library_name, pipeline_tag, base_model, license, tags, model-index

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

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

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

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