Text Generation
GGUF
English
Māori
llama.cpp
abteex-ai-labs
aotearoa
coder
coding
local-first
lumynax
Mixture of Experts
new-zealand
sovereign-ai
imatrix
conversational
Instructions to use AbteeXAILab/lumynax-coder-starcoder2-15b-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use AbteeXAILab/lumynax-coder-starcoder2-15b-gguf with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="AbteeXAILab/lumynax-coder-starcoder2-15b-gguf", filename="starcoder2-15b-instruct-v0.1-Q4_K_M.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use AbteeXAILab/lumynax-coder-starcoder2-15b-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-coder-starcoder2-15b-gguf:Q4_K_M # Run inference directly in the terminal: llama-cli -hf AbteeXAILab/lumynax-coder-starcoder2-15b-gguf:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf AbteeXAILab/lumynax-coder-starcoder2-15b-gguf:Q4_K_M # Run inference directly in the terminal: llama-cli -hf AbteeXAILab/lumynax-coder-starcoder2-15b-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 AbteeXAILab/lumynax-coder-starcoder2-15b-gguf:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf AbteeXAILab/lumynax-coder-starcoder2-15b-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 AbteeXAILab/lumynax-coder-starcoder2-15b-gguf:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf AbteeXAILab/lumynax-coder-starcoder2-15b-gguf:Q4_K_M
Use Docker
docker model run hf.co/AbteeXAILab/lumynax-coder-starcoder2-15b-gguf:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use AbteeXAILab/lumynax-coder-starcoder2-15b-gguf with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "AbteeXAILab/lumynax-coder-starcoder2-15b-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-coder-starcoder2-15b-gguf", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/AbteeXAILab/lumynax-coder-starcoder2-15b-gguf:Q4_K_M
- Ollama
How to use AbteeXAILab/lumynax-coder-starcoder2-15b-gguf with Ollama:
ollama run hf.co/AbteeXAILab/lumynax-coder-starcoder2-15b-gguf:Q4_K_M
- Unsloth Studio new
How to use AbteeXAILab/lumynax-coder-starcoder2-15b-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-coder-starcoder2-15b-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-coder-starcoder2-15b-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-coder-starcoder2-15b-gguf to start chatting
- Docker Model Runner
How to use AbteeXAILab/lumynax-coder-starcoder2-15b-gguf with Docker Model Runner:
docker model run hf.co/AbteeXAILab/lumynax-coder-starcoder2-15b-gguf:Q4_K_M
- Lemonade
How to use AbteeXAILab/lumynax-coder-starcoder2-15b-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull AbteeXAILab/lumynax-coder-starcoder2-15b-gguf:Q4_K_M
Run and chat with the model
lemonade run user.lumynax-coder-starcoder2-15b-gguf-Q4_K_M
List all available models
lemonade list
feat: initial LumynaX scaffold (card v6 + quickstart + manifest + Modelfile + Space scaffold)
c53b16e verified | """ | |
| LumynaX Coder StarCoder2 15B Instruct GGUF — LumynaX quickstart. | |
| This script fetches the upstream model from Hugging Face and runs a short | |
| LumynaX-flavoured prompt. Run it on a host that satisfies the resource budget | |
| documented in the README (LumynaX Coder StarCoder2 15B Instruct GGUF). | |
| Usage: | |
| python quickstart.py # one-shot demo prompt | |
| python quickstart.py --interactive # REPL | |
| python quickstart.py --gguf # use the GGUF mirror via llama-cpp | |
| LumynaX package repo: https://huggingface.co/AbteeXAILab/lumynax-coder-starcoder2-15b-gguf | |
| Upstream weights: https://huggingface.co/bigcode/starcoder2-15b-instruct-v0.1 | |
| """ | |
| from __future__ import annotations | |
| import argparse, os, sys | |
| LUMYNAX_SYSTEM = ( | |
| "You are LumynaX, the AbteeX AI Labs assistant from Aotearoa New Zealand. " | |
| "Ko te marama te tuapapa - the light is the foundation. " | |
| "Answer with care, cite uncertainty, and prefer local-first reasoning. " | |
| "Refuse unsafe, unlawful, or sovereignty-violating requests." | |
| ) | |
| DEMO_PROMPT = "Explain in 3 bullets why local-first AI matters for Aotearoa New Zealand." | |
| def _run_gguf(prompt: str, interactive: bool): | |
| from llama_cpp import Llama | |
| print("[lumynax] Loading GGUF from bartowski/starcoder2-15b-instruct-v0.1-GGUF (this can be large)...") | |
| llm = Llama.from_pretrained( | |
| repo_id="bartowski/starcoder2-15b-instruct-v0.1-GGUF", | |
| filename="starcoder2-15b-instruct-v0.1-Q4_K_M.gguf", | |
| n_ctx=16384, | |
| n_gpu_layers=int(os.environ.get("N_GPU_LAYERS", "-1")), | |
| verbose=False, | |
| ) | |
| def chat(user): | |
| out = llm.create_chat_completion(messages=[ | |
| {"role": "system", "content": LUMYNAX_SYSTEM}, | |
| {"role": "user", "content": user}, | |
| ], max_tokens=512, temperature=0.4) | |
| return out["choices"][0]["message"]["content"] | |
| if interactive: | |
| print("[lumynax] interactive mode — empty line exits.") | |
| while True: | |
| try: q = input("you> ").strip() | |
| except EOFError: break | |
| if not q: break | |
| print("lumynax> " + chat(q)) | |
| else: | |
| print(chat(prompt)) | |
| def main(): | |
| p = argparse.ArgumentParser() | |
| p.add_argument("--interactive", action="store_true") | |
| p.add_argument("--prompt", default=DEMO_PROMPT) | |
| p.add_argument("--gguf", action="store_true", help="kept for compatibility — this build is GGUF-only") | |
| args = p.parse_args() | |
| _run_gguf(args.prompt, args.interactive) | |
| if __name__ == "__main__": | |
| main() | |