Instructions to use michaelw9999/Qwopus3.6-27B-v2-MTP-NVFP4-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 michaelw9999/Qwopus3.6-27B-v2-MTP-NVFP4-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 michaelw9999/Qwopus3.6-27B-v2-MTP-NVFP4-GGUF:NVFP4 # Run inference directly in the terminal: llama cli -hf michaelw9999/Qwopus3.6-27B-v2-MTP-NVFP4-GGUF:NVFP4
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf michaelw9999/Qwopus3.6-27B-v2-MTP-NVFP4-GGUF:NVFP4 # Run inference directly in the terminal: llama cli -hf michaelw9999/Qwopus3.6-27B-v2-MTP-NVFP4-GGUF:NVFP4
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 michaelw9999/Qwopus3.6-27B-v2-MTP-NVFP4-GGUF:NVFP4 # Run inference directly in the terminal: ./llama-cli -hf michaelw9999/Qwopus3.6-27B-v2-MTP-NVFP4-GGUF:NVFP4
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 michaelw9999/Qwopus3.6-27B-v2-MTP-NVFP4-GGUF:NVFP4 # Run inference directly in the terminal: ./build/bin/llama-cli -hf michaelw9999/Qwopus3.6-27B-v2-MTP-NVFP4-GGUF:NVFP4
Use Docker
docker model run hf.co/michaelw9999/Qwopus3.6-27B-v2-MTP-NVFP4-GGUF:NVFP4
- LM Studio
- Jan
- Ollama
How to use michaelw9999/Qwopus3.6-27B-v2-MTP-NVFP4-GGUF with Ollama:
ollama run hf.co/michaelw9999/Qwopus3.6-27B-v2-MTP-NVFP4-GGUF:NVFP4
- Unsloth Desktop
- Pi
How to use michaelw9999/Qwopus3.6-27B-v2-MTP-NVFP4-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf michaelw9999/Qwopus3.6-27B-v2-MTP-NVFP4-GGUF:NVFP4
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "michaelw9999/Qwopus3.6-27B-v2-MTP-NVFP4-GGUF:NVFP4" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use michaelw9999/Qwopus3.6-27B-v2-MTP-NVFP4-GGUF with Docker Model Runner:
docker model run hf.co/michaelw9999/Qwopus3.6-27B-v2-MTP-NVFP4-GGUF:NVFP4
- Lemonade
How to use michaelw9999/Qwopus3.6-27B-v2-MTP-NVFP4-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull michaelw9999/Qwopus3.6-27B-v2-MTP-NVFP4-GGUF:NVFP4
Run and chat with the model
lemonade run user.Qwopus3.6-27B-v2-MTP-NVFP4-GGUF-NVFP4
List all available models
lemonade list
- Hermes Agent
How to use michaelw9999/Qwopus3.6-27B-v2-MTP-NVFP4-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 michaelw9999/Qwopus3.6-27B-v2-MTP-NVFP4-GGUF:NVFP4
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 michaelw9999/Qwopus3.6-27B-v2-MTP-NVFP4-GGUF:NVFP4
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use michaelw9999/Qwopus3.6-27B-v2-MTP-NVFP4-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf michaelw9999/Qwopus3.6-27B-v2-MTP-NVFP4-GGUF:NVFP4
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 "michaelw9999/Qwopus3.6-27B-v2-MTP-NVFP4-GGUF:NVFP4" \ --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"
Recommended parameters to run Llama CPP
#2
by jpmrblood - opened
Can you share how you run your model using your llama.cpp branch? Thanks
Just wanna say thank you for your model. This model is stable and fast using your forked llama.cpp MXFP6 NVFP4. Here's my current way running in single RTX 5090:
$LLAMA_CPP_HOME/build-v2/bin/llama-server \
-m "$MAIN_MODEL" \
--mmproj "$MMPROJ_MODEL" \
--no-mmproj-offload \
--image-min-tokens 1024 \
-fa on \
--kv-unified \
--no-ui \
-ctk q8_0 -ctv q8_0 \
--host 0.0.0.0 --port 8082 \
-ngl all \
-np 4 \
--no-mmap --mlock --jinja \
--no-host --metrics \
--log-timestamps --log-prefix -lv 3 \
--no-context-shift \
--reasoning on \
--chat-template-kwargs '{"preserve_thinking":true}' \
--temp 0.7 --top-k 20 --top-p 0.95 --min-p 0.05 --presence-penalty 0.1 --repeat-penalty 1.1