ahmetggg/Luck-Qwen2.5-Coder-3B-STEM-GGUF overview
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 traine…
Runs locally from ~1.48 GB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| qwen2.5-coder-3b.F16.gguf | GGUF | GGUF | 5.75 GB | Download |
| qwen2.5-coder-3b.Q3_K_M.gguf | GGUF | GGUF | 1.48 GB | Download |
| qwen2.5-coder-3b.Q4_0.gguf | GGUF | GGUF | 1.70 GB | Download |
| qwen2.5-coder-3b.Q4_K_M.gguf | GGUF | GGUF | 1.80 GB | Download |
| qwen2.5-coder-3b.Q5_K_M.gguf | GGUF | GGUF | 2.07 GB | Download |
| qwen2.5-coder-3b.Q6_K.gguf | GGUF | GGUF | 2.36 GB | Download |
| qwen2.5-coder-3b.Q8_0.gguf | GGUF | GGUF | 3.06 GB | Download |
Model Details
| Model ID | ahmetggg/Luck-Qwen2.5-Coder-3B-STEM-GGUF |
|---|---|
| Author | ahmetggg |
| Pipeline | text-generation |
| License | apache-2.0 |
| Base model | Qwen/Qwen2.5-Coder-3B-Instruct |
| Last modified | 2026-08-07T09:39:10.000Z |
Model README
---
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=0.2andmax_new_tokens=512for 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 ./modelsRun ahmetggg/Luck-Qwen2.5-Coder-3B-STEM-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models