Instructions to use Nexuss0781/SPACE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use Nexuss0781/SPACE 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 Nexuss0781/SPACE:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Nexuss0781/SPACE:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Nexuss0781/SPACE:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Nexuss0781/SPACE:Q4_K_M

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 Nexuss0781/SPACE:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Nexuss0781/SPACE:Q4_K_M

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 Nexuss0781/SPACE:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Nexuss0781/SPACE:Q4_K_M

Use Docker

docker model run hf.co/Nexuss0781/SPACE:Q4_K_M

LM Studio
Jan

vLLM

How to use Nexuss0781/SPACE with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Nexuss0781/SPACE"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Nexuss0781/SPACE",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/Nexuss0781/SPACE:Q4_K_M

Ollama
How to use Nexuss0781/SPACE with Ollama:
```
ollama run hf.co/Nexuss0781/SPACE:Q4_K_M
```
Unsloth Desktop

How to use Nexuss0781/SPACE with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Nexuss0781/SPACE:Q4_K_M

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": "Nexuss0781/SPACE:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use Nexuss0781/SPACE with Docker Model Runner:
```
docker model run hf.co/Nexuss0781/SPACE:Q4_K_M
```

Lemonade

How to use Nexuss0781/SPACE with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Nexuss0781/SPACE:Q4_K_M

Run and chat with the model

lemonade run user.SPACE-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use Nexuss0781/SPACE with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Nexuss0781/SPACE:Q4_K_M

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 Nexuss0781/SPACE:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use Nexuss0781/SPACE with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Nexuss0781/SPACE:Q4_K_M

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 "Nexuss0781/SPACE:Q4_K_M" \
  --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"

SPACE

Text (10 prompts, 256 max new tokens)

Model	Weights	Avg tok/s	Peak RSS	Wall (10 prompts)
SmolLM2-360M-Instruct (q4_k_m)	0.27 GB	57.73	474 MB	37.7s
SmolLM3-3B (q4_k_m)	1.92 GB	13.18	3,436 MB	196.6s
Qwen2.5-3B-Instruct (q4_k_m)	1.93 GB	13.43	3,336 MB	161.6s

Vision (10 image tasks, 128 max new tokens)

Model	Weights	Avg tok/s	Peak RSS	Wall (10 imgs)
SmolVLM2-500M-Video-Instruct (q8_0)	0.44 GB	67.15	1,026 MB	73.7s
SmolVLM-500M-Instruct (q8_0)	0.44 GB	65.06	1,026 MB	77.6s
SmolVLM2-2.2B-Instruct (q4_k_m)	1.11 GB	19.15	4,260 MB	363.3s
Moondream2 (q8_0)	1.51 GB	14.86	4,000 MB	236.1s
Gemma 3 4B IT (q4_k_m)	2.49 GB	13.19	5,309 MB	602.6s

Audio (10 speech clips, 128 max new tokens)

Model	Weights	Avg tok/s	Peak RSS	Wall (10 clips)
Qwen3-ASR-0.6B (q8_0)	0.80 GB	37.17	2,073 MB	24.1s
Ultravox 1B (q4_k_m)	0.81 GB	35.68	2,969 MB	209.2s
Qwen2.5-Omni-3B (q4_k_m)	2.10 GB	15.90	6,302 MB	435.4s
Qwen3-ASR-1.7B (q8_0)	2.17 GB	12.68	3,510 MB	45.6s
Ultravox 8B (q4_k_m)	4.92 GB	7.34	10,456 MB	448.1s

Selected

Modality	Micro (always-on)	Quality
Text	SmolLM2-360M-Instruct (q4_k_m, 57.7 tok/s)	Qwen2.5-3B-Instruct (q4_k_m, 13.4 tok/s)
Vision	SmolVLM2-500M-Video-Instruct (q8_0, 67.2 tok/s)	SmolVLM2-2.2B-Instruct (q4_k_m, 19.2 tok/s)
Audio	Qwen3-ASR-0.6B (q8_0, 37.2 tok/s)	Qwen3-ASR-1.7B (q8_0, 12.7 tok/s)

Downloads last month: 49

GGUF

Model size

3B params

Architecture

qwen2

Hardware compatibility

4-bit

8-bit