language:en license:apache-2.0 size_categories:1K<n<10K format:parquet modality:text library:datasets library:pandas library:mlcroissant library:polars region:us question&Answer
---
license: apache-2.0
dataset_info:
  features:
  - name: Query
    dtype: string
  - name: ShortResponse
    dtype: string
  - name: DetailedResponse
    dtype: string
  splits:
  - name: train
    num_bytes: 181752
    num_examples: 1426
  download_size: 85206
  dataset_size: 181752
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
language:
- en
tags:
- question&Answer
pretty_name: Question & Answer
size_categories:
- 1K<n<10K
---

# Query Response Dataset

## Overview

The **Query Response Dataset** is designed to provide a rich set of question-answer pairs, ideal for training AI models in natural language processing (NLP) tasks. This dataset contains structured query-response data that can be utilized for various applications, including chatbots, virtual assistants, and customer support systems.

### Dataset Details

- **Number of Entries**: 1.5K
- **Fields**:
  - **Query**: The question or inquiry made by a user.
  - **ShortResponse**: A concise answer to the query.
  - **DetailedResponse**: An expanded explanation or answer to the query.

## Purpose

This dataset is intended for researchers and developers who are building applications that require understanding and generating human-like responses to queries. It can be used to improve the performance of conversational AI systems and enhance user interactions.

## Features

- **Diverse Questions**: The dataset covers a wide range of topics, ensuring that models trained on this data can handle various user inquiries.
- **Structured Format**: The dataset is organized in a clear, structured format, making it easy to ingest and use in machine learning workflows.

## Usage

You can load this dataset using the `datasets` library from Hugging Face:

```python
from datasets import load_dataset

dataset = load_dataset("MohamedAshraf701/query-response-dataset")
```

### Example Usage

Here is a simple example of how to access data from the dataset:

```python
# Accessing the first entry
first_entry = dataset['train'][0]
print("Query:", first_entry['Query'])
print("Short Response:", first_entry['ShortResponse'])
print("Detailed Response:", first_entry['DetailedResponse'])
```

## Contributions

Contributions to this dataset are welcome! If you have additional questions or response pairs to add, feel free to open an issue or submit a pull request.

## License

This dataset is licensed under the [MIT License](LICENSE). 

## Contact

For any inquiries or support, please reach out to [ashrafchauhan567@gmail.com](mailto:ashrafchauhan567@gmail.com).