---
license: other
base_model: Qwen/Qwen2.5-0.5B-Instruct
language:
- ko
pipeline_tag: text-generation
tags:
- korean
- knowledge-graph
- qlora
- sft
- local-factual-data
---

# AIWORKX-KR-KG-Reasoner-0.5B-v0.10

## Overview

AIWORKX-KR-KG-Reasoner-0.5B-v0.10 is a small Korean-specialized language model fine-tuned from `Qwen/Qwen2.5-0.5B-Instruct`.

This model was created as a local MVP for K-AI leaderboard submission experiments. The training pipeline uses copyright-safe structured factual triples, converts them into a local knowledge graph, and generates Korean supervised fine-tuning data through deterministic rule-based templates.

## Base Model

- Base model: `Qwen/Qwen2.5-0.5B-Instruct`
- Fine-tuning method: QLoRA supervised fine-tuning
- Adapter merge: LoRA adapter merged into the base model

## Training Data

The training data was generated from local structured factual triples.

Pipeline:

1. Local factual triples
2. Knowledge graph nodes, edges, and evidence units
3. Rule-based Korean QA generation
4. SFT JSONL conversion
5. QLoRA fine-tuning

No OpenAI API, paid API, live external API, or web crawling was used in this MVP.

## Data Policy

The dataset uses structured factual triples rather than copied prose. The project is designed around copyright-safe factual data and knowledge-graph-based training.

## Intended Use

- Korean factual QA
- Knowledge-graph-grounded QA
- Triple-to-text generation
- Evidence-based relation extraction
- Small-scale K-AI leaderboard submission experiment

## Limitations

This is a small experimental model trained on a very small dataset. It may overfit to the rule-based format and may not perform well on broad open-domain tasks. It should not be used for high-stakes decisions.

## Version

- Version: 0.10
- Project motto: Copyright-safe factual data + Knowledge Graph + Local QLoRA