| --- |
| license: mit |
| language: |
| - en |
| tags: |
| - rust |
| - code |
| - instruction-tuning |
| - magicoder |
| - oss-instruct |
| pretty_name: Magicoder OSS Instruct Rust (3.9K Cleaned) |
| size_categories: |
| - 1K<n<10K |
| task_categories: |
| - text-generation |
| --- |
| |
| # 🦀 Magicoder-OSS-Instruct-Rust (3.9K Cleaned) |
|
|
| **Magicoder-OSS-Instruct-Rust** is a high-quality, syntax-verified dataset of **3,909** Rust coding instructions derived from real-world open-source GitHub projects. |
|
|
| This dataset is extracted from [ise-uiuc/Magicoder-OSS-Instruct-75K](https://huggingface.co/datasets/ise-uiuc/Magicoder-OSS-Instruct-75K), filtered specifically for Rust, and validated via in-memory compiler checks. No language translation was applied; the dataset remains in its original English format. |
|
|
| --- |
|
|
| ## ⚙️ Filtering and Verification Methodology |
|
|
| The dataset was processed using the following technical pipeline: |
|
|
| * **Language Filtering:** Extracted entries strictly where `lang: rust`, removing all other programming languages. |
| * **In-Memory Syntax Validation (`rustc` RAM Check):** All code snippets were evaluated on-the-fly via `rustc --crate-type=lib` through standard input (`stdin`). Entries with broken syntax, unclosed braces, or invalid AST structures were automatically discarded. |
| * **Format Standardization:** Converted raw problem/solution pairs into standard ChatML (`messages`) format for direct compatibility with SFT and Fine-Tuning frameworks (LoRA / QLoRA). |
|
|
| --- |
|
|
| ## ⚠️ Filtering Summary (75K -> 3.9K) |
|
|
| Out of the original 75,000 multi-language samples: |
| 1. Non-Rust programming languages were filtered out. |
| 2. Incomplete snippets or entries failing `rustc` syntax checks were removed. |
| 3. A clean, verified set of **3,909 high-quality Rust instructions** was produced. |
|
|
| --- |
|
|
| ## 📊 Dataset Structure |
|
|
| The dataset follows the **ChatML** (`messages`) format: |
|
|
| * **`system`**: System prompt assigning the expert Rust developer role. |
| * **`user`**: Rust programming task, module design requirement, or algorithmic problem. |
| * **`assistant`**: Corresponding idiomatic Rust solution. |
|
|
| ### Schema Details |
|
|
| | Field | Type | Description | |
| |---|---|---| |
| | `id` | `int64` | Original dataset index | |
| | `task_category` | `string` | Task category identifier (`oss_instruct`) | |
| | `messages` | `list` | Conversation history containing `role` and `content` (`system`, `user`, `assistant`) | |
|
|
| --- |
|
|
| ## 💡 Example Entry |
|
|
| ```json |
| { |
| "id": 1601, |
| "task_category": "oss_instruct", |
| "messages": [ |
| { |
| "role": "system", |
| "content": "You are an expert assistant who solves Rust programming problems and generates correct code." |
| }, |
| { |
| "role": "user", |
| "content": "You are tasked with creating a Rust module system for a 2D game engine..." |
| }, |
| { |
| "role": "assistant", |
| "content": "```rust\n// input_handler.rs\npub mod input_handler {\n pub struct InputHandler {\n // Implementation details\n }\n}\n\n// input.rs\npub mod input {\n pub use input_handler::InputHandler;\n pub use keyboard::Keyboard;\n pub use mouse::Mouse;\n pub use gamepad::Gamepad;\n}\n```\n\nIn this solution, we have created the input modules..." |
| } |
| ] |
| } |
| ``` |
| |
| --- |
| |
| ## 💻 Usage |
| |
| ```python |
| from datasets import load_dataset |
|
|
| dataset = load_dataset("WrittenWithRust/Magicoder-OSS-Instruct-Rust-3.9K") |
| print(dataset["train"][0]) |
| ``` |
| |
| --- |
| |
| ## 📜 Citation |
| |
| ```bibtex |
| @article{wei2023magicoder, |
| title={Magicoder: Source Code Is All You Need}, |
| author={Wei, Yuxiang and Wang, Zhe and Liu, Jiawei and Ding, Yuhang and Zhang, Lingming}, |
| journal={arXiv preprint arXiv:2312.02120}, |
| year={2023} |
| } |
| ``` |
