Voldy Retard GUide

This is a backup of the rentry.org/voldy guide before the february rehaul

The definitive Stable Diffusion experience ™ (Special thanks to all anons who contributed) ---FEATURE SHOWCASE & HOWTO---

SD News
Japanese guide here 日本語ガイド (JP Resources)
NovelAI FAQ

Minimum requirements:
-16gb ram
-Nvidia Maxwell (GTX 7xx) or newer GPU with at least 2gb vram
-Linux or Windows 7/8/10+
-20gb disk space

--GUIDE--

Step 1: Install Git (page)
-When installing, make sure to check the box for 'Windows Explorer integration -> Git Bash'

Step 2: Clone the WebUI repo to your desired location:
-Right-click anywhere and select 'Git Bash here'
-Enter git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui
(Note: to update, all you need to do is is type git pull within the newly made webui folder)

Step 3: Download your preferred model(s):

  • Official Stable Diffusion 1.4: Huggingface (requires signup) or HERE | (magnet)
  • Waifu Diffusion Final: (SD 1.4 + 680k Danbooru images, heavy anime bias) HERE | (Float32 Ver.)
  • Waifu Diffusion Alpha: (SD 1.4 + 56k Danbooru images, slight anime bias) HERE | (mirror) | (magnet)
  • Trinart2: (SD 1.4 trained for Anime concept art/'Pixiv style') HERE
  • See This page for additional models (Most in beta)

Step 4: Rename your .ckpt file to "model.ckpt", and place it in the /models/Stable-diffusionfolder
-You can have as many models as you want in the folder, "model.ckpt" is just the one it will load by default

Step 5: Install Python 3.10 (Windows 7 ver) (page)
-Make sure to choose "add to PATH" when installing

Step 6 (Optional):
This reduces VRAM, and allows you to generate at larger resolutions or batch sizes for a <10% loss in raw generation speed
(For me, singular results were slightly slower, but generating with a batch size of 4 made each result 25% faster on average)
This is recommended for most users
-Edit webui-user.bat
-Change COMMANDLINE_ARGS= to COMMANDLINE_ARGS=--medvram

Step 7: Launch webui-user.bat, Open it as normal user, not as administrator.

  • Wait patiently while it installs dependencies and does a first time run.
    It may seem "stuck" but it isn't. It may take up to 10-15 minutes.
    And you're done!

Usage

  • Launch webui-user.bat
  • After loading the model, it should give you a LAN address such as '127.0.0.1:7860'
  • Enter the address into your browser to enter the GUI environment
    Tip: Hover your mouse over UI elements for tooltips about what they do
  • To exit, close the CMD window

--NOVELAI SETUP--

Provided in service to freedom of information, testing and research
If you enjoy your results, consider subscribing

Step 1: Follow the main guide above
-(Ignore steps 3 and 4 if you only plan on using the NovelAI model)
Open a git bash by right-clicking inside your main stable diffusion webui folder and type git pullto make sure you're updated

Step 2: Download a Torrent Client if you don't have one already
-Add the following Magnet link:
magnet:?xt=urn:btih:5bde442da86265b670a3e5ea3163afad2c6f8ecc
-Deselect everything except for the the /animefull-final-pruned subfolder (under /stableckpt), and animevae.pt
-(Optional: select desired .pt hypernetworks in the /modules subfolder (These are not used by default in NAI but can provide unique results)

Step 3: Once finished, rename the following files you torrented like so:
animevae.pt >> nai.vae.pt
config.yaml >> nai.yaml
model.ckpt>> nai.ckpt

Step 4: Place all 3 files into /stable-diffusion-webui/models/Stable-diffusion

Step 5 (Optional): If you want to launch NovelAI by default, do the following
-Edit webui-user.bat in notepad and add the NAI .ckpt:
COMMANDLINE_ARGS=--ckpt nai.ckpt
Otherwise, you can just select it within the WebUI dropdown

Hypernetworks (Optional):
Using Hypernetwork .pt files can provide unique changes to your NAI output depending on which one you use
To enable them:
-Create /stable-diffusion-webui/models/hypernetworksfolder if it doesn't exist already
-Paste your .pt modules (anime, aini, furry etc) into the hypernetworks folder
-Reload the WebUI
-In the 'Settings' tab, choose your .pt under Stable Diffusion finetune hypernetwork and hit apply

Replicating NovelAI defaults

It is possible to create outputs identical to NovelAI's current subscription service by doing the following:

Standard (Euler)
-Set the sampler to Euler (Not Euler A)

-Use 28 Steps

-Set CFG Scale to 11

-Use masterpiece, best quality at the beginning of all positive prompts

-Use nsfw, lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry, artist name as the negative prompt
(nsfw is optional, and toggled on the site)

-In the Settings tab, change Ignore last layers of CLIP model to 2 and apply

Euler-A Defaults
If you want to replicate NovelAI Euler_a results, you must do the following alongside the defaults above:
-Under Sampler Parameters in settings, set 'ETA Noise Seed Delta' to 31337

And you should be ready to prompt!

Testing accuracy

The easiest way to test if your NovelAI setup is functioning properly is to attempt replicating a result from NovelAI itself:
For this example we'll be using best girl:
Asuka
Sampler: Euler
Seed: 2870305590
CFG: 12
Resolution: 512x512
Prompt: masterpiece, best quality, masterpiece, asuka langley sitting cross legged on a chair
Negative Prompt: lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts,signature, watermark, username, blurry, artist name
(Double check you copied the prompts exactly!)
Note: You may see very slight variation if you are using an optimization such as lowvram or xformers, but it should still be 95% similar
Troubleshooting incorrect Asukas

NovelAI resources

--TI, HYPERNETWORKS, AND LORAS--

It's possible to fine-tune your Stable Diffusion experience beyond just the model itself by using 'add-ons' of pre-trained data
There are 3 major ways this is done:

Textual Inversion (TI)

Small files typically used to introduce new concepts and characters to Stable Diffusion
They are passively loaded into memory on startup and can be activated by using their name in any prompt
Comes in either .pt or .bin file format
How to use TIs:

  • Move your Textual Inversion files into stable-diffusion-webui/embeddings
  • Reload your WebUI
  • Use the name of the file normally without it's extension in your prompt
    eg "1girl, blonde hair, in the style of arcane"

Hypernetworks

Larger packs of trained data that can be loaded on top of any given model, affects all results regardless of prompt while active
Often used for replicating distinct artstyles & aesthetics
Only one hypernetwork can be active at a time
Comes in .pt file format
How to use Hypernetworks:

  • Move your Hypernetwork .pt files into stable-diffusion-webui/models/hypernetworks
  • Create the folder if it doesn't exist
  • Reload WebUI and navigate to settings
  • Under the 'Stable Diffusion' tab, select the Hypernetwork dropdown
  • Select your Hypernetwork and then hit 'Apply Settings' at the top
  • Your Hypernetwork is now active!

LoRAs (Low Rank Adaptation)

Advanced hypernetworks that can be mixed with one another, their strength can be adjusted dynamically.
Comes in .safetensor file format
How to use LoRAs:

  • Navigate to the 'Extensions' tab in the WebUI
  • Select 'Install from URL'
  • Paste the following link in the URL field:
    https://github.com/kohya-ss/sd-webui-additional-networks and hit Install
  • Move your .safetensors files into stable-diffusion-webui/extensions/sd-webui-additional-networks/models/lora
    (create the /lora folder it doesn't exist)
  • Navigate back to 'Extensions' tab in WebUI
  • Hit 'Apply and restart UI' under
  • On your generation tab, there should be a new dropdown which says 'Additional Networks'
  • Check 'Enable' and select your LoRA models to use them in your generation
  • Use the slider to adjust LoRA strength, between 0.3 and 0.8 is recommended

Where do I download these?
All three types of add-ons can be found on CivitAI
Use the search filter to find whichever you want

--RUNNING ON 4GB (And under!)--

These parameters are also useful for regular users who want to make larger images or batch sizes!
It is possible to drastically reduce VRAM usage with some modifications:

  • Step 1: Edit webui-user.bat
  • Step 2: After COMMANDLINE_ARGS= , enter your desired parameters:
    Example: COMMANDLINE_ARGS=--medvram
  • If you have 4GB VRAM and want to make 512x512 (or maybe larger) images,
    use --medvram.
  • If you have 2GB VRAM,
    use --lowvram

If you are getting 'Out of memory' errors on either of these, add --always-batch-cond-uncond to the other arguments

NOTES:

  • If you get a green/black screen instead of generated pictures, you have a card that doesn't support half precision floating point numbers (known problem on 16xx cards):
    You must use --precision full --no-half in addition to other flags, and the model will take much more space in VRAM
    If you are using a .vae file, you must also add --no-half-vae
  • Make sure to disable hardware acceleration in your browser and close anything which might be occupying VRAM if you are getting out-of-memory errors, and possibly remove GFPGAN (if you have it)

--ALTERNATE GUIDE (Conda)--

(You can try this method if the traditional install isn't working)

  • Follow Steps 1-4 on the main guide above
  • Download Miniconda HERE. Download Miniconda 3
  • Install Miniconda in the default location. Install for all users.
    Uncheck "Register Miniconda as the system Python 3.9" unless you want to
  • Open Anaconda Prompt (miniconda3)
  • In Miniconda, navigate to the /stable-diffusion-webui folder wherever you downloaded using "cd" to jump folders.
    (Or just type "cd" followed by a space, and then drag the folder into the Anaconda prompt.)
  • Type the following commands to make an environment and install the necessary dependencies:
  • conda create --name qwe
    (You can name it whatever you want instead of qwe)
  • conda activate qwe
  • conda install python
  • conda install git
  • webui-user.bat
    (Note: it may seem like it's stuck on "Installing torch" in the beginning. This is normal and should take 10-15 minutes)
    It should now be ready to use

Usage

  • Navigate to /stable-diffusion-webui in Miniconda
  • Type conda activate qwe
    (You will need to type 'conda activate qwe' every time you wish to run webui)
  • Type webui-user.bat
  • After loading the model it should give you a LAN address such as '127.0.0.1:7860'
    Enter the address into your browser to enter the GUI environment

--LINUX INSTALLATION--

Step 1: Install dependencies

  • Debian-based:
    sudo apt install wget git python3 python3-venv
  • Red Hat-based:
    sudo dnf install wget git python3
  • Arch-based:
    sudo pacman -S wget git python3

Step 2: To install in /home/$(whoami)/stable-diffusion-webui/, run:
bash <(wget -qO- https://raw.githubusercontent.com/AUTOMATIC1111/stable-diffusion-webui/master/webui.sh)

--TROUBLESHOOTING--

IF YOUR PROBLEM ISN'T LISTED HERE:

Try updating your requirements, this can correct many obscure issues across SD
-1: Open an administrator powershell window in \stable-diffusion-webui\
(Windows shortcut: Hold ALT, then press F, S, then A)
-2: Enter Set-ExecutionPolicy Unrestricted and hit Yes
-3: Enter .\venv\Scripts\activate
-4: Enter pip install -r requirements.txt
(Note- it may take 20-30 minutes to finish, be patient)
-5: After requirements are installed, type Set-ExecutionPolicy Restricted for security reasons

  • Make sure your folder paths do not have spaces
  • If you get Git is not recognized as an internal or external command when launching, your Git is not set to PATH (Common issue on W7)
    -1: Open the start menu and search for "Edit system environment variables", open it
    -2: Click "Environment Variables"
    -3: Find Path under System Variables and double click it
    -4: Add your Git path:
    -W10: With the "New" button in the PATH editor, add C:\Program Files\Git\bin\ and C:\Program Files\Git\cmd\ to the end of the list.
    -W7: At the end of "Variable value", insert a ; followed by your Git path:
    eg. ;C:\Program Files\Git\bin\;C:\Program Files\Git\cmd\. Do not put a space between ; and the entry.
    -Git should now be recognized inside CMD!
  • If you get launch.py error, unrecognized arguments when trying to use the --ckpt flag, try using the full relative path for it in webui-user.bat
    eg. COMMANDLINE_ARGS= --ckpt ./models/Stable-diffusion/nai.ckpt
  • "I git pulled to update and something broke!"
    Naturally since many new features are introduced, there may be some instability. Follow These instructions to revert to a previous build
  • If you are getting a winerror when installing, or you feel you broke something and want to reinstall from scratch,
    delete these directories: venv, repositories and try again
  • If you are getting Python not found as an error, you may need to manually set your PATH in webui-user.bat:
    see "Setting Python PATH" under 'Howto Extras' below for instructions
  • (img2img) if you get RuntimeError: Sizes of tensors must match, you need to change the resolution of your input image
  • Make sure you have the latest CUDA toolkit and GPU drivers you can run
  • If you get Torch is not able to use GPU, you may have to download Python 3.7 instead
  • if your version of Python is not in PATH (or if another version is)
    create or modify webui.settings.bat in /stable-diffusion-webuifolder
    add the line set PYTHON=python to say the full path to your python executable: set PYTHON=B:\soft\Python310\python.exe
    You can do this for python, but not for git.
  • The installer creates a python virtual environment, so none of installed modules will affect your system installation of python if you had one prior to installing this.
  • To prevent the creation of virtual environment and use your system python, edit webui.bat replacing set VENV_DIR=venv with set VENV_DIR=
  • webui.bat installs requirements from files requirements_versions.txt, which lists versions for modules specifically compatible with Python 3.10.6.
    If you choose to install for a different version of python, editing webui.bat to have set REQS_FILE=requirements.txt instead of set REQS_FILE=requirements_versions.txt may help (but I still reccomend you to just use the recommended version of python).
  • If you get a green/black output instead of generated pictures, you have a card that doesn't support half precision floating point numbers (known problem on 16xx cards):
    -edit webui-user.bat
    -Modify line 6 to COMMANDLINE_ARGS=--precision full --no-halfalong with any other flags you wish to add
    If you are using a .vae file, you must also add --no-half-vae
    Unfortunately, the model will take much more space in VRAM-
    So it is recommended to use flags like --medvram in combination with it
  • If your output is a jumbled rainbow mess your image resolution is set TOO LOW
  • Having too high of a CFG level will also introduce color distortion, your CFG should be between 5-15
  • On older systems, you may have to change cudatoolkit=11.3 to cudatoolkit=9.0
  • Make sure your installation is on the C: drive
  • This guide is designed for NVIDIA GPUs only, as stable diffusion requires cuda cores.
    AMD users should try THIS GUIDE

--TIPS--

  • You can quickly switch between your downloaded .ckpt files within the WebUI
  • Unlike base SD, NovelAI can generate images natively up to 768x768 without any distortion
  • Otherwise, if you are generating images significantly larger than 512x512 in SD, make sure to check Highres, fix for the best results.
    if you don't, 'cloning' distortion may begin appearing (multiple faces, arms, etc)
    +Lower denoising strength seems to work best (I used 0.5)
  • Even with the available fix, it is still recommended to generate in 512x512 for the most accurate results, as the non-NovelAI models were trained on 512x images
  • The Waifu model and normal .ckpt have their own pros and cons;
    Non-anime promps done with the waifu .ckpt will be biased toward anime stylization, making realistic faces and people more difficult unless you merge it with another model
  • Do not use the --medvram or --lowvram argument when training! Results will be highly inferior
  • nai.yaml may not be necessary to achieve 1:1 with NovelAI results
  • Use ((( ))) around keywords to increase their strength and [[[ ]]] to decrease their strength
  • Unlike other samplers, k_euler_a can generate high quality results from low steps.
  • Save prompt as style allows you to save a prompt as an easily selectable output. A box to select will appear to the left of Roll after you save your first style, allowing you to make a selection. Prompts can be deleted by accessing styles.csv
    (This can be helpful if you find a combination that generations really good images and want to repeatedly use it with varied subjects.)
  • You can drag your favorite result from the output tab on the right back into img2img for further iteration
  • The k_euler_a and k_dpm_2_a samplers give vastly different, more intricate results from the same seed & prompt
    However their results are not consistent throughout steps. Other samplers provide more predictable, linear refinement with more steps
  • The seed for each generated result is in the output filename if you want to revisit it
  • Using the same keywords as a generated image in img2img produces interesting variants
  • It's recommended to have your prompts be at least 512 pixels in one dimension, or a 384x384 square at the absolute smallest
    Anything smaller will have heavy distortion
  • CLIP interrogator takes up a lot of space (8gb), you might not want to select it if you don't plan on using it frequently
  • Try Low strength (0.3-0.4) + High CFG in img2img for interesting outputs
  • You can use Japanese Unicode characters in prompts

--HOWTO EXTRAS--

-----Running on CPU----- It is possible to run the full WebUI on a CPU instead of a GPU, but it is very sluggish
If you want a faster but very basic CPU experience, try the Openvino version
Otherwise:

  • Follow the main Guide
  • Modify these 2 lines under def prepare_environment like so:
  • torch_command = os.environ.get('TORCH_COMMAND', "pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cpu")
  • commandline_args = os.environ.get('COMMANDLINE_ARGS', "--skip-torch-cuda-test --precision full --no-half")
  • Launch webui-user.bat like normal

-----Launching Different Models----- If you have multiple models installed and you want to launch from another conveniently, you can make another .bat

  • Make a copy of webui-user.bat and name it whatever you want
  • After COMMANDLINE_ARGS=, add --ckpt followed by the desired model to your launch parameters:
    eg: COMMANDLINE_ARGS=--ckpt wd-v1-2-full-emma.ckpt
    You can also select a different model while in the webUI, under the settings tab

-----Changing UI Defaults----- After running once, a ui-config.json file appears in the webui directory:
Edit values to your liking and the next time you launch the program they will be applied.

-----Running Online or through LAN----- Edit webui-user.bat and add the necessary parameters after COMMANDLINE_ARGS=, along with any existing parameters you have

  • Use --listen to make the server listen to network connections. This will allow devices on your local network to access the UI, and if you configure port forwarding, also computers on the internet.
  • Use --share option to run online. You will get a xxx.app.gradio link. This is the intended way to use the program in collabs.
  • Use --port xxxx to make the server listen on a specific port, xxxx being the wanted port. Remember that all ports below 1024 needs root/admin rights, for this reason it is advised to use a port above 1024. Defaults to port 7860 if available.
  • Use --share --gradio-auth username:password to add shared authentication
    Optionally, you can provide multiple sets of usernames and passwords separated by commas (user1:pw1, user2:pw2).

-----Setting Python PATH----- Sometimes, you may need to manually add your Python directory to PATH:

  • Find the location of your Python install
    it should be something along the lines of C:\Users\you\AppData\Local\Programs\Python
  • Open the folder and shift+right click python.exe
    then click 'copy as path'
  • Edit webui-user.bat
    paste the path you copied after PYTHON= (keeping quotes), and save

-----Auto-update----- Note: This only applies to those who used git clone to install the repo
You can set your script to automatically update by editing webui-user.bat
Add git pull one line above call webui.bat
Save

-----X/Y Plot----- Although most features are relatively self explanatory to use, the X/Y plot script can be particularly obtuse to understand, notably the "S/R" option

  • The S/R prompt Searches the whole prompt for the first entry in the the comma separated values field and Replaces all occurrences of the first word with with one entry from the values Prompt S/R field on every iteration.
  • The iterations of course also happen for every value of the other type field.
  • The keyword will also be iterated, so using something like "red, white, blue" will result in issues when your prompt also features "reddit gayfurs".

-----Setting Different Output Location----- -Copy the text Here and save it as output.bat, Move it to wherever you want your images to output to.
Run it, and it will create the appropriate sub-folders. You can delete the .bat after this is complete.
-Go to the Settings tab of the UI and assign your new file locations accordingly. Once you’ve assigned the locations, make sure to hit Apply Settings
It is also recommended to enable the following setting if you want your outputs to be organized
-[x] When writing images/grids, create a directory with name derived from the prompt

-----GFPGAN----- GFPGAN is used for correcting realistic faces, it was replaced with CodeFormer face correction which comes with the main install and is generally better.
To install GFPGAN, download and place GFPGANv1.3.pth into the main webUI directory

--PRUNING A .CKPT--

'Unpruned' models can be up to 7gb due to redundant training data,
but it can be reduced to 3.6gb without any loss of quality, reducing ram usage and loading time
(The original model is not lost, a new pruned copy is made)
NOTE: You should only do this after running webui-user.bat at least once

  • Place the .ckpt file you wish to prune in your main /stable-diffusion-webui folder
  • Copy https://raw.githubusercontent.com/harubaru/waifu-diffusion/main/scripts/prune.py
    Delete line 6 and 8
    Save as prune.py
    Save as 'all files' in your main /stable-diffusion-webui folder
  • Edit the last line in prune.py to the name of your ckpt:
    eg. prune_it('wd-v1-2-full-emma.ckpt') and save
  • Copy and save the script for launching prune.py HERE
    Save it as prune.bat in your main /stable-diffusion-webui folder
    Save as 'all files'
    (This loads venv and torch dependencies into memory before running prune.py)
  • Run prune.bat
    The pruning process may take a few minutes
    Afterward, you should now have a pruned .ckpt alongside your normal one

--SAFE UPDATING--

The AUTOMATIC1111 repo is what we call bleeding edge, which means that although new features are added rapidly, it's
not uncommon for new bugs to come along with them.
The good thing is, git pull updates are reversible if something ever breaks
Here's how you can update without taking a risk:

  • Open a git bash in your main Stable Diffusion folder
  • Enter git rev-parse --short HEADto get the hash of your current version. Write it down
    It should be a 7 character string like 'cc58036'
  • Update normally by typing git pull

If the newest version works fine, great!
If you need to revert, all you have to do is type git checkout followed by your previous version hash
eg. git checkout 7edd58d

--OUTPAINTING--

(9/17) A new and improved outpainting script has been added to the webUI!
Make sure to use git pullso you can update to the latest version
To use, go to img2img and select "Outpainting mk2" from the Script dropdown menu
Recommended parameters (Further testing is needed)
Steps: 85-100
Sampler: Euler a
CFG Scale: 7.5
Denoising Strength: 0.8
Width: Same as source image
Height: Same as source image
Pixels to expand: 128-256
Mask Blur: 10-25
Fall-off exponent: 1-2
Color variation: 0.05
Tips

  • Make sure your width and height are the same or close to the source image resolution,
    otherwise your outpainting results will be incoherent
  • Don't feel locked into these parameters, tweaking is highly encouraged
    they are just a rough approximation of what seemed to work best for me through a few minutes of testing
  • The higher the mask blur, the more 'seamless' results tend to be (to an extent)
    but if it's too high, deformed distortions occur

--W7 HELP--

On Windows 7, you may get "api-ms-win-core-path-l1-1-0.dll is missing" as an error when trying to follow this guide.
This is because many modern programs and frameworks require a system file only present in newer versions of Windows.
Luckily, it has been backported to be compatible with W7, and can be downloaded HERE (Github page)
Upzip and copy the x86 .dll into C:\Windows\SysWOW64 and the x64 .dll into C:\Windows\System32 and reboot, then you should be good to go
If you do not get that error, then you do not need to do this.

--MISC--

--OLD MODEL--
The original v1.3 leaked model from June can be downloaded here:
https://drinkordiecdn.lol/sd-v1-3-full-ema.ckpt
Backup Download: https://download1980.mediafire.com/3nu6nlhy92ag/wnlyj8vikn2kpzn/sd-v1-3-full-ema.ckpt
Torrent Magnet: https://rentry.co/6gocs

--OLD GUIDE--
Voldy guide pre-Table of Contents (9/15) https://rentry.org/voldyold
The original hlky guide (replaced as of 9/8/22) is here: https://rentry.org/GUItard
Japanese hlky guide https://news.livedoor.com/article/detail/22794512/
The original guide (replaced as of 8/25/22) is here: https://rentry.org/kretard

APPROXIMATE RENDER TIME BY GPU (50 steps) Time
SAMPLER COMPARISON Sampler Comparison

Edit
Pub: 16 Feb 2023 04:53 UTC
Edit: 16 Feb 2023 04:53 UTC
Views: 3029