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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- The dataset may contain imperfect or outdated coding practices.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 |