Instructions to use mgonzs13/SpaceOm-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use mgonzs13/SpaceOm-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 mgonzs13/SpaceOm-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf mgonzs13/SpaceOm-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf mgonzs13/SpaceOm-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf mgonzs13/SpaceOm-GGUF: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 mgonzs13/SpaceOm-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf mgonzs13/SpaceOm-GGUF: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 mgonzs13/SpaceOm-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf mgonzs13/SpaceOm-GGUF:Q4_K_M

Use Docker

docker model run hf.co/mgonzs13/SpaceOm-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use mgonzs13/SpaceOm-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "mgonzs13/SpaceOm-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mgonzs13/SpaceOm-GGUF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/mgonzs13/SpaceOm-GGUF:Q4_K_M

Ollama
How to use mgonzs13/SpaceOm-GGUF with Ollama:
```
ollama run hf.co/mgonzs13/SpaceOm-GGUF:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use mgonzs13/SpaceOm-GGUF with Docker Model Runner:
```
docker model run hf.co/mgonzs13/SpaceOm-GGUF:Q4_K_M
```

Lemonade

How to use mgonzs13/SpaceOm-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull mgonzs13/SpaceOm-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.SpaceOm-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

Improve model card: Add paper and benchmark GitHub links

by nielsr HF Staff - opened Jul 15, 2025

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

+26

-204

nielsr

Jul 15, 2025

Hi there!

This PR improves the model card for SpaceOm by enhancing its connection to the research paper and related code:

Adds the paper: 2506.07966 metadata tag to link the model directly to the SpaCE-10: A Comprehensive Benchmark for Multimodal Large Language Models in Compositional Spatial Intelligence paper on the Hugging Face Hub, improving discoverability.
Adds a prominent link to the SpaCE-10 paper and its associated GitHub repository (https://github.com/Cuzyoung/SpaCE-10) at the top of the model card content. This provides immediate context about the model's evaluation benchmark.

These changes help researchers and users quickly understand the model's origin and the context of its performance on the SpaCE-10 benchmark.

Improve model card: Add paper and benchmark GitHub links5c3a0db3

mgonzs13 changed pull request status to merged Jul 15, 2025

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