Text Generation
GGUF
English
Māori
llama.cpp
abteex-ai-labs
aotearoa
general
local-first
lumynax
new-zealand
smollm
sovereign-ai
text
vllm
vllm-compatible
vllm-experimental
nvidia-nim
nim-compatible
nim-candidate
nvidia-nemo
nem
nvidia-nemo-pathway
nem-pathway
nem-convert-required
conversational
Instructions to use AbteeXAILab/lumynax-infused-smollm2-360m-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use AbteeXAILab/lumynax-infused-smollm2-360m-gguf with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="AbteeXAILab/lumynax-infused-smollm2-360m-gguf", filename="smollm2-360m-instruct-q8_0.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use AbteeXAILab/lumynax-infused-smollm2-360m-gguf with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf AbteeXAILab/lumynax-infused-smollm2-360m-gguf:Q8_0 # Run inference directly in the terminal: llama-cli -hf AbteeXAILab/lumynax-infused-smollm2-360m-gguf:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf AbteeXAILab/lumynax-infused-smollm2-360m-gguf:Q8_0 # Run inference directly in the terminal: llama-cli -hf AbteeXAILab/lumynax-infused-smollm2-360m-gguf: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 AbteeXAILab/lumynax-infused-smollm2-360m-gguf:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf AbteeXAILab/lumynax-infused-smollm2-360m-gguf: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 AbteeXAILab/lumynax-infused-smollm2-360m-gguf:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf AbteeXAILab/lumynax-infused-smollm2-360m-gguf:Q8_0
Use Docker
docker model run hf.co/AbteeXAILab/lumynax-infused-smollm2-360m-gguf:Q8_0
- LM Studio
- Jan
- vLLM
How to use AbteeXAILab/lumynax-infused-smollm2-360m-gguf with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "AbteeXAILab/lumynax-infused-smollm2-360m-gguf" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AbteeXAILab/lumynax-infused-smollm2-360m-gguf", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/AbteeXAILab/lumynax-infused-smollm2-360m-gguf:Q8_0
- Ollama
How to use AbteeXAILab/lumynax-infused-smollm2-360m-gguf with Ollama:
ollama run hf.co/AbteeXAILab/lumynax-infused-smollm2-360m-gguf:Q8_0
- Unsloth Studio
How to use AbteeXAILab/lumynax-infused-smollm2-360m-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 AbteeXAILab/lumynax-infused-smollm2-360m-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 AbteeXAILab/lumynax-infused-smollm2-360m-gguf to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for AbteeXAILab/lumynax-infused-smollm2-360m-gguf to start chatting
- Atomic Chat new
- Docker Model Runner
How to use AbteeXAILab/lumynax-infused-smollm2-360m-gguf with Docker Model Runner:
docker model run hf.co/AbteeXAILab/lumynax-infused-smollm2-360m-gguf:Q8_0
- Lemonade
How to use AbteeXAILab/lumynax-infused-smollm2-360m-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull AbteeXAILab/lumynax-infused-smollm2-360m-gguf:Q8_0
Run and chat with the model
lemonade run user.lumynax-infused-smollm2-360m-gguf-Q8_0
List all available models
lemonade list
| { | |
| "command": [ | |
| "C:\\Users\\ijadimaa\\AppData\\Local\\Programs\\Python\\Python311\\python.exe", | |
| "C:\\Users\\ijadimaa\\AppData\\Local\\tinyluminax\\batch-gguf-releases\\lumynax-infused-smollm2-360m-gguf-v1\\quickstart.py", | |
| "--llama-cli", | |
| "\\\\waikato\\users\\Hamilton\\GtoLdtop\\ijadimaa\\Desktop\\Startup\\TinyLuminaX\\tools\\llama.cpp-prebuilt\\llama-cli.exe", | |
| "--prompt", | |
| "Reply with exactly: OK", | |
| "--max-new-tokens", | |
| "16", | |
| "--ctx-size", | |
| "256", | |
| "--temperature", | |
| "0", | |
| "--threads", | |
| "6" | |
| ], | |
| "elapsed_seconds": 5.812, | |
| "generated_at": "2026-05-10T13:28:15.168896+00:00", | |
| "returncode": 0, | |
| "status": "pass", | |
| "stderr_tail": "", | |
| "stdout_tail": "Loading model... \n\n\n\u2584\u2584 \u2584\u2584\n\u2588\u2588 \u2588\u2588\n\u2588\u2588 \u2588\u2588 \u2580\u2580\u2588\u2584 \u2588\u2588\u2588\u2584\u2588\u2588\u2588\u2584 \u2580\u2580\u2588\u2584 \u2584\u2588\u2588\u2588\u2588 \u2588\u2588\u2588\u2588\u2584 \u2588\u2588\u2588\u2588\u2584\n\u2588\u2588 \u2588\u2588 \u2584\u2588\u2580\u2588\u2588 \u2588\u2588 \u2588\u2588 \u2588\u2588 \u2584\u2588\u2580\u2588\u2588 \u2588\u2588 \u2588\u2588 \u2588\u2588 \u2588\u2588 \u2588\u2588\n\u2588\u2588 \u2588\u2588 \u2580\u2588\u2584\u2588\u2588 \u2588\u2588 \u2588\u2588 \u2588\u2588 \u2580\u2588\u2584\u2588\u2588 \u2588\u2588 \u2580\u2588\u2588\u2588\u2588 \u2588\u2588\u2588\u2588\u2580 \u2588\u2588\u2588\u2588\u2580\n \u2588\u2588 \u2588\u2588\n \u2580\u2580 \u2580\u2580\n\nbuild : b8840-9e5647aff\nmodel : smollm2-360m-instruct-q8_0.gguf\nmodalities : text\nusing custom system prompt\n\navailable commands:\n /exit or Ctrl+C stop or exit\n /regen regenerate the last response\n /clear clear the chat history\n /read <file> add a text file\n /glob <pattern> add text files using globbing pattern\n\n\n> Reply with exactly: OK\n\nI'm sorry for the misunderstanding, but as an AI, I don't have\n\n[ Prompt: 140.7 t/s | Generation: 86.3 t/s ]\n\nExiting...\n", | |
| "timeout_seconds": 240 | |
| } |