LLM Datasets

English Animals Medical dataset, Including hospital treatment details, hospital test results, hospital pet prescription, allergy test list, vaccination history for multiple animals, enhancing model performance in real and complex tasks. Quality tested by various AI companies. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied.

This dataset focuses on the financial field, covering sub items such as products, markets, behaviors, and principles, with a total of 250000 questions. Among them, multiple-choice questions and Q&A questions each account for half, with 125000 questions in total. The data is stored in JSON format, with providing rich materials for financial knowledge research, learning, and more.

20,846 Groups Image Caption Data of Cookbook. Each set of recipes contains 4-18 images and a text description for each image. Cuisines include Chinese Cuisine, Western Cuisine, Korean Cuisine, Japanese Cuisine and so on. Description languages are Chinese and English. In terms of text length, the Chinese description should be no less than 15 words, and the English description should be no less than 30 words. The data can be used for recipe recommendations, culinary education and more.

This dataset comprises a diverse collection of logical reasoning questions,the data covers various question types such as graphic reasoning questions, IQ test questions, thinking logic reasoning questions, graphic visual questions, knowledge encyclopedia image reasoning, detective reasoning type questions.Each question includes the problem statement, answer, and detailed explanation, with chain-of-thought (CoT) reasoning to enhance large language models' logical reasoning capabilities. We strictly adhere to data protection laws and privacy regulations(GDPR, CCPA, PIPL), ensuring secure data collection, storage, and usage while safeguarding user privacy and legal rights.

Korean Test Questions Structured Analysis Processing Data, around 2.4 million questions, contains question types, questions, answers, explanations, etc..For subjects, include [Primary School] Korean, Mathematics, English, Social Studies, Science; [Middle School] Korean, English, Mathematics, Science, Social Studies; [High School] Korean, English, Mathematics, Physics, Chemistry, Biology, History, Geography; question Types indlude single-choice question, fill-in question, true or false question, short answer question, etc. This dataset can be used for large-scale subject knowledge enhancement tasks.

32 million - Science Subjects Questions Text Parsing And Processing Data, including mathematics, physics, chemistry and biology in primary, middle and high school and university. Each questions contain title, answer, parse, type, subject, grade. The dataset can be used for large model subject knowledge enhancement tasks.

1 million - Chinese Code Questions Text Parsing And Processing Data, including c, c++, python, java, javascript multiple language code questions. Each test contains title, answer, parse, and language fields. This data can help model building and solidify code programming skills for better performance in programming tasks.

Japanese OKWAVE Q&A platform Text Parsing and Processing Data, Contains question, answer, category, create_datetime, user, etc, The data is continuously updated. As of the end of April 25, there were 8.4 million questions and 2.3 billion words. 27 million answers and 7.6 billion words; Thanks (the gratitude expressed by the questioner to the responder) 15.5 million pieces, 1.7 billion words; Supplementary explanations amount to 2.1 million pieces, totaling 360 million words, this dataset can be used for tasks such as LLM training, chatgpt

50,000 Sets - Image Editing Data. The types of editing include target removal, target addition, target modification, and target replacement. The editing targets cover scenes such as people, animals, products, plants, and landscapes. In terms of annotation, according to the editing instructions, the targets that need to be edited in the image are cropped and annotated for removal/addition/modification/replacement. The data can be used for tasks such as image synthesis, data augmentation, and virtual scene generation.