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--- |
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license: afl-3.0 |
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task_categories: |
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- text-generation |
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- text2text-generation |
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- summarization |
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language: |
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- en |
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pretty_name: Tamer Novel Dataset |
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size_categories: |
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- 100K<n<1M |
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tags: |
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- roleplay |
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- character |
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- ELiTA |
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- TaMeR |
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- RLHF |
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- novel |
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--- |
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# Tamer Novel Dataset |
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Welcome to the `tamer-novel` dataset. This unique dataset is crafted with the remarkable Tamer Novel Styler writing, enhanced by the ELiTA technique, and aims to augment self-awareness in large language models (LLMs). |
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## Overview |
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The Tamer Novel dataset is designed for researchers, developers, and enthusiasts in AI, specifically those working on enhancing the self-awareness and contextual understanding of LLMs. By leveraging the novel ELiTA technique, this dataset provides a rich source of stylized narrative text that challenges and refines AI models' comprehension and generation capabilities. |
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### Dataset Structure |
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The dataset is structured to facilitate easy access and manipulation for various AI projects. It includes: |
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- **Text Files**: Each file contains passages from the Tamer Novel, processed through the ELiTA technique. |
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- **Metadata**: Information about the passages, including style markers and annotations related to the ELiTA technique. |
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### Using the Dataset |
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To work with the `tamer-novel` dataset, we recommend using the upcoming AIflow Python library, which is designed to streamline AI research and development processes. Stay tuned for the library's release for an optimized experience. |
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## Applications |
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This dataset is ideal for: |
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- Train and evaluate LLMs on understanding and generating stylized narrative text. |
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- Research in AI ethics, focusing on developing self-aware AI systems. |
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- Exploratory projects aiming to understand the impact of narrative styles on AI comprehension and generation. |
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## How to Use |
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To get started with the `tamer-novel` dataset, please follow these steps: |
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1. Install the aiflow python library (coming soon). |
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2. Load the dataset using aiflow with the following code snippet: |
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```python |
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# Code snippet coming soon |
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``` |
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3. Explore the dataset and start your project! |
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# Additional Information: |
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Use this link to read more about the model usage: https://github.com/yukiarimo/yuna-ai |
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ELiTA Paper: https://www.academia.edu/116519117/ELiTA_Elevating_LLMs_Lingua_Thoughtful_Abilities_via_Grammarly |
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The Yuna AI V2 model was trained using such a dataset for the first time. You can check the model here: https://huggingface.co/yukiarimo/yuna-ai-v2 |
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## Contributing and Feedback |
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You can contact the developer for more information or to contribute to the project! |
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- [Discord](https://discord.com/users/1131657390752800899) |
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- [Twitter](https://twitter.com/yukiarimo) |
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[](https://www.patreon.com/YukiArimo) |
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[](https://github.com/yukiarimo) |
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## Acknowledgments |
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Special thanks to the contributors to the ELiTA technique and the upcoming AIflow Python library. Your innovations and contributions have been invaluable in creating this dataset. |
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## Citation |
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If you use the `tamer-novel` dataset in your research, please cite it as follows: |
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```bibtex |
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@misc{tamer-novel, |
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author = {Yuki Arimo}, |
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title = {Tamer Novel Dataset}, |
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year = {2024}, |
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publisher = {HuggingFace}, |
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journal = {HuggingFace Dataset Hub}, |
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} |
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``` |
