---
library_name: gguf
pipeline_tag: text-generation
base_model: Qwen/Qwen2.5-Coder-3B-Instruct
license: apache-2.0
tags:
- gguf
- q4_k_m
- qwen2.5-coder
- code
- stem
- kotlin
- unity
- python
model-index:
- name: Luck-Qwen2.5-Coder-3B-STEM
  results: []
---

# Luck-Qwen2.5-Coder-3B-STEM (GGUF Q4_K_M)

A fine-tuned version of **Qwen2.5-Coder-3B-Instruct** specialized in STEM and code-related tasks. This model has been trained on a curated mix of code, mathematics, and development-focused datasets with emphasis on Python, Kotlin, Unity (C#), and mathematical reasoning.

## ⚠️ Important Notice

This is an **experimental fine-tune**. While the model shows improvements in certain STEM domains, it has known limitations:

- May occasionally enter repetition loops on complex prompts
- Can produce verbose responses with unnecessary explanations
- HTML/JS generation quality is lower than the base model
- Best used with `temperature=0.2` and `max_new_tokens=512` for stable outputs

For production use, we recommend the original [Qwen/Qwen2.5-Coder-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-3B-Instruct).

## Model Details

- **Base Model:** Qwen2.5-Coder-3B-Instruct
- **Training Steps:** 1,500
- **Quantization:** Q4_K_M (~2.0 GB)
- **Format:** GGUF
- **Training Framework:** Unsloth + PEFT (LoRA)
- **Target Languages:** Python, Kotlin, C# (Unity), JavaScript, SQL

## Training Data Mix

| Dataset | Samples | Domain |
|---------|---------|--------|
| saurabh5/rlvr-code-data-Kotlin | 2,500 | Kotlin |
| ise-uiuc/Magicoder-Evol-Instruct-110K | 4,000 | Code Instruct |
| theblackcat102/evol-codealpaca-v1 | 2,500 | Code Alpaca |
| vishnuOI/unity-dev-instructions | 2,500 | Unity/C# |
| bigcode/python-stack-v1-functions-filtered-sc2 | 1,500 | Python |
| ryanmarten/OpenThoughts-1k-sample | 500 | Reasoning |
| TIGER-Lab/MathInstruct | 1,500 | Mathematics |

## Quick Start with Ollama

### 1. Download the model

```bash
huggingface-cli download ahmetggg/Luck-Qwen2.5-Coder-3B-STEM-GGUF --include "*.gguf" --local-dir ./models