| --- |
| dataset_info: |
| features: |
| - name: source |
| dtype: string |
| - name: language |
| dtype: string |
| - name: content |
| dtype: string |
| - name: tokens |
| dtype: int64 |
| - name: metadata |
| struct: |
| - name: type |
| dtype: string |
| - name: id |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 127466907 |
| num_examples: 59244 |
| download_size: 24864346 |
| dataset_size: 127466907 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| description: null |
| license: mit |
| language: |
| - en |
| tags: |
| - code |
| size_categories: |
| - 1M<n<10M |
| --- |
| 🚀 MUD-Code3-Mega – 10M Tokens of High‑Quality Code |
| This dataset contains 59244 synthetic code snippets designed to mimic real‑world production‑grade code across multiple domains (ML, web, async, data processing, deep learning, etc.). All samples are carefully crafted to be realistic, well‑structured, and high‑quality. |
|
|
| Total tokens: 10,000,112 |
| Languages: Python (with some snippets including other languages like SQL, Dockerfile) |
| Quality: High – generated from expert‑level templates with variations. |
| 📖 How to Use |
| from datasets import load_dataset |
| dataset = load_dataset("CompiwerAI/MUD-Code3-Mega") |
| print(dataset["train"][0]) |
|
|
| 📊 Stats |
| Metric Value |
| Total Documents 59244 |
| Total Tokens 10,000,112 |
| File Size (raw) ~129 MB |
| 🔍 Why This Dataset? |
| 🧠 Large scale – 10M tokens for robust training. |
| 🧪 High quality – templates from production code patterns. |
| 🌍 Diverse – covers many domains and paradigms. |
| 📦 Ready to use – standard format, no preprocessing needed. |
| 📜 License & Citation |
| MIT License. |
| If you use this dataset, please cite: |
|
|
| @misc{mud-code3-mega-2026, |
| author = {CompiwerAI}, |
| title = {MUD‑Code3-Mega: A 10M‑token High‑Quality Code Dataset}, |
| year = {2026}, |
| publisher = {Hugging Face}, |
| url = {https://huggingface.co/datasets/CompiwerAI/MUD-Code3-Mega} |
| } |
