Update hints.js

    "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", 

	"Batch size": "How many image to create in a single batch",

    "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",

    "\u267b\ufe0f": "Reuse seed from last generation, mostly useful if it was randomed",

    "\u{1f3b2}\ufe0f": "Set seed to -1 will set a new random number every time.",

    "\u267b\ufe0f": "Reuse seed from last generation, most useful if it was randomized.",

    "\u{1f3a8}": "Add a random artist to the prompt.",

    "\u2199\ufe0f": "Read generation parameters from prompt or last generation if prompt is empty into user interface.",

    "\u{1f4c2}": "Open images output directory",

    "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.",

    "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.",