Show HN: Anime Text Datasets for LLMs Training (github.com)

A new text-only anime dataset has been introduced for fine-tuning large language models (LLMs), catering specifically to a range of AI applications including instruction tuning, retrieval-augmented generation (RAG), and question answering (QA). This dataset, boasting 35,766 unique anime works, contains a wealth of structured data, including 283,477 characters, 535,642 staff credits, and nearly 317,907 QA pairs. By leveraging a vast array of text content — from episode details and series relationships to grounded instruction examples — this dataset aims to enhance the natural language processing capabilities of models trained on anime-related information. The significance of this dataset lies in its comprehensive and structured approach to anime content, which not only aids in fine-tuning existing language models but also provides a robust resource for education and research purposes. With a 30% preview available for free to anyone with a Hugging Face account, the dataset facilitates broader access and experimentation. Users can leverage various formats, including JSONL and Parquet, ensuring easy integration into existing pipelines for training and validation tasks. The meticulous design, including checks for data integrity, allows researchers to directly engage with high-quality, grounded textual data while adhering to licensing regimes for ethical use.