Cones-V2
Cones 2 provides an efficient method for image synthesis through the use of residual embeddings, allowing customizable representation of multiple subjects. This open-source project enables fine-tuning of text-to-image diffusion models like Stable Diffusion, requiring minimal storage of only 5 KB per subject. The layout guidance sampling feature facilitates the arrangement of multiple subjects with ease. The project details efficient techniques for controlling image aesthetics, with synthesized results demonstrating variety across different categories such as scenes and pets. Learn about this innovative approach for personalized image creation in a resource-efficient manner.
