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Stable UnCLIP 2.1. New stable diffusion finetune (Stable unCLIP 2.1, Hugging Face) at 768x768 resolution, based on SD2.1-768. This model allows for image variations and mixing operations as described in Hierarchical Text-Conditional Image Generation with CLIP Latents, and, thanks to its modularity, can be combined with other models such as KARLO.
No token limit for prompts (original stable diffusion lets you use up to 75 tokens) DeepDanbooru integration, creates danbooru style tags for anime prompts xformers , major speed increase for select cards: (add --xformers to commandline args)
Stable Diffusion is a latent text-to-image diffusion model. Thanks to a generous compute donation from Stability AI and support from LAION, we were able to train a Latent Diffusion Model on 512x512 images from a subset of the LAION-5B database. Similar to Google's Imagen, this model uses a frozen CLIP ViT-L/14 text encoder to condition the ...
Home. w-e-w edited this page on Sep 10, 2023 · 37 revisions. Stable Diffusion web UI is a browser interface for Stable Diffusion based on Gradio library.
Stable Diffusion的模型架构图. 个人感觉这里一个可能的点是怎样优化压缩模型， 采用更激进的下采样策略，同时又能保证压缩模型带来的精度损失在可接受的范围内，来实现更高分辨率的生成。. 举个具体例子，Stable Diffusion的VQGAN目前是将512×512的图像，压缩至64× ...
2024年1月6日 · Install and run with:./webui.sh {your_arguments*} *For many AMD GPUs, you must add --precision full --no-half or --upcast-sampling arguments to avoid NaN errors or crashing.
2024年8月17日 · Training Procedure Stable Diffusion v1-5 is a latent diffusion model which combines an autoencoder with a diffusion model that is trained in the latent space of the autoencoder. During training, Images are encoded through an encoder, which turns images into latent representations.
2023年2月11日 · Below is ControlNet 1.0. Official implementation of Adding Conditional Control to Text-to-Image Diffusion Models. ControlNet is a neural network structure to control diffusion models by adding extra conditions. It copys the weights of neural network blocks into a "locked" copy and a "trainable" copy. The "trainable" one learns your condition.
Stable Diffusion WebUI Forge is a platform on top of Stable Diffusion WebUI (based on Gradio ) to make development easier, optimize resource management, speed up inference, and study experimental features. The name "Forge" is inspired from "Minecraft Forge". This project is aimed at becoming SD WebUI's Forge.
A basic crash course for learning how to use the library's most important features like using models and schedulers to build your own diffusion system, and training your own diffusion model. Loading Guides for how to load and configure all the components (pipelines, models, and schedulers) of the library, as well as how to use different schedulers.
