Text Generation
GGUF
English
Māori
llama.cpp
abteex-ai-labs
aotearoa
coder
coding
local-first
lumynax
Mixture of Experts
new-zealand
sovereign-ai
starcoder
vllm
vllm-compatible
vllm-experimental
nvidia-nim
nim-compatible
nim-candidate
nvidia-nemo
nem
nvidia-nemo-pathway
nem-pathway
nem-convert-required
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 Settings
- 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
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
File size: 2,595 Bytes
c53b16e | 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 | """
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()
|