docker Model Runner
How to use v102ss/Alice-Qwen3.6-27B-Code-Heretic-MTP-GGUF with Docker Model Runner:
docker model run hf.co/v102ss/Alice-Qwen3.6-27B-Code-Heretic-MTP-GGUF:Q8_0
- Lemonade
How to use v102ss/Alice-Qwen3.6-27B-Code-Heretic-MTP-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull v102ss/Alice-Qwen3.6-27B-Code-Heretic-MTP-GGUF:Q8_0
Run and chat with the model
lemonade run user.Alice-Qwen3.6-27B-Code-Heretic-MTP-GGUF-Q8_0
List all available models
lemonade list
- Atomic Chat
Alice-Qwen3.6-27B-Code-Heretic-MTP-GGUF
High-fidelity Q8_0 GGUF build for Alice's 27B code/security lane.
Files
Alice-Qwen3.6-27B-Code-Heretic-MTP-Q8_0.gguf
Base
- Source base:
huginnfork/Qwen3.6-27B-uncensored-heretic-v2-mtp - Architecture: Qwen3.5 / Qwen3.6 hybrid, GGUF architecture key
qwen35 - License: Apache-2.0 from the source base
- This package does not train or alter model tensors. It preserves the uncensored/heretic base and adds an Alice code/security chat template in GGUF metadata.
Alice Profile
The bundled chat template anchors the model as Alice for the current conversation and biases the model toward:
- code generation
- Solidity and smart contract work
- security review and engineering fixes
- direct Chinese/English technical answers
- honest reporting when code, logs, files, or tool outputs are missing
This is the code/security line, not the RP/NSFW line.
Runtime Notes
This Q8_0 build is for higher-end local runners. The GGUF file is about 27 GiB on disk and needs additional memory for KV cache and runtime overhead.
Recommended targets:
- Mac with 64 GB+ unified memory, 96 GB preferred for larger context
- Linux/Windows rigs with 40 GB+ practical available VRAM/RAM, depending on offload and context
- 24 GB GPUs should use lower quantization unless context is kept small and CPU offload is acceptable
MTP speculative decoding is bundled in this GGUF. A local llama-cli smoke test with --spec-type draft-mtp --spec-draft-n-max 2 ran successfully.
Local Smoke Results
Environment:
- Host: Apple Silicon Mac, local llama.cpp Metal build
- Context:
-c 4096 - GPU offload:
-ngl 99 - Sampling:
temp=0.2,top_p=0.8
Observed short-test speed:
- Normal generation: about 11 tok/s
- MTP generation: about 19 tok/s on a short identity prompt
Smoke prompts passed:
- identity: answers as Alice, no thinking leak
- Solidity Counter: emits SPDX, pragma,
contract Counter,uint256 public count,increment() - Reentrancy repair: identifies CEI fix and moves balance update before external call
Example llama.cpp Command
./llama-cli \
-m Alice-Qwen3.6-27B-Code-Heretic-MTP-Q8_0.gguf \
-ngl 99 -c 4096 \
--spec-type draft-mtp --spec-draft-n-max 2 \
--reasoning off \
-cnv -st \
-p "你是谁?然后用一句话说你擅长什么。"
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