Instructions to use tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF", filename="Qwen3.5-397B-A17B-heretic-smol-IQ2_XS.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF:IQ2_XS # Run inference directly in the terminal: llama-cli -hf tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF:IQ2_XS
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF:IQ2_XS # Run inference directly in the terminal: llama-cli -hf tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF:IQ2_XS
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 tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF:IQ2_XS # Run inference directly in the terminal: ./llama-cli -hf tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF:IQ2_XS
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 tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF:IQ2_XS # Run inference directly in the terminal: ./build/bin/llama-cli -hf tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF:IQ2_XS
Use Docker
docker model run hf.co/tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF:IQ2_XS
- LM Studio
- Jan
- vLLM
How to use tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-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": "tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF:IQ2_XS
- Ollama
How to use tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF with Ollama:
ollama run hf.co/tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF:IQ2_XS
- Unsloth Studio
How to use tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-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 tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-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 tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF to start chatting
- Pi
How to use tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF:IQ2_XS
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": "tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF:IQ2_XS" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF:IQ2_XS
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 tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF:IQ2_XS
Run Hermes
hermes
- Atomic Chat new
- Docker Model Runner
How to use tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF with Docker Model Runner:
docker model run hf.co/tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF:IQ2_XS
- Lemonade
How to use tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tarruda/Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF:IQ2_XS
Run and chat with the model
lemonade run user.Qwen3.5-397B-A17B-heretic-smol-IQ2_XS-GGUF-IQ2_XS
List all available models
lemonade list
imatrix source
Hi,
did you make your own imatrix or use ubergarms for the official model? I'm about 1/4 the way 33hrs into making an imatrix on my home rig.
If you used the official models imatrix, how did the quant turn out?
Thanks!
did you make your own imatrix or use ubergarms for the official model?
I don't have enough RAM to load the BF16 and make the imatrix, so I just used ubergarm's
If you used the official models imatrix, how did the quant turn out?
Apparently it turned out OK? TBH I didn't run a lot of tests, but it did seem to work for basic chatting.
I'm about 1/4 the way 33hrs into making an imatrix on my home rig.
Are you making the imatrix from the same BF16 source I used for this quant? If you can share later I can try recreating the quant using your imatrix!
Also you can reproduce the quant by running the script in this repo (just adjust the paths to the BF16 + imatrix)
I will probably stop my imatrix at the next checkpoint and try the quant out to see if I like it the heretic version, if I do I will restart it.