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a ((word)) - increase attention to word by a factor of 1.21 (= 1.1 * 1.1).a (word) - increase attention to word by a factor of 1.1.Using () in the prompt increases the model's attention to enclosed words, and decreases it.
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A larger denoising strength is problematic due to the fact SD upscale works in tiles, as the diffusion process is then unable to give attention to the image as a whole.Denoising strength: 0.2, can go up to 0.4 if you feel adventurous.Because of overlap, the size of the tile can be very important: 512x512 image needs nine 512x512 tiles (because of overlap), but only Width and height, and UI's width and height sliders specify the size of individual tiles. The input image will be upscaled to twice the original To use this feature, select SD upscale from the scripts dropdown selection (img2img tab). It also has an option to let you do the upscaling part yourself in an external program, and just go through tiles with img2img. Upscale image using RealESRGAN/ESRGAN and then go through tiles of the result, improving them with img2img. It should only be used if VRAM bound, or in tandem with something like ControlNet + the tile model. This is not the preferred method of upscaling, as this causes SD to lose attention to the rest of the image due to tiling. A batch with multiple different prompts will only use the LoRA from the first prompt. The text for adding LoRA to the prompt,, is only used to enable LoRA, and is erased from prompt afterwards, so you can't do tricks with prompt editing like. LoRA cannot be added to the negative prompt. LoRA is added to the prompt by putting the following text into any location:, where filename is the name of file with LoRA on disk, excluding extension, and multiplier is a number, generally from 0 to 1, that lets you choose how strongly LoRA will affect the output. Support for LoRA is built-in into the Web UI, but there is an extension with original implementation by kohya-ss.Ĭurrently, LoRA networks for Stable Diffusion 2.0+ models are not supported by Web UI. A good way to train LoRA is to use kohya-ss. A method to fine tune weights for CLIP and Unet, the language model and the actual image de-noiser used by Stable Diffusion, published in 2021.