GraySoft
Projects Models Compare Cloud benchmarks FAQ Download guIDE →
Model Intelligence Sheet

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…

ggufq4_k_mqwen2.5-codercodestemkotlinunitypythontext-generationbase_model:Qwen/Qwen2.5-Coder-3B-Instructbase_model:quantized:Qwen/Qwen2.5-Coder-3B-Instructlicense:apache-2.0endpoints_compatibleregion:usconversational

Runs locally from ~1.48 GB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

Downloads
38
Likes
0
Pipeline
text-generation
Author

Repository Files & Downloads

7 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
qwen2.5-coder-3b.F16.ggufGGUFGGUF5.75 GBDownload
qwen2.5-coder-3b.Q3_K_M.ggufGGUFGGUF1.48 GBDownload
qwen2.5-coder-3b.Q4_0.ggufGGUFGGUF1.70 GBDownload
qwen2.5-coder-3b.Q4_K_M.ggufGGUFGGUF1.80 GBDownload
qwen2.5-coder-3b.Q5_K_M.ggufGGUFGGUF2.07 GBDownload
qwen2.5-coder-3b.Q6_K.ggufGGUFGGUF2.36 GBDownload
qwen2.5-coder-3b.Q8_0.ggufGGUFGGUF3.06 GBDownload

Model Details

Model IDahmetggg/Luck-Qwen2.5-Coder-3B-STEM-GGUF
Authorahmetggg
Pipelinetext-generation
Licenseapache-2.0
Base modelQwen/Qwen2.5-Coder-3B-Instruct
Last modified2026-08-07T09:39:10.000Z

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=0.2 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

Run 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.

Download guIDE → · Browse 524k+ models · Compare models

Source: Hugging Face · Compare models