ProFusion is a new framework for customized text-to-image generation that preserves fine-grained image details without using regularization, as proposed in the paper. ProFusion includes PromptNet, an encoder network, and Fusion Sampling, a method that generates customized images based on a single user-provided image and text requirements. The paper explains how ProFusion works and provides experiments demonstrating its superior performance compared to existing approaches, while still meeting additional user-defined requirements.
StyleDrop is a technology that generates images in any desired style using text-to-image transformer, Muse. The technology captures nuances of user-provided styles such as design patterns and colour schemes. StyleDrop works by fine-tuning a few trainable parameters and improves the quality of generated images via iterative training with human or automated feedback. The technology can generate high-quality images from text prompts, and style descriptors are added during training and synthesis to improve the results. StyleDrop is easy to use and can be trained with brand assets. It can be used to generate alphabets with consistent styles in a single reference image. StyleDrop on Muse outperforms other methods in style-tuning for text-to-image models.
Safe & Stable is a user-friendly tool designed to convert stable diffusion checkpoint files (.ckpt) to the safer and more secure .safetensors format for tensor storage. This new format enhances security by preventing malicious Python code while improving performance during model loading on both CPUs and GPUs. The tool's graphical interface simplifies file selection and monitors conversion progress. Although the initial conversion still requires .ckpt data, future models will be distributed exclusively in the .safetensors format, eliminating the need for scanning or converting from potentially harmful pickle files.
The text introduces Civitai, a platform that allows users to share and discover resources for creating AI art. Civitai provides users with custom models that they can train using their own data or download models created by other users. Models are machine learning algorithms that have been trained to generate art or media in a particular style. Users can use these models with AI art software to create unique works of art. Civitai's community is constantly sharing new and interesting models, making it a vibrant and supportive community of AI artists.
Guide on using Dreambooth for dataset collection and basic Dreambooth settings. The author suggests fine-tuning Stable Diffusion 2.0 and recommends using xformers with a 512x512 base model. The article emphasizes the importance of high-quality samples in dataset creation and advises cropping and resizing images into 512x512 squares. The author recommends avoiding fan art or different styles unless aiming for style fusion. The article warns against using real images as reg images and suggests using class images instead. Finally, the author recommends using 100 steps per sample image for dataset training.
The HuggingFace DreamBooth library browser currently contains 204 DreamBooth models. To use these models with AUTOMATIC1111's SD WebUI, users must convert them by downloading the model archive and using a script to create a .cktp file.
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