---
license: gfdl
language:
- es
- en
base_model:
- Qwen/Qwen2.5-Coder-7B-Instruct
tags:
- gguf
- unity
- csharp
- code
---
# Pygenesis Unity GGUF (Qwen 2.5 Coder Fine-Tuned)

**Pygenesis Unity** is a specialized, fine-tuned LLM based on the Qwen 2.5 Coder architecture, optimized for **Unity game development and advanced C# scripting**. This repository contains the model weights in **GGUF format**, making it perfect for efficient local inference.

The model was fine-tuned using a curated dataset of nearly 1,000 high-quality, domain-specific instruction-response pairs sourced from official Unity documentation, advanced C# manuals, and high-tier synthetic data.

## Model Description

- **Developed by:** Pygenesis Association
- **Base Model:** Qwen 2.5 Coder
- **Format:** GGUF (Optimized for local deployment)
- **Specialization:** Unity Engine & C# Language

## Training Details

The training pipeline focused heavily on structure and logic:
* Full coverage of Unity Manual best practices, Monobehaviours, Scriptable Objects, and performance optimization.
* Advanced C# scripting patterns applied to game design.
* Instructional data distillation using frontier models to maximize code accuracy and deep reasoning capabilities.

## Intended Use

Pygenesis Unity is tailored for indie developers and technical leads who want a privacy-first, offline assistant to:
* Generate clean, optimized C# scripts for Unity loops and systems.
* Debug engine-specific code and refactor legacy scripts.
* Implement performance-oriented architecture (such as object pooling, memory management, or basic DOTS structures).

## How to Use

Since this model is provided in GGUF format, you can run it locally using various inference engines.

### Example using Llama.cpp CLI:
```bash
./llama-cli -m pygenesis-unity-qwen2.5-coder.gguf -p "Write a highly optimized C# script for an object pooling system in Unity." -n 512