LLM Datasets

50,000 Sets - Image Editing Data. The editing types include human attribute editing, image semantic editing, and image structure editing. The editing targets cover scenes such as people, animals, goods, plants, and landscapes. In terms of annotation, based on the editing instructions, the targets that need to be edited in the image are edited. The data can be used for tasks such as image synthesis, data augmentation, and virtual scene generation.

This dataset includes 120,000 multimodal question-answer pairs across six major academic disciplines, including medicine, engineering, art, science, and more. Each QA pair combines textual and visual content—such as charts, diagrams, blueprints, and artworks—crafted to test logical reasoning, cross-modal understanding, and domain-specific knowledge. All questions have been reviewed by subject-matter experts to ensure academic quality and accuracy. Ideal for training multimodal large language models (MLLMs), visual question answering (VQA) systems, and AI applications requiring deep contextual reasoning, this dataset supports fine-tuning tasks like knowledge grounding, visual-text alignment, and decision-making. All data complies with GDPR, CCPA, and PIPL regulations, ensuring ethical use and privacy protection.

100,145 Sets of ICONS Image Caption Data. The data includes two major categories of icons, namely 3D Style Icons and Vector Illustration Icons, totaling 16 subcategories. In terms of annotation, the icon descriptions are in Chinese, with a description length of about 30 characters. The data can be used for tasks such as graphic recognition and interface interaction.

100,000 Fine-Tuning Text Dataset for English LLM General Domain SFT is a high-quality supervised fine-tuning corpus designed to optimize instruction-following capabilities in large language models. Each data point is double-verified by experienced linguistic professionals and AI engineers to ensure relevance, clarity, and effectiveness in improving model alignment and response precision. The dataset supports instruction tuning tasks across a wide range of general knowledge domains and is compatible with leading open-source LLMs such as LLaMA, Falcon, GPT-NeoX, and Mistral. Ideal for use in alignment, safety tuning, and instruction-based generation enhancement, this dataset offers a robust foundation for model adaptation and performance improvement. All data complies with global data usage and privacy standards.

300 Million Pairs of High-Quality Image-Caption Dataset includes a large-scale collection of photographic and vector images paired with English textual descriptions. The complete image library comprises nearly 300 million images, with a curated subset of 100 million high-quality image-caption pairs available for generative AI and vision-language model training. All images are authentic and legally licensed works created by professional photographers. The dataset primarily features English captions with minimal Chinese, offering diverse scenes, objects, and compositions suitable for tasks such as image captioning, visual question answering (VQA), image-text retrieval, and multimodal foundation model pretraining. The dataset supports large-scale LLM and VLM applications and complies with global data privacy and copyright regulations, including GDPR, CCPA, and PIPL.

This dataset contains 2.4 million structured Korean exam questions covering primary, middle, and high school subjects including Korean, Mathematics, English, Social Studies, Science, Physics, Chemistry, Biology, History, and Geography. Each record includes question type (multiple-choice, fill-in-the-blank, true/false, short answer), the question itself, standard answers, and detailed explanations. The data is professionally annotated and categorized by subject and academic level, making it ideal for training AI models in educational applications such as question answering systems, tutoring bots, academic reasoning, and subject-level knowledge enhancement. It is widely applicable for natural language processing tasks involving structured QA, exam-style NLP training, and educational content generation. All data is collected and processed in compliance with GDPR, CCPA, and PIPL standards, ensuring privacy and legal integrity throughout the lifecycle.

7 million global genuine high-quality videos. All are genuine video works released by photographers around the world. 6 million of them are described in English and 1 million in Chinese. They cover a variety of categories such as people, landscapes, animals, etc. The resolution is above 1080p.

This dataset focuses on the four major European languages (French, German, Spanish, Italian) and contains 480000 pairs of original and corrected text pairs. Each piece of data is presented in JSON format, including two fields: input (raw text) and output (corrected text), which can assist in natural language processing, machine translation, and language teaching research.

Massive 3D Models & Scenes Dataset includes 270 million sets of 3D models and 18 million 3D scenes. 3D models cover conventional models, interactive models, and physics-enhanced models with various objects in indoor residential environments. 3D scenes cover indoor home decoration scenarios and commercial space environments. This dataset can be used for tasks like 3D asset generation, virtual environment simulation, AI model training, and industrial design applications.