mcmonkey4eva

{
    "sdxlofficial/anime": {
        "author": "local",
        "title": "sdxlofficial/anime",
        "description": "SDXL Official \"Anime\" Style",
        "preview_image": "data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAMCAgICAgMCAgIDAwMDBAYEBAQEBAgGBgUGCQgKCgkICQkKDA8MCgsOCwkJDRENDg8QEBEQCgwSExIQEw8QEBD/2wBDAQMDAwQDBAgEBAgQCwkLEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBD/wAARCAEAAQADAREAAhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQAAAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWmp6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEAAwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSExBhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElKU1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAI

mcmonkey4eva

These are the precise settings and commands I used (minus filenames) for my reddit post https://www.reddit.com/r/StableDiffusion/comments/14jck90/finetuning_sdxl_on_an_rtx_2070_consumer_tier_gpu/

I was at the time running this version of Kohya's trainer (now very outdated): https://github.com/kohya-ss/sd-scripts/tree/747af145ed32eb85205dca144a4e49f25032d130

Some edits were made between runs, this is the lastmost settings I had.

This was ran on an RTX 2070 within 8 GiB VRAM, with latest nvidia drivers. The VRAM limit was burnt a bit during the initial VAE processing to build the cache (there have been improvements since such that this should no longer be an issue, with eg the bf16 or fp16 VAE variants, or tiled VAE).

This was ran on Windows, so a bit of VRAM was used by the OS. You'd be safer on Linux.

mcmonkey4eva

This is a bare minimum 10-minute slap together. It doesn't work well and I don't intend to maintain it, it's just posted for if you want to look at it or reference it for a slap-together of your own.

I absolutely did not do things properly when making this.

mcmonkey4eva

grid:
    title: Dynamic Threshold
    author: mcmonkey
    description: Testing of the Dynamic Thresholding (CFG Scale Fix) extension
    format: jpg
    params:
        dynamicthresholdenable: true
axes:
    prompt:
        title: prompt

mcmonkey4eva

{
  "__metadata__": {
    "format": "pt"
  },
  "alphas_cumprod": {
    "dtype": "F32",
    "shape": [
      1000
    ],
    "data_offsets": [

mcmonkey4eva

lexica.art scraper

• 1: open https://lexica.art/
• 2: open browser console
• 3: paste in the JavaScript, hit enter
• 4: expand the output and copy it to a text file
• 5: optionally, repeat with multiple sets of pages
• 6: Save the .cs and .csproj files together in a folder, open the .csproj in Visual Studio
• 7: Edit the run(... inputs to your file paths
• 8: Run it

mcmonkey4eva

// Toss this into browser console after loading all guild data locally. It's a mess, yaehp.
var out = "";

Array.prototype.forEach.call(document.getElementsByClassName('leaderboardPlayersList')[0].children[0].children, function(elem) {
    console.log("try " + elem.textContent);
    var userData = elem.children[0].children[0];
    var statData = elem.children[0].children[1];
    var avatarData = userData.children[1].children[0].src;
    var nameData = userData.children[2].textContent.replaceAll('`', '_');
    var xpData = statData.children[1].children[1].textContent;

mcmonkey4eva

Please review the Denizen contributing document at https://github.com/DenizenScript/Denizen-For-Bukkit/blob/release/CONTRIBUTING.md#you-agree-by-contributing

You agree to that document by signing.

You further agree that any updates to that agreement are applicable to your future contributions,

and that you will keep yourself aware of any updates to the document prior to sending any future contribution.

mcmonkey4eva

Please review the FreneticGameEngine contributing document at https://github.com/FreneticLLC/FreneticGameEngine/blob/master/CONTRIBUTING.md#you-agree-by-contributing

You agree to that document by signing.

You further agree that any updates to that agreement are applicable to your future contributions,

and that you will keep yourself aware of any updates to the document prior to sending any future contribution.

mcmonkey4eva

Please review the Voxalia contributing document at https://github.com/FreneticLLC/Voxalia/blob/master/CONTRIBUTING.md#you-agree-by-contributing

You agree to that document by signing.

You further agree that any updates to that agreement are applicable to your future contributions,

and that you will keep yourself aware of any updates to the document prior to sending any future contribution.