---
license: apache-2.0
tags:
  - python
  - code-generation
  - fine-tuned
  - qwen
  - gguf
  - coding
  - programming
---

# Qwen2.5-Coder-3B-High

[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)

> **Fine-tuned version of Qwen2.5-Coder-3B** optimized specifically for Python programming tasks. Outperforms the base model on Python-related problems, code generation, and real-world development scenarios.

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## 🚀 Overview

This repository hosts a fine-tuned variant of **Qwen2.5-Coder-3B**, trained on a high-quality dataset of Python programming problems, coding challenges, and real-world software engineering examples. The fine-tuning process significantly enhances the model’s ability to understand and generate idiomatic, efficient, and correct Python code.

### ✅ Key Improvements Over Base Model:
- Higher accuracy on Python syntax, standard library usage, and common frameworks (e.g., Pandas, NumPy, asyncio)
- Better code completion and function generation from natural language prompts
- Improved reasoning for algorithmic problems (e.g., sorting, recursion, data structures)
- More consistent and readable output formatting

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## 📦 Model Files (GGUF Format)

All models are provided in **GGUF** format for broad compatibility with inference engines like `llama.cpp`, `Ollama`, `LM Studio`, and more.

| Filename                                | Quantization | Size   | Recommended Use Case        |
|----------------------------------------|--------------|--------|-----------------------------|
| `Qwen2.5-Coder-3B-High.F16.gguf`       | Float16      | ~6.2 GB| Maximum quality (GPU)       |
| `Qwen2.5-Coder-3B-High.Q8_0.gguf`      | Q8_0         | ~3.3 GB| High quality, CPU/GPU       |
| `Qwen2.5-Coder-3B-High.Q5_K_M.gguf`    | Q5_K_M       | ~2.2 GB| Balanced speed/quality      |
| `Qwen2.5-Coder-3B-High.Q4_K_M.gguf`    | Q4_K_M       | ~1.9 GB| Fast inference, low RAM     |

> 💡 **Recommendation**: Start with `Q5_K_M` for most local development tasks.

---

## 📈 Performance

Evaluated on an internal benchmark of 200 Python-specific prompts (including LeetCode-style problems, docstring-to-code, bug fixes, and library usage):

| Metric                          | Base Qwen2.5-Coder-3B | Qwen2.5-Coder-3B-High |
|--------------------------------|------------------------|------------------------|
| Code Correctness (Pass@1)      | 68%                    | **84%**                |
| Syntax Validity                | 92%                    | **98%**                |
| Library Usage Accuracy         | 71%                    | **89%**                |
| Readability (Human Eval)       | 3.8 / 5                | **4.5 / 5**            |

> 🔍 *Benchmark details available upon request.*

---

## 🛠️ Usage Examples

### With `llama.cpp`
```bash
./main -m ./models/Qwen2.5-Coder-3B-High.Q5_K_M.gguf \
       -p "Write a Python function that takes a list of integers and returns the sum of even numbers." \
       -n 256 --temp 0.2