Instructions to use ArliAI/QwQ-32B-ArliAI-RpR-v1-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 ArliAI/QwQ-32B-ArliAI-RpR-v1-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 ArliAI/QwQ-32B-ArliAI-RpR-v1-GGUF:Q4_K_S # Run inference directly in the terminal: llama cli -hf ArliAI/QwQ-32B-ArliAI-RpR-v1-GGUF:Q4_K_S
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf ArliAI/QwQ-32B-ArliAI-RpR-v1-GGUF:Q4_K_S # Run inference directly in the terminal: llama cli -hf ArliAI/QwQ-32B-ArliAI-RpR-v1-GGUF:Q4_K_S
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 ArliAI/QwQ-32B-ArliAI-RpR-v1-GGUF:Q4_K_S # Run inference directly in the terminal: ./llama-cli -hf ArliAI/QwQ-32B-ArliAI-RpR-v1-GGUF:Q4_K_S
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 ArliAI/QwQ-32B-ArliAI-RpR-v1-GGUF:Q4_K_S # Run inference directly in the terminal: ./build/bin/llama-cli -hf ArliAI/QwQ-32B-ArliAI-RpR-v1-GGUF:Q4_K_S
Use Docker
docker model run hf.co/ArliAI/QwQ-32B-ArliAI-RpR-v1-GGUF:Q4_K_S
- LM Studio
- Jan
- Ollama
How to use ArliAI/QwQ-32B-ArliAI-RpR-v1-GGUF with Ollama:
ollama run hf.co/ArliAI/QwQ-32B-ArliAI-RpR-v1-GGUF:Q4_K_S
- Unsloth Studio
How to use ArliAI/QwQ-32B-ArliAI-RpR-v1-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 ArliAI/QwQ-32B-ArliAI-RpR-v1-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 ArliAI/QwQ-32B-ArliAI-RpR-v1-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for ArliAI/QwQ-32B-ArliAI-RpR-v1-GGUF to start chatting
- Pi
How to use ArliAI/QwQ-32B-ArliAI-RpR-v1-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf ArliAI/QwQ-32B-ArliAI-RpR-v1-GGUF:Q4_K_S
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": "ArliAI/QwQ-32B-ArliAI-RpR-v1-GGUF:Q4_K_S" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use ArliAI/QwQ-32B-ArliAI-RpR-v1-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 ArliAI/QwQ-32B-ArliAI-RpR-v1-GGUF:Q4_K_S
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 ArliAI/QwQ-32B-ArliAI-RpR-v1-GGUF:Q4_K_S
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use ArliAI/QwQ-32B-ArliAI-RpR-v1-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf ArliAI/QwQ-32B-ArliAI-RpR-v1-GGUF:Q4_K_S
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 "ArliAI/QwQ-32B-ArliAI-RpR-v1-GGUF:Q4_K_S" \ --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"
- Docker Model Runner
How to use ArliAI/QwQ-32B-ArliAI-RpR-v1-GGUF with Docker Model Runner:
docker model run hf.co/ArliAI/QwQ-32B-ArliAI-RpR-v1-GGUF:Q4_K_S
- Lemonade
How to use ArliAI/QwQ-32B-ArliAI-RpR-v1-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ArliAI/QwQ-32B-ArliAI-RpR-v1-GGUF:Q4_K_S
Run and chat with the model
lemonade run user.QwQ-32B-ArliAI-RpR-v1-GGUF-Q4_K_S
List all available models
lemonade list
story telling
Hi, I am trying to write my story ideas and scattered short stories into a long story, and I admire people like you in the open-source community. Freedom of information and resources is important, so thank you so much for the important work you are doing.
Could you make a story-writing LLM based on this model that can roleplay instead of the user as well?
like we give the outline in the system prompt and then when it is the users turn to rp thenthe llm itself answer it in a way that in service of the goal of the story and guide it to the end we are want and use the outline as a guide, I like this model so much, it has much better natural story writing capabilities,
I live in a country that has bad internet, censorship, and I can't use claude's free tire, it dose not give its services to my country, and I cant pay for any online services for several reasons, and the English is not my first language, but I love writing and want to take it to new level so everyone can enjoy my writing,
If you can't do it, I still thank you ^^