Update README.md

README.md

@@ -21,7 +21,6 @@ language:
 # Index <a name="index"></a>
 
 * [Introduction](#intro)
-* [Google Colab](#colab)
 * [Local Installation (Windows + Nvidia)](#install)
 * [Getting Started](#start)
    1. [Models](#model)
@@ -48,50 +47,28 @@ Stable Diffusion is a very powerful AI image generation software you can run on
 
 The images you create may be used for any purpose, depending on the used model's license. Whether they are "yours" in a legal sense varies by local laws and is often inconclusive. Neither I or any of the people involved in Stable Diffusion or its models are responsible for anything you make, and you are expressively forbidden from creating illegal or harmful content.
 
-This guide was finished in March 2023 and was last revised in October 2023. One month is like a year in AI time, so hopefully it is still useful by the time you read it.
-
-&nbsp;
-
-# Google Colab <a name="colab"></a>[▲](#index)
-
-The easiest way to use Stable Diffusion is through Google Colab. It borrows Google's computers to use AI, with variable time limitations, usually a few hours every day. You will need at least one Google account and we will be using Google Drive to store your settings and resulting images.
-
-**Revision:** Google Colab now requires a subscription to run Stable Diffusion instances.
-
-If you instead want to run it on your own computer, [scroll down ▼](#install).
-
-1. Open [THIS PAGE](https://colab.research.google.com/drive/1wEa-tS10h4LlDykd87TF5zzpXIIQoCmq).
-
-1. Near the top, click **Copy to Drive**. Wait for the new window to open and close the old one. This is now your personalized colab which will save your settings, and you should open it from your Google Drive from now on. If the original receives an update you'll have to replace yours to benefit from it.
-
-1. Turn on the following options under **Configurations**: `output_to_drive, configs_in_drive, no_custom_theme`. Then, turn on the following options under **Models, VAEs, etc**: `anything_vae`, `wd_vae`, `sd_vae`.
-
-1. If you're already familiar with Stable Diffusion, you may paste links to your desired resources in the `custom_urls` text box. We will add some links later in this guide. Links must be **direct downloads** to each file (ideally from civitai or huggingface), and must be separated by commas.
-
-1. Press the play button to the left, anywhere in the first section of the page labeled **Start 🚀**. Wait a few minutes for it to finish, while a few progress messages appear near the bottom. Then, a **public link** will be created, which you can open in a new tab to start using Stable Diffusion. **Keep the colab tab open!** (On mobile try the trick at the bottom of the colab to keep the tab open)
-
-1. You can now make some decent anime images thanks to the default **Anything 4.5** model. But we can do more. Also, what are all of these options? [Scroll down ▼](#start) to get started.
+This guide was finished in March 2023 and was last revised in March 2024. One month is like a year in AI time, so hopefully it is still useful by the time you read it.
 
 &nbsp;
 
 # Local Installation (Windows + Nvidia) <a name="install"></a>[▲](#index)
 
-To run Stable Diffusion on your own computer you'll need at least 16 GB of RAM and 4 GB of VRAM (preferably 8). I will only cover the case where you are running Windows 10/11 and using an NVIDIA graphics card series 16XX, 20XX or 30XX (though 10XX also work). My apologies to AMD, Linux, and Mac users, but their cases are harder to cover. If you don't meet the hardware requirements, you can just proceed with the Google Colab method [above ▲](#colab).
+To run Stable Diffusion on your own computer you'll need a graphics card. An old one with 2 GB of VRAM might just be enough for slow small images, while 4 GB of VRAM is enough for slow XL generations, and 6 and 8 GB of VRAM being even better. I will only cover the case where you are running Windows 10/11 and using an NVIDIA graphics card series 16XX, 20XX, 30XX, or 40XX (though 10XX also work). My apologies to AMD, Linux, and Mac users, but their cases are harder to cover. If you don't meet the hardware requirements, you may look for online alternatives, which I won't cover anymore.
 
-1. Get the latest release from [this page](https://github.com/EmpireMediaScience/A1111-Web-UI-Installer/releases). 
+1. Get the latest Stable Diffusion Webui Forge installer from [here](https://github.com/lllyasviel/stable-diffusion-webui-forge/releases/download/latest/webui_forge_cu121_torch21.7z). 
 
-1. Run the installer, choose an easy and accessible location to install to, and wait for it to finish.
+1. Unzip the installer in an easy and accessible location, and run `update.bat`.
 
-1. Run the program. You will see a few options. First, turn on **medvram** and **xformers**. You may skip medvram if you have 12 or more GB of VRAM.
+1. After it is done, run `run.bat`. It will continue to install and it will also download a decent AI model for you to use.
 
-1. Click **Launch** and wait for a browser window to open with the interface. It may take a while the first time.
+1. After everything is finished, it will open a window in your browser. If it doesn't automatically do this, you can type `localhost:7860` in your browser window.
 
 1. The page is now open. It's your own private website. The starting page is where you can make your images. But first, we'll go to the **Settings** tab. There will be sections of settings on the left.
     * In the *Stable Diffusion* section, scroll down and increase **Clip Skip** from 1 to 2. This is said to produce better images, specially for anime.
     * In the *User Interface* section, scroll down to **Quicksettings list** and change it to `sd_model_checkpoint, sd_vae`
     * Scroll back up, click the big orange **Apply settings** button, then **Reload UI** next to it.
 
-1. You are more than ready to generate some images, but you only have the basic model available. It's not great, at most it can make some paintings. Also, what are all of these options? See [below ▼](#start) to get started.
+1. You are more than ready to generate some images, but you only have one AI model available, which might not be able to generate what you want. Also, what are all of these options? See [below ▼](#start) to get started.
 
 &nbsp;
 
@@ -102,21 +79,23 @@ If you followed the instructions above, the top of your page should look similar
 
 ![Top](images/top.png)
 
-Here you can select your checkpoint and VAE. We will go over what these are and how you can get some. The colab has additional settings here too, you should ignore them for now.
+Here you can select your checkpoint and VAE. We will go over what these are and how you can get some.
 
 1. **Models** <a name="model"></a>[▲](#index)
 
    The **model**, also called **checkpoint**, is the brain of your AI, designed for the purpose of producing certain types of images. There are many options, most of which are on [civitai](https://civitai.com). But which to choose? These are my recommendations:
-   * For anime, [MeinaMix](https://civitai.com/models/7240/meinamix) and its family of models should serve most purposes very well. I also merged my own model called [Limbo Mix](https://civitai.com/models/155337) which you may try if you'd like.
+   * For anime, [MeinaMix](https://civitai.com/models/7240/meinamix) and its family of models should serve most purposes very well. I also personally enjoy [Based66](https://civitai.com/models/61643/based66).
    * For general art go with [DreamShaper](https://civitai.com/models/4384/dreamshaper), there are few options quite like it in terms of creativity. An honorable mention goes to [Pastel Mix](https://civitai.com/models/5414/pastel-mix-stylized-anime-model), which has a beautiful and unique aesthetic with the addition of anime.
    * For photorealism go with [Deliberate](https://civitai.com/models/4823/deliberate). It can do almost anything, but specially photographs. Very intricate results.
    * The [Uber Realistic Porn Merge](https://civitai.com/models/2661/uber-realistic-porn-merge-urpm) is self-explanatory.
 
-   If you're using the colab in this guide, copy the **direct download link to the file** and paste it in the text box labeled `custom_urls`. Multiple links are separated by commas.
+   Nowadays there are also XL models. They are larger and slower and use more memory, but they can often create better images.
+   * For XL anime, as of March 2024 we use [AutismMix](https://civitai.com/models/288584?modelVersionId=324524).
+   * I have not tried realism in XL yet, so I can't recommend models for those. See what you can find!
 
-   If you're running the program locally, the models normally go into the `stable-diffusion-webui/models/Stable-diffusion` folder.
+   The models normally go into the `webui/models/Stable-diffusion` folder.
 
-   Please note that checkpoints in the format `.safetensors` are safe to use while `.ckpt` **may** contain viruses, so be careful. Additionally, when choosing models you may have a choice between fp32, fp16 and pruned. They all produce the same images within a tiny margin of error, so just go with the smallest file (pruned-fp16). If you want to use them for training or merging, go with the largest one instead.
+   Please note that checkpoints in the format `.safetensors` are safe to use while `.ckpt` **may** contain viruses, so be careful. Additionally, when choosing models you may have a choice between fp32, fp16 and pruned. They all produce the same images within a tiny margin of error, so just go with the smallest file (pruned-fp16).
 
    **Tip:** Whenever you place a new file manually you can either restart the UI at the bottom of the page or press the small 🔃 button next to its dropdown.
 
@@ -124,14 +103,14 @@ Here you can select your checkpoint and VAE. We will go over what these are and
 
    Most checkpoints don't come with a VAE built in. The VAE is a small separate model, which "converts your image into human format". Without it, you'll get faded colors and ugly eyes, among other things.
 
-   If you're using the colab in this guide, you should already have the below VAEs, as I told you to select them before running.
-
    Most people use one of 3 different VAEs:
    * [anything vae](https://huggingface.co/WarriorMama777/OrangeMixs/resolve/main/VAEs/orangemix.vae.pt), also known as the orangemix vae. Used to be the most popular for anime, but it's the least vibrant of all vaes.
    * [vae-ft-mse](https://huggingface.co/stabilityai/sd-vae-ft-mse-original/blob/main/vae-ft-mse-840000-ema-pruned.safetensors), the latest from Stable Diffusion itself. Used by photorealism models and such.
-   * [kl-f8-anime2](https://huggingface.co/hakurei/waifu-diffusion-v1-4/resolve/main/vae/kl-f8-anime2.ckpt), also known as the Waifu Diffusion VAE, it is older and produces more saturated results. 
+   * [kl-f8-anime2](https://huggingface.co/hakurei/waifu-diffusion-v1-4/resolve/main/vae/kl-f8-anime2.ckpt), also known as the Waifu Diffusion VAE, it is older and produces more saturated results.
+  
+   And for SDXL you should use the [sdxl-vae](https://huggingface.co/stabilityai/sdxl-vae/resolve/main/sdxl_vae.safetensors).
 
-   The VAEs normally go into the `stable-diffusion-webui/models/VAE` folder.
+   The VAEs normally go into the `webui/models/VAE` folder.
    
    If you did not follow this guide up to this point, you will have to go into the **Settings** tab, then the **Stable Difussion** section, to select your VAE.
 
@@ -154,7 +133,7 @@ Here you can select your checkpoint and VAE. We will go over what these are and
       * `EasyNegative, worst quality, low quality, normal quality, child, painting, drawing, sketch, cartoon, anime, render, 3d, blurry, deformed, disfigured, morbid, mutated, bad anatomy, bad art`
 
    * **EasyNegative:** <a name="promptneg"></a>The negative prompts above use EasyNegative, which is an *embedding* or "magic word" that encodes many bad things to make your images better. Otherwise you'd have to use a huge negative prompt.
-      * If you're using the colab in this guide you already have this installed. Otherwise, you will have to [download this tiny file](https://huggingface.co/datasets/gsdf/EasyNegative/resolve/main/EasyNegative.safetensors), put it in your `stable-diffusion-webui/embeddings` folder, then go to the bottom of your WebUI page and click *Reload UI*. It will then work when you type that word.
+      * You will have to [download this tiny file](https://huggingface.co/datasets/gsdf/EasyNegative/resolve/main/EasyNegative.safetensors), put it in your `webui/embeddings` folder, then go to the bottom of your WebUI page and click *Reload UI*. It will then work when you type that word.
 
    A comparison with and without these negative prompts including EasyNegative can be seen [further down ▼](#matrixneg).
 
@@ -179,7 +158,7 @@ Here you can select your checkpoint and VAE. We will go over what these are and
    * **CFG Scale:** "Lower values produce more creative results". You should almost always stick to 7, but 4 to 10 is an acceptable range.
    * **Seed:** A number that guides the creation of your image. The same seed with the same prompt and parameters produces the same image every time, except for small details and under some circumstances.
   
-   **Hires fix:** Lets you create larger images without distortion. Often used at 2x scale. When selected, more options appear:
+   **Hires fix:** Lets you create larger images (specially in non-XL models) without distortion. Often used at 2x scale. When selected, more options appear:
    * **Upscaler:** The algorithm to upscale with. `Latent` and its variations produce creative and detailed results, but you may also like `R-ESRGAN 4x+` and its anime version. [More explanation and some comparisons further down ▼](#upscale). 
    * **Hires steps:** I recommend at least half as many as your sampling steps. Higher values aren't always better, and they take a long time, so be conservative here.
    * **Denoising strength:** The most important parameter. Near 0.0, no detail will be added to the image. Near 1.0, the image will be changed completely. I recommend something between 0.2 and 0.6 depending on the image, to add enough detail as the image gets larger, without *destroying* any original details you like.
@@ -212,13 +191,11 @@ Here you can select your checkpoint and VAE. We will go over what these are and
 
 Here are some useful extensions. If you're using the colab in this guide you already have most of these, otherwise I hugely recommend you manually add the first 2:
 * [ADetailer](https://github.com/Bing-su/adetailer) - Improves the faces or other features of your generated images by refining those details.
-* [Image Browser (updated)](https://github.com/AlUlkesh/stable-diffusion-webui-images-browser) - This will let you browse your past generated images very efficiently, as well as directly sending their prompts and parameters back to txt2img, img2img, etc.
+* [Infinite image browser](https://github.com/zanllp/sd-webui-infinite-image-browsing) - This will let you browse your past generated images very efficiently, as well as directly sending their prompts and parameters back to txt2img, img2img, etc.
 * [TagComplete](https://github.com/DominikDoom/a1111-sd-webui-tagcomplete) - Absolutely essential for anime art. It will show you the matching booru tags as you type. Anime models work via booru tags, and prompts without them usually don't work, so knowing them is godmode. Not all tags will work well in all models though, specially if they're rare.
-* [ControlNet](https://github.com/Mikubill/sd-webui-controlnet) - A huge extension deserving of [its own guide ▼](#controlnet). It lets you analyze any image and use it as an referene for your own image. Practically speaking, it can create any pose or environment you want.
-* [Ultimate Upscale](https://github.com/Coyote-A/ultimate-upscale-for-automatic1111) - A script usable from the img2img section to make really large images, where normally you can only go as high as your VRAM allows. See [Ultimate Upscaler ▼](#ultimate).
-* [Two-shot](https://github.com/opparco/stable-diffusion-webui-two-shot) - Normally you can't create more than one distinct character in the same image without them blending together. This extension lets you divide the image into parts; full, left side, right side; allowing you to make nice 2-character images.
 * [Dynamic Prompts](https://github.com/adieyal/sd-dynamic-prompts) - A script to let you generate randomly chosen elements in your image, among other things.
 * [Model Converter](https://github.com/Akegarasu/sd-webui-model-converter) - Lets you convert most 7GB/4GB models down to 2GB, by choosing `safetensors`, `fp16`, and `no-ema`. These pruned models work "almost the same" as the full models, which is to say, there is no appreciable difference due to math reasons. Most models come in 2 GB form nowadays regardless.
+* [ControlNet](#controlnet) and other useful extensions now come preinstalled in Stable Diffusion Webui Forge.
 
 &nbsp;
 
@@ -228,7 +205,7 @@ LoRA or *Low-Rank Adaptation* is a form of **Extra Network** and the latest tech
 
 Loras can represent a character, an artstyle, poses, clothes, or even a human face (though I do not endorse this). Checkpoints are usually capable enough for general work, but when it comes to specific details with little existing examples, you'll need a Lora. They can be downloaded from [civitai](https://civitai.com) or [elsewhere (NSFW)](https://gitgud.io/gayshit/makesomefuckingporn#lora-list) and are usually between 9 MB and 144 MB. Note that bigger Loras are not necessarily better. They come in `.safetensors` format, same as most checkpoints.
 
-Place your Lora files in the `stable-diffusion-webui/models/Lora` folder, or if you're using the colab in this guide paste the direct download link into the `custom_urls` text box. Then, look for the 🎴 *Show extra networks* button below the big orange Generate button. It will open a new section either directly below or at the very bottom. Click on the Lora tab and press the **Refresh** button to scan for new Loras. When you click a Lora in that menu it will get added to your prompt, looking like this: `<lora:filename:1>`. The start is always the same. The filename will be the exact filename in your system without the `.safetensors` extension. Finally, the number is the weight, like we saw [earlier ▲](#promptweight). Most Loras work between 0.5 and 1 weight, and too high values might "fry" your image, specially if using multiple Loras at the same time.
+Place your Lora files in the `webui/models/Lora` folder, or if you're using the colab in this guide paste the direct download link into the `custom_urls` text box. Then, look for the 🎴 *Show extra networks* button below the big orange Generate button. It will open a new section either directly below or at the very bottom. Click on the Lora tab and press the **Refresh** button to scan for new Loras. When you click a Lora in that menu it will get added to your prompt, looking like this: `<lora:filename:1>`. The start is always the same. The filename will be the exact filename in your system without the `.safetensors` extension. Finally, the number is the weight, like we saw [earlier ▲](#promptweight). Most Loras work between 0.5 and 1 weight, and too high values might "fry" your image, specially if using multiple Loras at the same time.
 
 ![Extra Networks](images/extranetworks.png)
 
@@ -338,9 +315,9 @@ Scripts can be found at the bottom of your generation parameters in txt2img or i
 
 # ControlNet <a name="controlnet"></a>[▲](#index)
 
-ControlNet is an extremely powerful recent technology for Stable Diffusion. It lets you analyze information about any previously existing image and use it to guide the generation of your AI images. We'll see what this means in a moment.
+ControlNet is an extremely powerful technology for Stable Diffusion. It lets you analyze information about any previously existing image and use it to guide the generation of your AI images. We'll see what this means in a moment.
 
-If you're using the colab in this guide, you should enable the `all_control_models` option. Otherwise, you should first install the ControlNet [extension ▲](#extensions), then go [here](https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/tree/main) to download some models which you'll need to place in `stable-diffusion-webui/extensions/sd-webui-controlnet/models`. I recommend at least Canny, Depth, Openpose and Scribble, which I will show here.
+If you're using the Webui Forge recommended in this guide, you should already have ControlNet installed. You may need ControlNet models; go [here](https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/tree/main) to download some models which you'll need to place in `webui/extensions/sd-webui-controlnet/models`. I recommend at least Canny, Depth, Openpose and Scribble, which I will show here.
 
 I will demonstrate how ControlNet may be used. For this I chose a popular image online as our "sample image". It's not necessary for you to follow along, but you can download the images and put them in the **PNG Info** tab to view their generation data.
 
@@ -414,9 +391,9 @@ To train a [Lora ▲](#lora) is regarded as a difficult task. However, my new gu
 
 **[🎴 Read my Lora making guide here](https://civitai.com/models/22530)**
 
-You can also train a Lora on your own computer if you have at least 8 GB of VRAM. For that, I will list a few resources below:
+You can also train a Lora on your own computer if you have at least 6 GB of VRAM (or 12 GB of VRAM for XL). For that, I will list a few resources below:
 
-* For training, use [bmaltais' Kohya GUI](https://github.com/bmaltais/kohya_ss). It has all the same settings as my trainer colab and more, so you can follow my guide too. Also there are youtube tutorials available in this link.
+* For training, use [Derrian's Easy Lora trainer](https://github.com/derrian-distro/LoRA_Easy_Training_Scripts). It has all the same settings as my trainer colab and more, so you can follow my guide too. 
 * Also, here's an [angry Lora training guide by ao](https://rentry.org/tohoaifaq#opinionated-lora-guide-for-colab)
 * To collect your images from Gelbooru like in my guide, install [Grabber](https://github.com/Bionus/imgbrd-grabber/releases).
 * To tag your dataset use the [WD1.4 Tagger extension](https://github.com/toriato/stable-diffusion-webui-wd14-tagger) for webui. First add and enable the extension, and restart your entire webui. Then go to the new **Tagger** tab, then **Batch from directory**, and select the folder with your images. Set the output name to `[name].txt` and the threshold at or above 0.35 (this is how closely each tag must match an image to be included). Then **Interrogate** and it will start generating your text files.