Luck-Qwen2.5-Coder-3B-STEM-GGUF

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.

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

Quick Start with Ollama

1. Download the model

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