Instructions to use HelloSun/flint_cpu_opt 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 HelloSun/flint_cpu_opt 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 HelloSun/flint_cpu_opt:UD-Q4_K_XL # Run inference directly in the terminal: llama cli -hf HelloSun/flint_cpu_opt:UD-Q4_K_XL
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf HelloSun/flint_cpu_opt:UD-Q4_K_XL # Run inference directly in the terminal: llama cli -hf HelloSun/flint_cpu_opt:UD-Q4_K_XL
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf HelloSun/flint_cpu_opt:UD-Q4_K_XL # Run inference directly in the terminal: ./build/bin/llama cli -hf HelloSun/flint_cpu_opt:UD-Q4_K_XL
Use Docker
docker model run hf.co/HelloSun/flint_cpu_opt:UD-Q4_K_XL
- Llama new
- LM Studio
- Jan
- vLLM
How to use HelloSun/flint_cpu_opt with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "HelloSun/flint_cpu_opt" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "HelloSun/flint_cpu_opt", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/HelloSun/flint_cpu_opt:UD-Q4_K_XL
- Ollama
How to use HelloSun/flint_cpu_opt with Ollama:
ollama run hf.co/HelloSun/flint_cpu_opt:UD-Q4_K_XL
- Unsloth Desktop
- Pi
How to use HelloSun/flint_cpu_opt with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf HelloSun/flint_cpu_opt:UD-Q4_K_XL
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": "HelloSun/flint_cpu_opt:UD-Q4_K_XL" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use HelloSun/flint_cpu_opt with Docker Model Runner:
docker model run hf.co/HelloSun/flint_cpu_opt:UD-Q4_K_XL
- Lemonade
How to use HelloSun/flint_cpu_opt with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull HelloSun/flint_cpu_opt:UD-Q4_K_XL
Run and chat with the model
lemonade run user.flint_cpu_opt-UD-Q4_K_XL
List all available models
lemonade list
- Hermes Agent
How to use HelloSun/flint_cpu_opt with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf HelloSun/flint_cpu_opt:UD-Q4_K_XL
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 HelloSun/flint_cpu_opt:UD-Q4_K_XL
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use HelloSun/flint_cpu_opt with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf HelloSun/flint_cpu_opt:UD-Q4_K_XL
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 "HelloSun/flint_cpu_opt:UD-Q4_K_XL" \ --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"
Download benchmarks/nvfp4/summary.csv from HelloSun/flint_cpu_opt: direct link, hf CLI and curl.
- Browser
- Download file 756 Bytes
-
https://huggingface.co/HelloSun/flint_cpu_opt/resolve/main/benchmarks/nvfp4/summary.csv
- Command line
-
hf download hf://HelloSun/flint_cpu_opt/benchmarks/nvfp4/summary.csv
-
curl -L -o summary.csv https://huggingface.co/HelloSun/flint_cpu_opt/resolve/main/benchmarks/nvfp4/summary.csv
756 Bytes
| build,round,test,t_s | |
| stock,1,pp256,83.903 | |
| stock,1,pp2048,76.355 | |
| stock,1,tg128,14.123 | |
| stock,2,pp256,83.722 | |
| stock,2,pp2048,84.768 | |
| stock,2,tg128,32.324 | |
| stock,3,pp256,72.615 | |
| stock,3,pp2048,83.625 | |
| stock,3,tg128,30.604 | |
| patch_before,1,pp256,77.655 | |
| patch_before,1,pp2048,83.862 | |
| patch_before,1,tg128,32.042 | |
| patch_before,2,pp256,83.785 | |
| patch_before,2,pp2048,84.387 | |
| patch_before,2,tg128,31.764 | |
| patch_before,3,pp256,82.345 | |
| patch_before,3,pp2048,85.166 | |
| patch_before,3,tg128,30.796 | |
| patch_nvfp4_opt,1,pp256,153.081 | |
| patch_nvfp4_opt,1,pp2048,206.675 | |
| patch_nvfp4_opt,1,tg128,32.142 | |
| patch_nvfp4_opt,2,pp256,178.487 | |
| patch_nvfp4_opt,2,pp2048,218.632 | |
| patch_nvfp4_opt,2,tg128,29.835 | |
| patch_nvfp4_opt,3,pp256,181.638 | |
| patch_nvfp4_opt,3,pp2048,211.052 | |
| patch_nvfp4_opt,3,tg128,32.365 | |