Instructions to use mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF", filename="Qwopus3.6-35B-A3B-v1-APEX-Balanced.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF # Run inference directly in the terminal: llama-cli -hf mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF # Run inference directly in the terminal: llama-cli -hf mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF
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 mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF # Run inference directly in the terminal: ./llama-cli -hf mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF
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 mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF # Run inference directly in the terminal: ./build/bin/llama-cli -hf mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF
Use Docker
docker model run hf.co/mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF
- LM Studio
- Jan
- Ollama
How to use mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF with Ollama:
ollama run hf.co/mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF
- Unsloth Studio new
How to use mudler/Qwopus3.6-35B-A3B-v1-APEX-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 mudler/Qwopus3.6-35B-A3B-v1-APEX-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 mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF to start chatting
- Pi new
How to use mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF
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": "mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use mudler/Qwopus3.6-35B-A3B-v1-APEX-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 mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF
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 mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF
Run Hermes
hermes
- Docker Model Runner
How to use mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF with Docker Model Runner:
docker model run hf.co/mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF
- Lemonade
How to use mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF
Run and chat with the model
lemonade run user.Qwopus3.6-35B-A3B-v1-APEX-GGUF-{{QUANT_TAG}}List all available models
lemonade list
will there be a MTP version?
to speed up with mtp
yes, totally. I'm following up llama.cpp upstream closely. Once that's merged I'll create an MTP version right away!
You can use the script I created to experience the MTP effect firsthand :)
I have tested it, and it can run on the APEX model.
https://www.modelscope.cn/models/HereIsMark/Qwen3.6-35B-A3B-MTP-Donor
yes, totally. I'm following up llama.cpp upstream closely. Once that's merged I'll create an MTP version right away!
Tons of MTP-refined models are popping up now. We’ve already pulled the branch locally and it’s stable. Reddit is buzzing with discussions. I’d recommend getting started with the new models right away—things are happening way too fast.
Really excited for the MTP version, @mudler ! Great to hear you're tracking the llama.cpp upstream so closely — that dedication shows in the quality of your work. This model is already fantastic, and with MTP support it's going to be even better. Keep it up, can't wait!
是的 非常期待您这款优秀模型的MTP版本, 还有谷歌模型的草稿版本
yes, totally. I'm following up llama.cpp upstream closely. Once that's merged I'll create an MTP version right away!
MTP has just been merged.