license:mit size_categories:n<1K format:json modality:text library:datasets library:pandas library:mlcroissant library:polars region:us
---
license: mit
---

# Dataset Card for Dataset Name

<!-- Provide a quick summary of the dataset. -->
This dataset contains conversations between a text-to-image bot and users, 
designed to train and evaluate dialogue systems for image generation based on user descriptions.


## Dataset Details

### Dataset Description

<!-- Provide a longer summary of what this dataset is. -->
This dataset consists of text-based conversations between a text-to-image bot and users. 
Each conversation focuses on a user describing an image they want the bot to generate. 
The conversations include details about the desired content, style, and composition of the image.


- **Curated by:** [Tharuka Pavith](https://huggingface.co/th4ruka)
- **Funded by:** N/A
- **Shared by:** N/A
- **Language(s):** English
- **License:** MIT License

## Uses

<!-- Address questions around how the dataset is intended to be used. -->

### Direct Use

<!-- This section describes suitable use cases for the dataset. -->
This dataset can be used to train various machine learning models, including:

- Text-to-image dialogue systems
- Chatbots focused on image generation
- NLP models for understanding user intent and generating image prompts


### Out-of-Scope Use

<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
This dataset is not intended for:

- Training models for generating hateful or offensive content
- Training models for biased image generation
- Evaluating models on tasks unrelated to text-to-image generation

## Dataset Structure

<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
Each conversation in the dataset is stored in a JSON Lines (JSONL) format. 
Each line represents a single message in the conversation. The JSON object within the JSONL file has the following structure:
```
{
  "role": "system" | "user" | "assistant",
  "content": "text content of the message"
}
```

## Dataset Creation

### Curation Rationale

<!-- Motivation for the creation of this dataset. -->
This dataset was created to provide training data for dialogue systems that can assist users in 
generating images based on textual descriptions.

### Source Data

<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
The source data for this dataset consists of simulated conversations between a hypothetical text-to-image bot and users. 
These conversations were designed to cover a variety of image types and user requests.

#### Data Collection and Processing

<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
  The conversations were manually created by GPT 3.5, focusing on clear and concise user descriptions 
and informative bot responses to ensure a comprehensive understanding for image generation.

#### Who are the source data producers?

<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
GPT 3.5

### Annotations [optional]

<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
N/A


## Bias, Risks, and Limitations

<!-- This section is meant to convey both technical and sociotechnical limitations. -->
This dataset is limited by the following:

The conversations are simulated and may not reflect real-world user interactions perfectly.
The dataset size might be limited depending on the collection process.
Biases inherent in the model used for simulation might be present in the conversations.

### Recommendations

<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users should be aware of these limitations and potential biases when using the dataset. 
Consider collecting additional real-world user interactions to complement this dataset.

**BibTeX:**
```
@misc{bard_text2image_dataset,
  title={Text-to-Image Bot Conversations Dataset},
  author={Tharuka Pavith},
  year={2024},
}
```

**APA:**
Tharuka Pavith (2024). 
Text-to-Image Bot Conversations Dataset. [dataset].

## Glossary 

<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
- Text-to-image bot: A software program that can generate images based on textual descriptions.
- Dialogue system: A system that can hold a conversation with a human user.
- NLP: Natural Language Processing


## Dataset Card Authors
[Tharuka Pavith](https://huggingface.co/th4ruka)

## Dataset Card Contact
[Tharuka Pavith](https://huggingface.co/th4ruka)