
# Visual Novel Dataset

This dataset contains parsed Visual Novel scripts for training language models. The dataset consists of approximately 60 million tokens of parsed scripts.

## Dataset Structure

The dataset follows a general structure for visual novel scripts:

- Dialogue lines: Dialogue lines are formatted with the speaker's name followed by a colon, and the dialogue itself enclosed in quotes. For example:

    ```
    John: "Hello, how are you?"
    ```

- Actions and narration: Actions and narration within the Visual Novel scripts are often enclosed in asterisks, but it's important to note that not all visual novels follow this convention. Actions and narration provide descriptions of character movements, background settings, or other narrative elements.

    ```
    *John looked around the room, searching for answers.*
    ```

## Contents

- `visual-novels.txt`: This file contains all the parsed VNs concatenated within a single plaintext file. Each entry is separated with this string:
  ```
  [          - title - {visual-novel-title-1.txt}          ]
  ```

- `VNDB/`: This directory contains `.json` files that contain VNDB IDs for the corresponding VN's characters. Does not include unparsed VNs.

- `Archives/visual-novels-parsed.tar.zst`: This archive contains the parsed VNs but with each script in a separate text file (i.e. not concatenated).

- `Archives/visual-novels-unparsed.tar.zst`: This archive contains all the unparsed VNs along with the original script for the currently parsed VNs.

## Usage

You can utilize this dataset to train language models, particularly for tasks related to natural language processing and text generation. By leveraging the parsed visual novel scripts, you can train models to understand dialogue structures and generate coherent responses. Additionally, the inclusion of the unparsed scripts allows for further analysis and processing.

## Contribution

This dataset was gathered and parsed by the [PygmalionAI](https://hugginface.co/PygmalionAI) Data Processing Team. Listed below are the team members, sorted by contribution amount:

- **Suikamelon**: [HuggingFace](https://huggingface.co/lemonilia) - (2,787,704 ++ 672,473 --)
- **Alpin**: [HuggingFace](https://huggingface.co/alpindale) - [GitHub](https://github.com/AlpinDale) (1,170,985 ++ 345,120 --)
- **Spartan**: [GitHub](https://github.com/Spartan9772) (901,046 ++ 467,915 --)
- **Unlucky-AI** [GitHub](https://github.com/Unlucky-AI) (253,316 ++ 256 --)

## Citation

If you use this dataset in your research or projects, please cite it appropriately.

## Acknowledgements

This dataset is compiled and shared for research and educational purposes. The dataset includes parsed visual novel scripts from various sources, which are predominantly copyrighted and owned by their respective publishers and creators. The inclusion of these scripts in this dataset does not imply any endorsement or authorization from the copyright holders.
We would like to express our sincere gratitude to the original copyright holders and creators of the visual novels for their valuable contributions to the art and storytelling. We respect and acknowledge their intellectual property rights.
We strongly encourage users of this dataset to adhere to copyright laws and any applicable licensing restrictions when using or analyzing the provided content. It is the responsibility of the users to ensure that any use of the dataset complies with the legal requirements governing intellectual property and fair use.
Please be aware that the creators and distributors of this dataset disclaim any liability or responsibility for any unauthorized or illegal use of the dataset by third parties.
If you are a copyright holder or have any concerns about the content included in this dataset, please contact us at [this email address](mailto:alpin@alpindale.dev) to discuss the matter further and address any potential issues.



task_categories:conversational task_categories:text-generation language:en license:apache-2.0 region:us
{"language": ["en"], "license": "apache-2.0", "task_categories": ["conversational", "text-generation"], "pretty_name": "Visual Novels"}
TAGS
#task_categories-conversational #task_categories-text-generation #language-English #license-apache-2.0 #region-us 


# Visual Novel Dataset

This dataset contains parsed Visual Novel scripts for training language models. The dataset consists of approximately 60 million tokens of parsed scripts.

## Dataset Structure

The dataset follows a general structure for visual novel scripts:

- Dialogue lines: Dialogue lines are formatted with the speaker's name followed by a colon, and the dialogue itself enclosed in quotes. For example:

    

- Actions and narration: Actions and narration within the Visual Novel scripts are often enclosed in asterisks, but it's important to note that not all visual novels follow this convention. Actions and narration provide descriptions of character movements, background settings, or other narrative elements.

    

## Contents

- 'URL': This file contains all the parsed VNs concatenated within a single plaintext file. Each entry is separated with this string:
  

- 'VNDB/': This directory contains '.json' files that contain VNDB IDs for the corresponding VN's characters. Does not include unparsed VNs.

- 'Archives/URL': This archive contains the parsed VNs but with each script in a separate text file (i.e. not concatenated).

- 'Archives/URL': This archive contains all the unparsed VNs along with the original script for the currently parsed VNs.

## Usage

You can utilize this dataset to train language models, particularly for tasks related to natural language processing and text generation. By leveraging the parsed visual novel scripts, you can train models to understand dialogue structures and generate coherent responses. Additionally, the inclusion of the unparsed scripts allows for further analysis and processing.

## Contribution

This dataset was gathered and parsed by the PygmalionAI Data Processing Team. Listed below are the team members, sorted by contribution amount:

- Suikamelon: HuggingFace - (2,787,704 ++ 672,473 --)
- Alpin: HuggingFace - GitHub (1,170,985 ++ 345,120 --)
- Spartan: GitHub (901,046 ++ 467,915 --)
- Unlucky-AI GitHub (253,316 ++ 256 --)

If you use this dataset in your research or projects, please cite it appropriately.

## Acknowledgements

This dataset is compiled and shared for research and educational purposes. The dataset includes parsed visual novel scripts from various sources, which are predominantly copyrighted and owned by their respective publishers and creators. The inclusion of these scripts in this dataset does not imply any endorsement or authorization from the copyright holders.
We would like to express our sincere gratitude to the original copyright holders and creators of the visual novels for their valuable contributions to the art and storytelling. We respect and acknowledge their intellectual property rights.
We strongly encourage users of this dataset to adhere to copyright laws and any applicable licensing restrictions when using or analyzing the provided content. It is the responsibility of the users to ensure that any use of the dataset complies with the legal requirements governing intellectual property and fair use.
Please be aware that the creators and distributors of this dataset disclaim any liability or responsibility for any unauthorized or illegal use of the dataset by third parties.
If you are a copyright holder or have any concerns about the content included in this dataset, please contact us at this email address to discuss the matter further and address any potential issues.



# Visual Novel Dataset

This dataset contains parsed Visual Novel scripts for training language models. The dataset consists of approximately 60 million tokens of parsed scripts. ## Dataset Structure

The dataset follows a general structure for visual novel scripts:

- Dialogue lines: Dialogue lines are formatted with the speaker's name followed by a colon, and the dialogue itself enclosed in quotes. For example:

    

- Actions and narration: Actions and narration within the Visual Novel scripts are often enclosed in asterisks, but it's important to note that not all visual novels follow this convention. Actions and narration provide descriptions of character movements, background settings, or other narrative elements. ## Contents

- 'URL': This file contains all the parsed VNs concatenated within a single plaintext file. Each entry is separated with this string:
  

- 'VNDB/': This directory contains '.json' files that contain VNDB IDs for the corresponding VN's characters. Does not include unparsed VNs.

- 'Archives/URL': This archive contains the parsed VNs but with each script in a separate text file (i.e. not concatenated).

- 'Archives/URL': This archive contains all the unparsed VNs along with the original script for the currently parsed VNs. ## Usage

You can utilize this dataset to train language models, particularly for tasks related to natural language processing and text generation. By leveraging the parsed visual novel scripts, you can train models to understand dialogue structures and generate coherent responses. Additionally, the inclusion of the unparsed scripts allows for further analysis and processing. ## Contribution

This dataset was gathered and parsed by the PygmalionAI Data Processing Team. Listed below are the team members, sorted by contribution amount:

- Suikamelon: HuggingFace - (2,787,704 ++ 672,473 --)
- Alpin: HuggingFace - GitHub (1,170,985 ++ 345,120 --)
- Spartan: GitHub (901,046 ++ 467,915 --)
- Unlucky-AI GitHub (253,316 ++ 256 --)

If you use this dataset in your research or projects, please cite it appropriately. ## Acknowledgements

This dataset is compiled and shared for research and educational purposes. The dataset includes parsed visual novel scripts from various sources, which are predominantly copyrighted and owned by their respective publishers and creators. The inclusion of these scripts in this dataset does not imply any endorsement or authorization from the copyright holders.
We would like to express our sincere gratitude to the original copyright holders and creators of the visual novels for their valuable contributions to the art and storytelling. We respect and acknowledge their intellectual property rights.
We strongly encourage users of this dataset to adhere to copyright laws and any applicable licensing restrictions when using or analyzing the provided content. It is the responsibility of the users to ensure that any use of the dataset complies with the legal requirements governing intellectual property and fair use.
Please be aware that the creators and distributors of this dataset disclaim any liability or responsibility for any unauthorized or illegal use of the dataset by third parties.
If you are a copyright holder or have any concerns about the content included in this dataset, please contact us at this email address to discuss the matter further and address any potential issues.
TAGS
#task_categories-conversational #task_categories-text-generation #language-English #license-apache-2.0 #region-us 
 # Visual Novel Dataset

This dataset contains parsed Visual Novel scripts for training language models. The dataset consists of approximately 60 million tokens of parsed scripts. ## Dataset Structure

The dataset follows a general structure for visual novel scripts:

- Dialogue lines: Dialogue lines are formatted with the speaker's name followed by a colon, and the dialogue itself enclosed in quotes. For example:

    

- Actions and narration: Actions and narration within the Visual Novel scripts are often enclosed in asterisks, but it's important to note that not all visual novels follow this convention. Actions and narration provide descriptions of character movements, background settings, or other narrative elements. ## Contents

- 'URL': This file contains all the parsed VNs concatenated within a single plaintext file. Each entry is separated with this string:
  

- 'VNDB/': This directory contains '.json' files that contain VNDB IDs for the corresponding VN's characters. Does not include unparsed VNs.

- 'Archives/URL': This archive contains the parsed VNs but with each script in a separate text file (i.e. not concatenated).

- 'Archives/URL': This archive contains all the unparsed VNs along with the original script for the currently parsed VNs. ## Usage

You can utilize this dataset to train language models, particularly for tasks related to natural language processing and text generation. By leveraging the parsed visual novel scripts, you can train models to understand dialogue structures and generate coherent responses. Additionally, the inclusion of the unparsed scripts allows for further analysis and processing. ## Contribution

This dataset was gathered and parsed by the PygmalionAI Data Processing Team. Listed below are the team members, sorted by contribution amount:

- Suikamelon: HuggingFace - (2,787,704 ++ 672,473 --)
- Alpin: HuggingFace - GitHub (1,170,985 ++ 345,120 --)
- Spartan: GitHub (901,046 ++ 467,915 --)
- Unlucky-AI GitHub (253,316 ++ 256 --)

If you use this dataset in your research or projects, please cite it appropriately. ## Acknowledgements

This dataset is compiled and shared for research and educational purposes. The dataset includes parsed visual novel scripts from various sources, which are predominantly copyrighted and owned by their respective publishers and creators. The inclusion of these scripts in this dataset does not imply any endorsement or authorization from the copyright holders.
We would like to express our sincere gratitude to the original copyright holders and creators of the visual novels for their valuable contributions to the art and storytelling. We respect and acknowledge their intellectual property rights.
We strongly encourage users of this dataset to adhere to copyright laws and any applicable licensing restrictions when using or analyzing the provided content. It is the responsibility of the users to ensure that any use of the dataset complies with the legal requirements governing intellectual property and fair use.
Please be aware that the creators and distributors of this dataset disclaim any liability or responsibility for any unauthorized or illegal use of the dataset by third parties.
If you are a copyright holder or have any concerns about the content included in this dataset, please contact us at this email address to discuss the matter further and address any potential issues.
passage: TAGS
#task_categories-conversational #task_categories-text-generation #language-English #license-apache-2.0 #region-us 
# Visual Novel Dataset

This dataset contains parsed Visual Novel scripts for training language models. The dataset consists of approximately 60 million tokens of parsed scripts.## Dataset Structure

The dataset follows a general structure for visual novel scripts:

- Dialogue lines: Dialogue lines are formatted with the speaker's name followed by a colon, and the dialogue itself enclosed in quotes. For example:

    

- Actions and narration: Actions and narration within the Visual Novel scripts are often enclosed in asterisks, but it's important to note that not all visual novels follow this convention. Actions and narration provide descriptions of character movements, background settings, or other narrative elements.## Contents

- 'URL': This file contains all the parsed VNs concatenated within a single plaintext file. Each entry is separated with this string:
  

- 'VNDB/': This directory contains '.json' files that contain VNDB IDs for the corresponding VN's characters. Does not include unparsed VNs.

- 'Archives/URL': This archive contains the parsed VNs but with each script in a separate text file (i.e. not concatenated).

- 'Archives/URL': This archive contains all the unparsed VNs along with the original script for the currently parsed VNs.## Usage

You can utilize this dataset to train language models, particularly for tasks related to natural language processing and text generation. By leveraging the parsed visual novel scripts, you can train models to understand dialogue structures and generate coherent responses. Additionally, the inclusion of the unparsed scripts allows for further analysis and processing.