"Sampling steps":"How many times to improve the generated image iteratively; higher values take longer; very low values can produce bad results",
"Sampling method":"Which algorithm to use to produce the image",
"GFPGAN":"Restore low quality faces using GFPGAN neural network",
"Euler a":"Euler Ancestral - very creative, each can get a completely different picture depending on step count, setting steps higher than 30-40 does not help",
"DDIM":"Denoising Diffusion Implicit Models - best at inpainting",
"UniPC":"Unified Predictor-Corrector Framework for Fast Sampling of Diffusion Models",
"DPM adaptive":"Ignores step count - uses a number of steps determined by the CFG and resolution",
"Batch count":"How many batches of images to create (has no impact on generation performance or VRAM usage)",
"Batch size":"How many image to create in a single batch (increases generation performance at cost of higher VRAM usage)",
"GFPGAN":"Restore low quality faces using GFPGAN neural network",
"Euler a":"Euler Ancestral - very creative, each can get a completely different picture depending on step count, setting steps higher than 30-40 does not help",
"DDIM":"Denoising Diffusion Implicit Models - best at inpainting",
"UniPC":"Unified Predictor-Corrector Framework for Fast Sampling of Diffusion Models",
"DPM adaptive":"Ignores step count - uses a number of steps determined by the CFG and resolution",
"Batch count":"How many batches of images to create (has no impact on generation performance or VRAM usage)",
"Batch size":"How many image to create in a single batch (increases generation performance at cost of higher VRAM usage)",
"CFG Scale":"Classifier Free Guidance Scale - how strongly the image should conform to prompt - lower values produce more creative results",
"Seed":"A value that determines the output of random number generator - if you create an image with same parameters and seed as another image, you'll get the same result",
"\u{1f3b2}\ufe0f":"Set seed to -1, which will cause a new random number to be used every time",
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@@ -40,7 +40,7 @@ titles = {
"Inpaint at full resolution":"Upscale masked region to target resolution, do inpainting, downscale back and paste into original image",
"Denoising strength":"Determines how little respect the algorithm should have for image's content. At 0, nothing will change, and at 1 you'll get an unrelated image. With values below 1.0, processing will take less steps than the Sampling Steps slider specifies.",
"Skip":"Stop processing current image and continue processing.",
"Interrupt":"Stop processing images and return any results accumulated so far.",
"Save":"Write image to a directory (default - log/images) and generation parameters into csv file.",
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@@ -96,7 +96,7 @@ titles = {
"Add difference":"Result = A + (B - C) * M",
"No interpolation":"Result = A",
"Initialization text":"If the number of tokens is more than the number of vectors, some may be skipped.\nLeave the textbox empty to start with zeroed out vectors",
"Initialization text":"If the number of tokens is more than the number of vectors, some may be skipped.\nLeave the textbox empty to start with zeroed out vectors",
"Learning rate":"How fast should training go. Low values will take longer to train, high values may fail to converge (not generate accurate results) and/or may break the embedding (This has happened if you see Loss: nan in the training info textbox. If this happens, you need to manually restore your embedding from an older not-broken backup).\n\nYou can set a single numeric value, or multiple learning rates using the syntax:\n\n rate_1:max_steps_1, rate_2:max_steps_2, ...\n\nEG: 0.005:100, 1e-3:1000, 1e-5\n\nWill train with rate of 0.005 for first 100 steps, then 1e-3 until 1000 steps, then 1e-5 for all remaining steps.",
"Clip skip":"Early stopping parameter for CLIP model; 1 is stop at last layer as usual, 2 is stop at penultimate layer, etc.",
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@@ -113,38 +113,38 @@ titles = {
"Discard weights with matching name":"Regular expression; if weights's name matches it, the weights is not written to the resulting checkpoint. Use ^model_ema to discard EMA weights.",
"Extra networks tab order":"Comma-separated list of tab names; tabs listed here will appear in the extra networks UI first and in order lsited.",
"Negative Guidance minimum sigma":"Skip negative prompt for steps where image is already mostly denoised; the higher this value, the more skips there will be; provides increased performance in exchange for minor quality reduction."