---
license: apache-2.0
license_link: https://huggingface.co/Qwen/Qwen3-1.7B-GGUF
library_name: llama-cpp-python
pipeline_tag: text-generation
language:
- en
- mi
tags:
- lumynax
- lumynax-infused-qwen3-17b-gguf
- qwen3-1-7b
- gguf
- llama-cpp
- abteex-ai-labs
- local-first
---
# LumynaX Infused Qwen3 1.7B GGUF

LumynaX Infused Qwen3 1.7B GGUF is a Hugging Face-ready LumynaX GGUF release package. It wraps a
prebuilt GGUF artifact for local `llama.cpp`, `llama-cpp-python`, Ollama, LM
Studio, Jan, or compatible GGUF runtimes.

## Provenance

- upstream base model: `Qwen/Qwen3-1.7B`
- source GGUF repo: `Qwen/Qwen3-1.7B-GGUF`
- packaged GGUF file: `Qwen3-1.7B-Q8_0.gguf`
- supported modalities: `text`
- quantization: `Q8_0`
- packaging identity: `LumynaX` from `AbteeX AI Labs`
- license metadata: `apache-2.0`
- weight claim: this release packages the referenced GGUF artifact and does not claim a private weight merge

## Quick Start

```bash
pip install -r requirements.txt
python quickstart.py --interactive
python quickstart.py --prompt "Say hello in one short sentence."
```

To use the bundled llama.cpp fallback directly:

```bash
python quickstart.py --llama-cli C:\path\to\llama-cli.exe --prompt "Say hello."
```


## Ollama

```bash
cd ollama
powershell -NoProfile -ExecutionPolicy Bypass -File ./create_ollama_model.ps1
ollama run lumynax-infused-qwen3-17b-gguf
```

## Included Files

- `Qwen3-1.7B-Q8_0.gguf`: primary GGUF model artifact
- `quickstart.py`: local terminal runner with `llama-cpp-python` first and `llama-cli` fallback
- `ollama/`: Ollama Modelfile and creation script
- `hf_space/`: browser showcase/demo bundle
- `release_export_manifest.json`: package metadata and runtime defaults
- `checksums.sha256`: release integrity manifest

## Publisher

- organization / lab: `AbteeX AI Labs`
- website: `https://abteex.com`
- Hugging Face owner account: `AbteeXAILab`
- recommended model repo: `AbteeXAILab/lumynax-infused-qwen3-17b-gguf`
- recommended local model name: `lumynax-infused-qwen3-17b-gguf`

<!-- lumynax-public-release-block:v2 -->

## LumynaX Infusion Identity

This is a public LumynaX release package from AbteeX AI Labs for local-first inference.
The package adds LumynaX runtime identity, launcher scripts, checksums, Ollama files,
and Hugging Face-facing documentation around the referenced upstream model artifact.

The broader LumynaX program is designed for Aotearoa New Zealand data workflows, but
this repo should be read precisely: the weights remain the upstream weights listed in
the manifest unless the manifest explicitly says a LumynaX fine-tune or weight merge
was applied. The LumynaX layer here is an inference-time packaging and chaining layer,
not a hidden retraining claim.

## Download And Run

Clone the full repo so the GGUF, quickstart, checksums, and Ollama files stay together:

```bash
git lfs install
git clone https://huggingface.co/AbteeXAILab/lumynax-infused-qwen3-17b-gguf
cd lumynax-infused-qwen3-17b-gguf
pip install -r requirements.txt
python quickstart.py --llama-cli /path/to/llama-cli --prompt "Say hello in one short sentence."
```

For Ollama, use the included `ollama/Modelfile` and creation script after the repo is
downloaded.

## Runtime Components

- `README.md`: this model card and release instructions
- `quickstart.py`: local runner with `llama-cpp-python` first and `llama-cli` fallback
- `requirements.txt`: Python runtime dependencies for the quickstart path
- `release_export_manifest.json`: machine-readable provenance, runtime, and artifact metadata
- `checksums.sha256`: integrity hashes for the shipped files
- `ollama/`: Ollama packaging files
- `hf_space/`: lightweight Hugging Face Space scaffold
- packaged source: `Qwen/Qwen3-1.7B-GGUF`
- upstream base model: `Qwen/Qwen3-1.7B`
- supported modalities: `text`
- license metadata: `apache-2.0`

## Smoke Status

Bundled `quickstart.py` completed a local llama.cpp smoke test on this workstation at `2026-05-10T12:59:39.815418+00:00`.

Hardware still matters. Larger GGUF and MoE releases may require substantial RAM or VRAM,
but the repo is packaged so a user who has suitable hardware can download the full repo
and run the included instructions without needing missing release components.