Text Generation
GGUF
llama.cpp
qwen3
cpu-inference
ssd-offload
ssd-streaming
low-memory
conversational
Instructions to use HelloSun/qwen3-0.6b-ssd-streaming 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/qwen3-0.6b-ssd-streaming 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/qwen3-0.6b-ssd-streaming:Q8_0 # Run inference directly in the terminal: llama cli -hf HelloSun/qwen3-0.6b-ssd-streaming:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf HelloSun/qwen3-0.6b-ssd-streaming:Q8_0 # Run inference directly in the terminal: llama cli -hf HelloSun/qwen3-0.6b-ssd-streaming:Q8_0
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 HelloSun/qwen3-0.6b-ssd-streaming:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf HelloSun/qwen3-0.6b-ssd-streaming:Q8_0
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 HelloSun/qwen3-0.6b-ssd-streaming:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf HelloSun/qwen3-0.6b-ssd-streaming:Q8_0
Use Docker
docker model run hf.co/HelloSun/qwen3-0.6b-ssd-streaming:Q8_0
- LM Studio
- Jan
- vLLM
How to use HelloSun/qwen3-0.6b-ssd-streaming with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "HelloSun/qwen3-0.6b-ssd-streaming" # 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/qwen3-0.6b-ssd-streaming", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/HelloSun/qwen3-0.6b-ssd-streaming:Q8_0
- Ollama
How to use HelloSun/qwen3-0.6b-ssd-streaming with Ollama:
ollama run hf.co/HelloSun/qwen3-0.6b-ssd-streaming:Q8_0
- Unsloth Desktop
- Pi
How to use HelloSun/qwen3-0.6b-ssd-streaming with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf HelloSun/qwen3-0.6b-ssd-streaming:Q8_0
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/qwen3-0.6b-ssd-streaming:Q8_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use HelloSun/qwen3-0.6b-ssd-streaming with Docker Model Runner:
docker model run hf.co/HelloSun/qwen3-0.6b-ssd-streaming:Q8_0
- Lemonade
How to use HelloSun/qwen3-0.6b-ssd-streaming with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull HelloSun/qwen3-0.6b-ssd-streaming:Q8_0
Run and chat with the model
lemonade run user.qwen3-0.6b-ssd-streaming-Q8_0
List all available models
lemonade list
- Hermes Agent
How to use HelloSun/qwen3-0.6b-ssd-streaming 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/qwen3-0.6b-ssd-streaming:Q8_0
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/qwen3-0.6b-ssd-streaming:Q8_0
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use HelloSun/qwen3-0.6b-ssd-streaming with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf HelloSun/qwen3-0.6b-ssd-streaming:Q8_0
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/qwen3-0.6b-ssd-streaming:Q8_0" \ --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"
File size: 2,658 Bytes
26012bf | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 | {
"sample_interval_seconds": 0.1,
"sample_count": 14,
"peak_rss_bytes": 713650176,
"peak_rss_mib": 680.59,
"peak_metric": "max(smaps_rollup.Rss, VmHWM)",
"peak_anon_bytes": 60903424,
"peak_process_swap_bytes": 0,
"all_process_swap_samples_zero": true,
"memory_limit_gib": 1.0,
"within_memory_limit": true,
"samples": [
{
"time_unix": 1791188400,
"VmHWM": 1458176,
"VmRSS": 1458176,
"VmSwap": 0,
"Rss": 1789952,
"Anonymous": 159744
},
{
"time_unix": 1791188400,
"VmHWM": 35917824,
"VmRSS": 35917824,
"VmSwap": 0,
"Rss": 35917824,
"Anonymous": 22663168
},
{
"time_unix": 1791188401,
"VmHWM": 39743488,
"VmRSS": 39743488,
"VmSwap": 0,
"Rss": 40239104,
"Anonymous": 26787840
},
{
"time_unix": 1791188401,
"VmHWM": 67735552,
"VmRSS": 67735552,
"VmSwap": 0,
"Rss": 67735552,
"Anonymous": 54153216
},
{
"time_unix": 1791188401,
"VmHWM": 72695808,
"VmRSS": 72695808,
"VmSwap": 0,
"Rss": 72695808,
"Anonymous": 59047936
},
{
"time_unix": 1791188401,
"VmHWM": 124624896,
"VmRSS": 124624896,
"VmSwap": 0,
"Rss": 126427136,
"Anonymous": 54571008
},
{
"time_unix": 1791188401,
"VmHWM": 344309760,
"VmRSS": 271564800,
"VmSwap": 0,
"Rss": 249901056,
"Anonymous": 56467456
},
{
"time_unix": 1791188401,
"VmHWM": 344309760,
"VmRSS": 89395200,
"VmSwap": 0,
"Rss": 89395200,
"Anonymous": 56913920
},
{
"time_unix": 1791188401,
"VmHWM": 344309760,
"VmRSS": 89395200,
"VmSwap": 0,
"Rss": 89395200,
"Anonymous": 56913920
},
{
"time_unix": 1791188401,
"VmHWM": 344309760,
"VmRSS": 89395200,
"VmSwap": 0,
"Rss": 89395200,
"Anonymous": 56913920
},
{
"time_unix": 1791188401,
"VmHWM": 344309760,
"VmRSS": 121397248,
"VmSwap": 0,
"Rss": 128864256,
"Anonymous": 59080704
},
{
"time_unix": 1791188402,
"VmHWM": 344309760,
"VmRSS": 243027968,
"VmSwap": 0,
"Rss": 314331136,
"Anonymous": 60903424
},
{
"time_unix": 1791188402,
"VmHWM": 708186112,
"VmRSS": 537792512,
"VmSwap": 0,
"Rss": 712339456,
"Anonymous": 60903424
},
{
"time_unix": 1791188402,
"VmHWM": 708186112,
"VmRSS": 634343424,
"VmSwap": 0,
"Rss": 713650176,
"Anonymous": 60903424
}
]
}
|