Datasets:
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---
language:
- en
license: mit
task_categories:
- text2text-generation
- text-generation
- summarization
tags:
- chemistry
- biology
- finance
- legal
- music
- art
- code
- climate
- medical
- synthetic
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: input
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 20371003
num_examples: 94501
download_size: 13771195
dataset_size: 20371003
---
# LLM Prompt Dataset
## Overview
The LLM Prompt Dataset is designed to enhance the performance of large language models (LLMs) by transforming user inputs into structured prompts. This dataset aims to facilitate the understanding of complex queries and improve the interaction between users and LLMs.
## Dataset Structure
The dataset is organized in JSON format, where each entry consists of an `input` and a `prompt`. The `input` represents the original user query or statement, while the `prompt` provides a clear and concise reformulation suitable for LLM processing.
## Features
- **User-Centric Design**: Each entry is crafted to reflect common user queries, ensuring relevance and applicability.
- **Diverse Topics**: The dataset covers a wide range of topics, making it suitable for various applications in natural language processing and machine learning.
- **Structured Format**: The use of JSON format ensures compatibility with various data processing tools and frameworks.
## Usage
To use this dataset, you can download it directly from the Hugging Face repository or access it using the Hugging Face `datasets` library. The dataset can be utilized for training, fine-tuning, or evaluating large language models.
### Installation
You can install the `datasets` library using pip if you haven't done so already:
```bash
pip install datasets
```
### Loading the Dataset
Here’s how to load the dataset using the Hugging Face `datasets` library:
```python
from datasets import load_dataset
dataset = load_dataset("your_username/your_dataset_name")
```
## Contributing
Contributions to this dataset are welcome! If you have suggestions for additional entries or improvements, please open an issue or submit a pull request.
## License
This dataset is licensed under [MIT License](LICENSE).
## Acknowledgments
Thank you to the community for supporting the development and improvement of this dataset. Your contributions make a difference in the field of natural language processing. |