"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 to higher than 30-40 does not help",
"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",
"DPM adaptive":"Ignores step count - uses a number of steps determined by the CFG and resolution",
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@@ -74,7 +74,7 @@ titles = {
"Style 1":"Style to apply; styles have components for both positive and negative prompts and apply to both",
"Style 2":"Style to apply; styles have components for both positive and negative prompts and apply to both",
"Apply style":"Insert selected styles into prompt fields",
"Create style":"Save current prompts as a style. If you add the token {prompt} to the text, the style use that as placeholder for your prompt when you use the style in the future.",
"Create style":"Save current prompts as a style. If you add the token {prompt} to the text, the style uses that as a placeholder for your prompt when you use the style in the future.",
"Checkpoint name":"Loads weights from checkpoint before making images. You can either use hash or a part of filename (as seen in settings) for checkpoint name. Recommended to use with Y axis for less switching.",
"Inpainting conditioning mask strength":"Only applies to inpainting models. Determines how strongly to mask off the original image for inpainting and img2img. 1.0 means fully masked, which is the default behaviour. 0.0 means a fully unmasked conditioning. Lower values will help preserve the overall composition of the image, but will struggle with large changes.",
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@@ -92,12 +92,12 @@ titles = {
"Weighted sum":"Result = A * (1 - M) + B * M",
"Add difference":"Result = A + (B - C) * M",
"Learning rate":"how fast should the 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.",
"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.",
"Approx NN":"Cheap neural network approximation. Very fast compared to VAE, but produces pictures with 4 times smaller horizontal/vertical resoluton and lower quality.",
"Approx cheap":"Very cheap approximation. Very fast compared to VAE, but produces pictures with 8 times smaller horizontal/vertical resoluton and extremely low quality.",
"Approx NN":"Cheap neural network approximation. Very fast compared to VAE, but produces pictures with 4 times smaller horizontal/vertical resolution and lower quality.",
"Approx cheap":"Very cheap approximation. Very fast compared to VAE, but produces pictures with 8 times smaller horizontal/vertical resolution and extremely low quality.",
"Hires. fix":"Use a two step process to partially create an image at smaller resolution, upscale, and then improve details in it without changing composition",
"Hires steps":"Number of sampling steps for upscaled picture. If 0, uses same as for original.",
