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68,750 sets of image editing (reasoning-based editing) data
Image Editing
Reasoning-based Editing
Knowledge-based Editing
Physical Rule-based Editing
68,750 groups in total, among which 62,500 are knowledge-based editing and 6,250 are physics rule editing.The images cover various scenarios, multiple categories, and more.In terms of annotation, the original images are edited according to document instructions to generate effect images; most category data also involves reasoning processes.The matching accuracy between image and text content is no less than 95%.The data can be used for tasks such as virtual scene generation,image synthesis, and data augmentation .
This is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.
Specifications
Data Content
Each data set consists of one original image, one edited/result image (annotated based on edits applied to the original image), one Chinese TXT document, and one English TXT document.
Data Scale
68750 sets in total, of which 62500 are knowledge based editing sets and 6250 are physical rule based editing sets.
Data diversity
Covers a wide range of scenes, multiple categories, and various question types.
Data format
Images in formats such as JPG, etc.; documents in TXT format.
Nexdata’s LLM datasets can support a wide range of large language model development tasks, including pre-training, supervised fine-tuning, instruction tuning, preference optimization, evaluation, and domain-specific model development. Depending on the dataset, data may include text, instruction-response pairs, conversations, question-answer pairs, reasoning data, and other structured or annotated content.
Can Nexdata customize LLM datasets based on our specific model and requirements?
Yes. If our off-the-shelf LLM datasets do not fully match your requirements, Nexdata provides flexible custom data collection, generation, annotation, curation, and quality control services. We can customize datasets based on your target languages, domains, use cases, data formats, task types, volume, and quality requirements to support specific LLM training and evaluation projects.
Can Nexdata provide large-scale and high-quality data for LLM development?
Yes. Nexdata can support large-scale LLM data projects across multiple languages, domains, and data types. Our data services include multi-stage quality control, data cleaning, annotation, validation, and curation to help ensure consistency and usability. For projects requiring data beyond our existing datasets, our customized data services can be scaled according to the required volume, specifications, and delivery schedule.
Specifications
Sample
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