| --- |
| language: |
| - en |
|
|
| license: apache-2.0 |
|
|
| task_categories: |
| - text-generation |
|
|
| tags: |
| - custom |
| - vibecodinginstruct |
| pretty_name: Vibe-Coding-Instruct |
| size_categories: |
| - 1M<n<10M |
| --- |
| |
| # Vibe-Coding-Instruct |
|
|
| ## Dataset Summary |
|
|
| Vibe-Coding-Instruct is a large-scale instruction-following dataset designed for supervised fine-tuning (SFT) of coding-focused large language models. The dataset contains over **1.1 million** instruction-response pairs covering programming, debugging, code explanation, software engineering, algorithms, scripting, web development, and general developer assistance. |
|
|
| Each example consists of an instruction, optional input context, the expected output, and a preformatted prompt suitable for instruction-tuned models. |
|
|
| ## Dataset Structure |
|
|
| Each record contains four fields: |
|
|
| | Column | Description | |
| |---------|-------------| |
| | `instruction` | The user's coding task or request | |
| | `input` | Optional additional context | |
| | `output` | Expected assistant response | |
| | `prompt` | Preformatted prompt combining instruction and input | |
|
|
| ## ✨ Highlights |
|
|
| - 🚀 1.1M instruction-response pairs |
| - 💻 Covers multiple programming languages |
| - 🧠 Optimized for Supervised Fine-Tuning (SFT) |
| - 🤖 Compatible with Llama, Qwen, Gemma, Mistral, DeepSeek |
| - 📦 Ready-to-use Parquet format |
| - ⚡ Includes pre-formatted prompts |
| |
| Example: |
|
|
| ```json |
| { |
| "instruction": "Write a Python function to reverse a string.", |
| "input": "", |
| "output": "def reverse_string(s):\n return s[::-1]", |
| "prompt": "### Instruction:\nWrite a Python function to reverse a string.\n\n### Response:" |
| } |
| ``` |
|
|
| ## Quick Start |
|
|
| ```python |
| from datasets import load_dataset |
| |
| dataset = load_dataset( |
| "LeeChanRX/Vibe-Coding-Instruct" |
| ) |
| |
| print(dataset["train"][0]) |
| ``` |
|
|
| ## Intended Uses |
|
|
| This dataset is suitable for: |
|
|
| - Supervised Fine-Tuning (SFT) |
| - Coding assistants |
| - Code generation models |
| - Debugging assistants |
| - Instruction-following LLMs |
| - Research on code-focused language models |
|
|
| ## Data Sources |
|
|
| The dataset was curated and generated by **LeeChanRX**. It contains instruction-response pairs intended for training language models and may include both synthetic and curated examples. |
|
|
| ## Limitations |
|
|
| - The dataset may contain imperfect or outdated coding practices. |
| - Generated code should be reviewed before production use. |
| - Responses have not been manually verified for every sample. |
|
|
| ## Citation |
|
|
| If you use this dataset, please cite the repository: |
|
|
| ``` |
| @dataset{VibeCodingInstruct, |
| author = {LeeChanRX}, |
| title = {Vibe-Coding-Instruct}, |
| year = {2026}, |
| publisher = {Hugging Face} |
| } |
| ``` |
|
|
| ## License |
|
|
| Apache-2.0 |
