https://github.com/AUTOMATIC1111/stable-diffusion-webui/discussions/2017
Part 1 NAI (with all the trackers I can find):
Part 2 NovelAI Leak:
SD RESOURCE GOLDMINE
PSA: Do not use --share in any webui using gradio (like AUTOMATIC1111's webui). Remote code execution exploit discovered. Bad actors will have access to the terminal, can run malicious code, and can generate unsolicited content.
On AUTO's webui, git pull to keep yourself safe. Use the hide_ui_dir_config if you plan on using --share after updating. Set a password.
https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/2571
Colab uses --share by default. It's speculated that a javascript injection could occur. Bad actors using your account for malicious purposes can get it suspended
PSA: Monitor your GPU temps and increase cooling and/or undervolt them if you need to. There have been claims of frying/breaking/worsening GPUs due to high temps. There has been a claim of display kernel errors, but that might be user error.
PSA: Ckpts/hypernetworks/embeddings are not interently safe. They can be pickled/contain malicious code. Use your common sense and protect yourself as you would with any random download link you would see on the internet.
Links are dying. Make sure to save the ones you want before they go down. If you happen to save every link (esp. the embeddings and hypernetworks), upload them somewhere, and get the link to me, I'll add it to the rentry and your name somewhere
Changelog: everything from hdg from the last week (lots of links here and there), the GREAT JAPANESE TOME OF MASTERMINDING ANIME PROMPTS AND IMAGINATIVE AI MACHINATIONS 101 GUIDE, berrymix recipe
TODO: ADD STUFF FROM SDG, cio thing
Editor's note: irl stuff came up that I couldn't ignore, so I've been busy. Updating rentry now. Everything will be slightly out of date until its all updated.
IF YOU HAVE A FILE THAT IS NOT IN THIS LIST, PLEASE GET IT TO ME.
Quicklinks:
- News: https://rentry.org/sdupdates#newsfeed
- Prompting: https://rentry.org/sdupdates#prompting
- Models, Embeddings, and Hypernetworks: https://rentry.org/sdupdates#models-embeddings-and-hypernetworks
- Embeddings: https://rentry.org/sdupdates#embeddings
- Hypernetworks: https://rentry.org/sdupdates#hypernetworks
- DEAD: https://rentry.org/sdupdates#dead
- Training: https://rentry.org/sdupdates#training
- FAQ: https://rentry.org/sdupdates#common-questions-ctrlcmd-f
- Link Dump: https://rentry.org/sdupdates#rentrys-link-dump-will-sort
- Confirmed Drama: https://rentry.org/sdupdates#confirmed-drama
- Unconfirmed Drama: https://rentry.org/sdupdates#unconfirmed-drama
- Fed Bait Information: https://rentry.org/sdupdates#fed-bait-information
- Hall of Fame: https://rentry.org/sdupdates#hall-of-fame
NEWSFEED
10/21 - 10/25
- Optimized dreambooth
- train under 10 minutes without class images on multiple subjects, retrainable-ish model
- https://www.reddit.com/r/StableDiffusion/comments/yd9oks/new_simple_dreambooth_method_is_out_train_under/
- https://github.com/TheLastBen/fast-stable-diffusion
- Hypernetwork structures added
- more numbers = more vram needed = deeper hypernetwork = better results (?)
- Deep hypernetworks are suited for training with large datasets
- Waifu Diffusion 1.4 roadmap:
- Extensions added to AUTOMATIC1111's webui
- Test embeddings before you download them
- UMI AI, a wildcard engine, released
- Free
- Tutorial: https://www.patreon.com/posts/umi-ai-official-73544634
- Discord (SFW and NSFW): https://discord.gg/9K7j7DTfG2
- More info in https://rentry.org/sdupdates#prompting
- Don't forget to git pull to get a lot of new optimizations, if it breaks go backward in commits
10/20
- SD v1.5 released by RunwayML
- Uncensored, legitimate 1.5
- Huggingface: https://huggingface.co/runwayml/stable-diffusion-v1-5
- Tweet: https://twitter.com/runwayml/status/1583109275643105280
- https://nitter.it/runwayml/status/1583109275643105280#m
- https://rentry.org/sdmodels
- Reddit thread: https://www.reddit.com/r/StableDiffusion/comments/y91pp7/stable_diffusion_v15/
- Drama recap: https://www.reddit.com/r/StableDiffusion/comments/y99yb1/a_summary_of_the_most_recent_shortlived_so_far/
- https://rentry.org/sdupdates#confirmed-drama for recap + links
10/19
- Git pull for a lot of new stuff
- theme argument: https://github.com/AUTOMATIC1111/stable-diffusion-webui/commit/665beebc0825a6fad410c8252f27f6f6f0bd900b
- A lot of optimizations
- Layered hypernetworks
- Time left estimation (if jobs take more than 60 sec)
- Minor UI changes
- Runway released new SD inpainting/outpainting model
- Stability AI event recap
- https://www.reddit.com/r/StableDiffusion/comments/y6v0v9/stability_event_happening_now_news_so_far/
- Animation API next week
- DreamStudio Pro in progress (automatic gen of video from music + latent space exploration)
- will fund 100 PHDs this year
- Their cluster is 4000 A100s on AWS and plans to grow 5x-10x next year
- will reduce price of Dreamstudio by half
- Game universes created with AI: https://twitter.com/Plinz/status/1582202096983498754
- Dreambooth GUI: https://github.com/smy20011/dreambooth-gui
- NAI possibly tinkering with their backend based on tests by touhou anons
- better hands
- Unreal Engine 5 SD plugin: https://github.com/albertotrunk/UE5-Dream
- Underreported: You can highlight a part of your prompt and ctrl + up/down to change weights
10/18
- Clarification on censoring SD's next model by the question asker
- https://rentry.org/sdupdates#confirmed-drama
- TLDR: SD will probably release a censored model before releasing their 1.5 model because of legal issues (like with CP)
10/17
- $101 million in funding from Stability AI for opensource and free AI
- xformers degrading quality
- https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/2967
- It's a bug that causes the variance with --xformers
- New trinart model
- Discovered hi-res generations are affected by the video card used
- https://desuarchive.org/g/thread/89259005/#89260871
- TLDR: 3000s series are similar, 2000s and 1000s will vary
10/16
-
Remote code execution exploit discovered 2 days ago
- AUTOMATIC pushed an update to deal with this. Use the hide_ui_dir_config if you plan on using --share after updating. Set a password.
- Gradio fix in progress: https://github.com/gradio-app/gradio/issues/2470
- https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/2571
- https://github.com/AUTOMATIC1111/stable-diffusion-webui/discussions/920
- https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/1576
- https://www.reddit.com/r/StableDiffusion/comments/y56qb9/security_warning_do_not_use_share_in/
- Deforum script released for AUTOMATIC1111's webui
- Google open sourced their prompt-to-prompt method
10/15
- Embeddings now shareable via images
- No need to download .pt files anymore
- To use, finish training an embedding, download the image of the embedding (the one with the circles at the edges), and place it in your embeddings folder. The name at the top of the image is the name you use to call the embedding.
- https://www.reddit.com/r/StableDiffusion/comments/y4tmzo/auto1111_new_shareable_embeddings_as_images/
- Example (2nd and 3rd image): https://www.reddit.com/gallery/y4tmzo
- Stability AI update pipeline (https://www.reddit.com/r/StableDiffusion/comments/y2x51n/the_stability_ai_pipeline_summarized_including/)
- This week:
- Updates to CLIP (not sure about the specifics, I assume the output will be closer to the prompt)
- Clip-guidance comes out open source (supposedly)
- Next week:
- DNA Diffusion (applying generative diffusion models to genetics)
- A diffusion based upscaler ("quite snazzy")
- A new decoding architecture for better human faces ("and other elements")
- Dreamstudio credit pricing adjustment (cheaper, that is more options with credits)
- Discord bot open sourcing
- Before the end of the year:
- Text to Video ("better" than Meta's recent work)
- LibreFold (most advanced protein folding prediction in the world, better than Alphafold, with Havard and UCL teams)
- "A ton" of partnerships to be announced for "converting closed source AI companies into open source AI companies"
- (Potentially) CodeCARP, Code generation model from Stability umbrella team Carper AI (currently training)
- (Potentially) Gyarados (Refined user preference prediction for generated content by Carper AI, currently training)
- (Potentially) CHEESE (some sort of platform for user preference prediction for generated content)
- (Potentially) Dance Diffusion, generative audio architecture from Stability umbrella project HarmonAI (there is already a colab for it and some training going on i think)
- This week:
- Animation Stable Diffusion:
- Stable Diffusion in Blender
- https://airender.gumroad.com/l/ai-render
- Uses Dreamstudio for now
- DreamStudio will now use CLIP guidance
- Stable Diffusion running on iPhone
- Cycle Diffusion: https://github.com/ChenWu98/cycle-diffusion
- txt2img > img2img editors, look at github to see examples
- Information about difference merging added to FAQ
- Distributed model training planned
- SD Training Labs server
- Gradio updated
- Optimized, increased speeds
- Git pulling should be safe
10/14
- Fed bait claims
- You can generate forever by right clicking on the generate button
- Can now load checkpoint, clip skip, and hypernet from infotext for AUTO's webui
- Advanced Prompt Tuning, minimizes prompt typing and optimzes output quality
- https://github.com/7eu7d7/APT-stable-diffusion-auto-prompt
- planned to be PR on AUTO's repo once updated
- 3D photo inpainting
- Beginner's guide released:
- New method for merging models on AUTOMATIC1111's UI
- Double model merging + difference merging using a third model
10/13
- Emad QnA Summary
- Image animation
- Motion Diffusion available (text to a video of human motion)
- Text to video available for everyone
- VR SD in the works
- Emad's statement on censoring SAI's next model: https://desuarchive.org/g/thread/89182040#89182584
- NSFW model is hard to train right now, meaning the next release will have:
- No more nudity
- Violence allowed
- Opt-out tool coming for artists who do not want their art to be trained
- NSFW model is hard to train right now, meaning the next release will have:
- New method for training styles that doesn't require as many computing resources
- Method for faster and low step count generations
10/12
- StabilityAI is only releasing SFW models from now on
10/11
- Training embeddings and hypernetworks are possible on --medvram now
- Easy to setup local booru by booru anon, might be pickled: https://github.com/demibit/stable-toolkit
- Planned to be open source in about a week
- Can now train hypernetworks, git pull and find it in the textual inversion tab
- Sample (bigrbear): https://files.catbox.moe/wbt30i.pt
- Anon (might be wrong): xformers now works on a lot of cards natively, try a clean install with --xformers
- Early Anime Video Generation, trained by dep
10/10
- New unpickler for new ckpts: https://rentry.org/safeunpickle2
HENTAI DIFFUSION MIGHT HAVE A VIRUSconfirmed to be safe by some kind people- github taken down because of nude preview images, hf files taken down because of complaints, windows defender false positive, some kind anons scanned the files with a pickle scanner and and it came back safe
- automatic's repo has security checks for pickles
- anon scanned with a "straced-container", safe
- NAI's euler A is now implemented in AUTOMATIC1111's build
- git pull to access
- New open-source (?) generation method revealed making good images in 4 steps
- Supposedly only 64x64, might be wrong
- Discovered that hypernetworks were meant to create anime using the default SD model
10/9
- Full NAI frontend + backend implementation: https://desuarchive.org/g/thread/89095460#89097704 (PICKLE??, careful might actually be pickled)
- 1:1 recreation, is NAI ran locally (offline NAI)
- 8GB VRAM required
- has danbooru tag suggestions, past generation history, and mobile support (from anon)
- Unlimited prompt tokens
- NAI 1:1 Recreation for Euler (ASUKA, https://desuarchive.org/g/thread/89097837#89098634 https://boards.4chan.org/h/thread/6887840#p6888020)
- detailed setup guide: https://github.com/AUTOMATIC1111/stable-diffusion-webui/discussions/2017
- xformers working for 30s series and up, anything below needs tinkering (https://rentry.org/25i6yn)
- Use --xformers to enable for 30s series, --force-enable-xformers for others
- Deepdanbooru integrated: Use --deepdanbooru as an argument to webui-user.bat and find the interrogation change in img2img
- CLIP layer thing integrated, check settings after update
- v2.pt working
- VAE working
- Full models working
Prompting
Google Docs with a prompt list/ranking/general info for waifu creation:
https://docs.google.com/document/d/1Vw-OCUKNJHKZi7chUtjpDEIus112XBVSYHIATKi1q7s/edit?usp=sharing
Anon's prompt collection: https://mega.nz/folder/VHwF1Yga#sJhxeTuPKODgpN5h1ALTQg
GREAT CHINESE TOME OF PROMPTING KNOWLEDGE AND WISDOM 101 GUIDE: https://docs.qq.com/doc/DWHl3am5Zb05QbGVs
- Backup: https://www105.zippyshare.com/v/lUYn1pXB/file.html
GREAT JAPANESE TOME OF MASTERMINDING ANIME PROMPTS AND IMAGINATIVE AI MACHINATIONS 101 GUIDE https://p1atdev.notion.site/021f27001f37435aacf3c84f2bc093b5?p=f9d8c61c4ed8471a9ca0d701d80f9e28 - author: https://twitter.com/p1atdev_art/
Japanese prompt generator: https://magic-generator.herokuapp.com/
Build your prompt (chinese): https://tags.novelai.dev/
NAI Prompts: https://seesaawiki.jp/nai_ch/d/%c8%c7%b8%a2%a5%ad%a5%e3%a5%e9%ba%c6%b8%bd/%a5%a2%a5%cb%a5%e1%b7%cf
Japanese wiki: https://seesaawiki.jp/nai_ch/
Korean wiki: https://arca.live/b/aiart/60392904
Korean wiki 2: https://arca.live/b/aiart/60466181
Tip Dump: https://rentry.org/robs-novel-ai-tips
Tips: https://github.com/TravelingRobot/NAI_Community_Research/wiki/NAI-Diffusion:-Various-Tips-&-Tricks
Embedding tester: https://huggingface.co/spaces/sd-concepts-library/stable-diffusion-conceptualizer
Script for tagging (like in NAI) in AUTOMATIC's webui: https://github.com/DominikDoom/a1111-sd-webui-tagcomplete
Danbooru Tag Exporter: https://sleazyfork.org/en/scripts/452976-danbooru-tags-select-to-export
Another: https://sleazyfork.org/en/scripts/453380-danbooru-tags-select-to-export-edited
Tags (latest vers): https://sleazyfork.org/en/scripts/453304-get-booru-tags-edited
Basic gelbooru scraper: https://pastebin.com/0yB9s338
NEW UMI AI:
- FREE
- SFW and NSFW
- Goal: ultimate char-gen
- Tutorial: https://www.patreon.com/posts/umi-ai-official-73544634
- Why you should use it: https://www.patreon.com/posts/umi-ai-ultimate-73560593
- Examples:
- Straddling Sluts random prompt:
https://i.imgur.com/eDpRdjj.png
https://i.imgur.com/1mZ0u6q.png
https://i.imgur.com/cOjwAMm.png - Cocksucking Cunts prompt.
https://i.imgur.com/GdVCZuV.png
https://i.imgur.com/i5WTTB5.png
https://i.imgur.com/xj3mp8V.png - Bedded Bitches prompt.
https://i.imgur.com/urwxn6S.png
https://i.imgur.com/5gfC1oP.png - Oneshot H-Manga prompt.
https://i.imgur.com/oBec2uO.jpeg
https://i.imgur.com/UiWYTgr.jpeg
https://i.imgur.com/GuhU0Kz.jpeg
- Straddling Sluts random prompt:
- Discord: https://discord.gg/9K7j7DTfG2
- Author is looking for help filling out and improving wildcards
- Ex: https://cdn.discordapp.com/attachments/1032201089929453578/1034546970179674122/Popular_Female_Characters.txt
- Author: Klokinator#0278
- Looking for wildcards with traits and tags of characters
- Planned updates
- Code will get cleaned up
- the 'species' are rudimentary rn but stuff like 'superior slimegirls' are the direction I want to head with species moving forward
- the genders are still unigender, but I'll be separating m/f very soon
- and finally, I just need to add shitloads more content and scenarios
Random Prompts: https://rentry.org/randomprompts
Python script of the random prompts: https://rentry.org/nsfw-random-prompt-gen
Prompt randomizer: https://github.com/adieyal/sd-dynamic-prompting
Animation Script: https://github.com/amotile/stable-diffusion-studio
Animation script 2: https://github.com/Animator-Anon/Animator
Video Script: https://github.com/memes-forever/Stable-diffusion-webui-video
Masking Script: https://github.com/dfaker/stable-diffusion-webui-cv2-external-masking-script
XYZ Grid Script: https://github.com/xrpgame/xyz_plot_script
Vector Graphics: https://github.com/GeorgLegato/Txt2Vectorgraphics/blob/main/txt2vectorgfx.py
Txt2mask: https://github.com/ThereforeGames/txt2mask
Prompt changing scripts:
- https://github.com/yownas/seed_travel
- https://github.com/feffy380/prompt-morph
- https://github.com/EugeoSynthesisThirtyTwo/prompt-interpolation-script-for-sd-webui
Giffusion tutorial:
Inpainting Tips: https://www.pixiv.net/en/artworks/102083584
Rentry version: https://rentry.org/inpainting-guide-SD
Krita guide by anon:
- Get
https://krita.org/en/
https://github.com/Interpause/auto-sd-krita/wiki/Quick-Switch-Using-Existing-AUTOMATIC1111-Install
https://github.com/Interpause/auto-sd-krita/wiki/Install-Guide#plugin-installation - then you can run prompts in th app or pull one in then to inpaint like a boss, you add a new layer
https://files.catbox.moe/xy6z32.png - then use a white brush to brush the bits you want to change
https://files.catbox.moe/esdqk7.png - Turn off the layer off by hitting the eye icon but leave it selected
https://files.catbox.moe/wzaiw9.png - if you set everythign up right you have this section
https://files.catbox.moe/n43yrh.png - type what your after hit inpaint
Positive:
Biggest tip: just write what you want. the AI will generally understand and create it
- NAI's default (generally good) positive prompts to add at the beginning of all prompts: masterpiece, best quality
- can swap best for highest, high, etc.
- Group the things that you want that are similar together (e.g. things relating to body type, things relating to clothing, etc.), and put these groups in order of most important to least important
- Anon's order:
the picture's quality
the picture's subject
their physical appearance
their emotion
their clothing
their pose
the picture's setting
- Anon's order:
- "Anime screencap" creates scenes from an anime
- from anon: to use character (franchise/series/show/etc.), you have to format it as character \(franchise\)
- the tokenizer struggles to parse underscores, ymmv
Negative:
- NAI's default (remove "nsfw" if you want nsfw outputs): 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
Tags: https://danbooru.donmai.us/tags
Tag Groups: https://danbooru.donmai.us/wiki_pages/tag_groups
Most Popular Tags: https://danbooru.donmai.us/tags?commit=Search&search%5Bhide_empty%5D=yes&search%5Border%5D=count
Faces and heads:
Expressions:
Camera Angles:
Hair Styles:
Hands
- Hands: writing "in the style of Serpieri" increased hand quality in SD v1.4
Colors:
Posture
Posing
Locations
VAE:
- SD 1.4 Anime styled: https://huggingface.co/hakurei/waifu-diffusion-v1-4/blob/main/vae/kl-f8-anime.ckpt
Booru tag scraping:
- https://sleazyfork.org/en/scripts/451098-get-booru-tags
- script to run in browser, hover over pic in Danbooru and Gelbooru
- https://rentry.org/owmmt
- another script
- https://pastecode.io/s/jexs5p9c
- another script, maybe pickle
- press tilde on dan, gel, e621
- https://textedit.tools/
- if you want an online alternative
- https://github.com/onusai/grab-booru-tags
- works with e621, dev will try to get it to work with rule34.xxx
- https://pastecode.io/s/jexs5p9c
- https://pastecode.io/s/61owr7mz
- Press ] on the page you want the tags from
- Another script: https://pastecode.io/s/q6fpoa8k
- Another: https://pastecode.io/s/t7qg2z67
- Github for scraper: https://github.com/onusai/grab-booru-tags
Wildcards:
- https://desuarchive.org/g/thread/89006003#89007479
- https://rentry.org/sdWildcardLists
- Guide (ish): https://is2.4chan.org/h/1665343016289442.png
- A few wildcards: https://cdn.lewd.host/EtbKpD8C.zip
- https://github.com/Lopyter/stable-soup-prompts/tree/main/wildcards
- https://github.com/Lopyter/sd-artists-wildcards
- Allows you to split up the artists.csv from Automatic by category
- Another wildcard script: https://raw.githubusercontent.com/adieyal/sd-dynamic-prompting/main/dynamic_prompting.py
- wildcardNames.txt generation script: https://files.catbox.moe/c1c4rx.py
- Another script: https://files.catbox.moe/hvly0p.rar
- Script: https://gist.github.com/h-a-te/30f4a51afff2564b0cfbdf1e490e9187
- UMI AI: https://www.patreon.com/posts/umi-ai-official-73544634
- Wildcard dump:
- faces https://rentry.org/pu8z5
- focus https://rentry.org/rc3dp
- poses https://rentry.org/hkuuk
- times https://rentry.org/izc4u
- views https://rentry.org/pv72o
- Clothing: https://pastebin.com/EyghiB2F
- Another dump: https://github.com/jtkelm2/stable-diffusion-webui-1/tree/master/scripts/wildcards
- Big NAI Wildcard List: https://rentry.org/NAIwildcards
- 316 colors list: https://pastebin.com/s4tqKB8r
- 82 colors list: https://pastebin.com/kiSEViGA
- Backgrounds: https://pastebin.com/FCybuqYW
- More clothing: https://pastebin.com/DrkG1MRw
- Dump: https://www.dropbox.com/s/oa451lozzgo7sbl/wildcards.zip?dl=1
- 483 txt files, huge dump (for Danbooru trained models): https://files.catbox.moe/ipqljx.zip
- old 329 version: https://files.catbox.moe/qy6vaf.zip
- old 314 version: https://files.catbox.moe/11s1tn.zip
- Styles: https://pastebin.com/71HTfsML
- Word list (small): https://cdn.lewd.host/EtbKpD8C.zip
- Emotions/expressions: https://pastebin.com/VVnH2b83
- Clothing: https://pastebin.com/cXxN1fJw
- More clothing: https://files.catbox.moe/88s7bf.zip
- Cum: https://rentry.org/hoom5
- Dump: https://www.mediafire.com/file/iceamfawqhn5kvu/wildcards.zip/file
- Locations: https://pastebin.com/R6ugwd2m
- Clothing/outfits: https://pastebin.com/Xhhnyfvj
- Locations: https://pastebin.com/uyDJMnvC
- Clothes: https://pastebin.com/HaL3rW3j
- Color (has nouns): https://pastebin.com/GTAaLLnm
- Dump: https://files.catbox.moe/qyybik.zip
- Artists: https://pastebin.com/1HpNRRJU
- Animals: https://pastebin.com/aM4PJ2YY
- Food: https://pastebin.com/taFkYwt9
- Characters: https://files.catbox.moe/xe9qj7.txt
- Backgrounds: https://pastebin.com/gVue2q8g
- WIP random h-manga scene generator: https://files.catbox.moe/ukah7u.jpg
- Collection from https://rentry.org/NAIwildcards: https://files.catbox.moe/s7expb.7z
Some artists (may or may not work with NAI):
- SD 1.5 artists (might lag your pc): https://docs.google.com/spreadsheets/d/1SRqJ7F_6yHVSOeCi3U82aA448TqEGrUlRrLLZ51abLg/htmlview#
- pre-modern art: https://www.artrenewal.org/Museum/Search#/
- SD 1.4 artists: https://rentry.org/artists_sd-v1-4
- Link list: https://pastebin.com/HD7D6pnh
- Artist comparison grids: https://files.catbox.moe/y6bff0.rar
- Artist Comparison: https://reddit.com/r/NovelAi/comments/y879x1/i_made_an_experiment_with_different_artists_here/
Creating fake animes:
1:1 NAI/Novel AI Cheatsheet:
-
1:1 NAI cheatsheet by anon:
- Use unpruned/full model
- Load with ema weights (use .yaml config from base stable-diffusion, set use_ema to true) (minor)
- Doubles ram
-
Anon: "I copied the one from this path (which is what voldy defaults to if one isn't specified):
/repositories/stable-diffusion/configs/stable-diffusion/v1-inference.yamlAnd then on line 18 I set use_ema to True, and put that copy into the models folder with the correct name (name of model.yaml)."
- CLIP layer = 2
- Reset sigma noise / strength to the default value of 1 (no need to use 0.69 / 0.67)
- Set eta noise seed delta to 31337
- If using Euler a, eta noise seed delta = 31337
- If prompt has weights, manually adjust the weight accordingly (voldy uses 1.1, NAI uses 1.05)
- Use --no-half argument (minor)
Anon's workflow:
Artist list: https://rentry.org/anime_and_titties
Expressions and (STYLE): https://rentry.org/faces-faces-faces
Anon's order:
the picture's quality
the picture's subject
their physical appearance
their emotion
their clothing
their pose
the picture's setting
Anon's Refinement Technique:
- generate a picture with the prompt that you want, be very precise. I personally generate pictures that are 512x512 initially.
- once you get a decent picture to come out of the generation, it will be used as the base "sketch" to feed to img2img.
- if you want to, increase the resolution but if you do so set the denoising to about .60
- once you have the resolution you want and everything, keep reprocessing the image with a denoising of about 0.2 - 0.3.
- if something on the image bothers you, work on it in an image editor, for example using a brush of the same colour of the what's adjacent to the detail you want to remove, or if you want to add something (like refining fingers), make sure to use the pencil with a contrasted colour (I generally use black).
- after editing, always reprocess the image with a denoising of about 0.3
- once the result satisfies you enough, use the "R-ESRGAN 4x+ Anime6B" upscaler if you want the image upscaled.
Models, Embeddings, and Hypernetworks
Models, embeddings, and hypernetworks can be pickled. Download at your own risk. Use https://rentry.org/safeunpickle2 to unpickle
Models (WIP)
Organized list: https://rentry.org/sdmodels
Groups (add more later):
- Waifu Diffusion (https://huggingface.co/hakurei/waifu-diffusion-v1-4)
- Stability AI
- Zeipher (https://ai.zeipher.com/)
Upcoming models:
- Waifu Diffusion v1.4: https://huggingface.co/hakurei/waifu-diffusion-v1-4
Stable Diffusion v1.4
- Torrent: magnet:?xt=urn:btih:3A4A612D75ED088EA542ACAC52F9F45987488D1C&tr=udp://tracker.opentrackr.org:1337
- HuggingFace: https://huggingface.co/CompVis/stable-diffusion-v-1-4-original
- Login required
- Google Drive: https://drive.google.com/file/d/1wHFgl0ivCmIZv88hVZXkb8oy9qCuaBGA/view
Waifu Diffusion VAE (250k images)
- https://huggingface.co/hakurei/waifu-diffusion-v1-4/blob/main/vae/kl-f8-anime.ckpt
- https://twitter.com/haruu1367/status/1579286947519864833
- "finetuned the SD 1.4 vae on a bunch of anime-styled images"
- Supposedly improves eyes and fingers
- To load, rename .ckpt to .vae.pt
Waifu Diffusion v1.3
- https://huggingface.co/hakurei/waifu-diffusion-v1-3
- Click "Files and versions" to view all epochs
- 600,000 high-resolution Danbooru images, 10 Epochs
- Release Notes: https://gist.github.com/harubaru/f727cedacae336d1f7877c4bbe2196e1
Waifu Diffusion v1.2
Pruned Torrent:
Full EMA Torrent:
Trinart2
- https://huggingface.co/naclbit/trinart_stable_diffusion_v2/tree/main
- Uses dropouts, 10k more images than Trinart1, new tagging strategy, and trained for longer
Trinart1
- https://huggingface.co/naclbit/trinart_stable_diffusion/tree/main
- 3.5 epochs, 30k images
- Obsolete
gg1342_testrun1_pruned
- 280 NSFW nude solo women + 80 SFW fiction characters
Hentai Diffusion
- https://huggingface.co/Deltaadams/Hentai-Diffusion/tree/main
- Based on Waifu Diffusion 1.2, trainede on 150k images from rule34 and gelbooru, focused training on hands and poses
- Updated weekly
RD1412
- Pruned FP16
- Pruned FP32
RD1212
- Pruned FP16
- Pruned FP32
- Full EMA
Bare Feet / Full Body b4_t16_noadd
- Focused on bare feet and full body nude female images, good for genitalia and photorealistic feet
- Pruned FP16 v3
- Pruned FP32 v3
Lewd Diffusion
- 70k images from Danbooru, based on Waifu Diffusion 1.2
- Dataset: https://drive.google.com/drive/folders/1f_BYi88LLTZUzBHkUz8PDgw6l7M7swkd?usp=sharing
- Dataset stats: https://docs.google.com/spreadsheets/d/1BzNSXyT4fhiM64DwIJSCyAXuhRQ9fkxqcr-t1frIYkc/edit
- 2 epochs
- 1 epoch
- 0 epochs, 40k images
Yiffy
- During training explicit was misspelled as explict
- Tags:
- 18 epochs (210k images from e621):
- 15 epochs (210k images from e621):
- https://sexy.canine.wf/file/yiffy-ckpt/yiffy-e15.ckpt
- https://pixeldrain.com/u/qkRKKpqg
- https://iwiftp.yerf.org/Furry/Software/Stable%20Diffusion%20Furry%20Finetune%20Models/Finetune%20models/yiffy-e15.ckpt
-
13 epochs
- first 4 epochs were trained on ~70k images with lama infilling (the cause of all of our headaches, because the network found a pattern in the edges and started replicating it everywhere)
- next 6 epochs were trained on ~120k images with random cropping and a lower LR
- last epochs were done on a different dataset, not bigger than 150k
- https://iwiftp.yerf.org/Furry/Software/Stable%20Diffusion%20Furry%20Finetune%20Models/Finetune%20models/yiffy-e13.ckpt
Furry
- 300k images from e621
- Tags:
- Epoch 4
- https://pixeldrain.com/u/dtYiYN7g
- https://iwiftp.yerf.org/Furry/Software/Stable%20Diffusion%20Furry%20Finetune%20Models/Finetune%20models/furry_epoch4.ckpt
- Epoch 1
- https://iwiftp.yerf.org/Furry/Software/Stable%20Diffusion%20Furry%20Finetune%20Models/Finetune%20models/furry_epoch1.ckpt
- https://iwiftp.yerf.org/Furry/Software/Stable%20Diffusion%20Furry%20Finetune%20Models/Finetune%20models/furry_epoch1.ckpt
- Epoch 0
Zack3D_Kinky-v1
- Over 100k images, filtered aesthetics, NSFW, trained on SD v1.4, good for furry, specializes in kinks like transformation, latex, tentacles, goo, ferals, bondage, etc.
- Uses e621 tags with underscores
Anal Vore AVHumanFurryPony7
- 7 epochs, continued from Zack3D_Kinky-v1
- Tags
R34
Pussy Diffusion 10/14 (only use for inpainting)
- trained on sankaku+e621 on gaping_anus,gaping_pussy,large_penetration,fisting, prolapse
- https://gofile.io/d/Viv9CJ
- https://bbs.kfpromax.com/read.php?tid=963487
- 链接: https://pan.baidu.com/s/1sC69cgSTWGuXCY79K5C_DA 提取码: 7qdp
a merged model of 80 NAI 20 TRIN120k
- https://mega nz/file/jB5lwa6J#ciSArZnJQLszvhatiMK2NTKFNjKYUhHJlXt9At3WRss
Berrymix Recipe
Make sure you have all the models needed, Novel Ai, Stable Diffusion 1.4, Zeipher F111, and r34_e4. All but Novel Ai can be downloaded from HERE
Open the Checkpoint Merger tab in the web ui
Set the Primary Model (A) to Novel Ai
Set the Secondary Model (B) to Zeipher F111
Set the Tertiary Model (C) to Stable Diffusion 1.4
Enter in a name that you will recognize
Set the Multiplier (M) slider all the way to the right, at "1"
Select "Add Difference"
Click "Run" and wait for the process to complete
Now set the Primary Model (A) to the new checkpoint you just made (Close the cmd and restart the webui, then refresh the web page if you have issues with the new checkpoint not being an option in the drop down)
Set the Secondary Model (B) to r34_e4
Ignore Tertiary Model (C) (I've tested it, it wont change anything)
Enter in the name of the final mix, something like "Berry's Mix" ;)
Set Multiplier (M) to "0.25"
Select "Weighted Sum"
Click "Run" and wait for the process to complete
Restart the Web Ui and reload the page just to be safe
At the top left of the web page click the "Stable Diffusion Checkpoint" drop down and select the Berry's Mix.ckpt (or whatever you named it) it should have the hash "[c7d3154b]"
Dreambooth Models:
Links:
- https://huggingface.co/waifu-research-department
- https://huggingface.co/jinofcoolnes
- For preview pics/descriptions:
- https://huggingface.co/nitrosocke
- https://rentry.org/sdmodels
- Big collection: https://publicprompts.art/
- Nami: https://mega.nz/file/VlQk0IzC#8MEhKER_IjoS8zj8POFDm3ZVLHddNG5woOcGdz4bNLc
- https://huggingface.co/IShallRiseAgain/StudioGhibli/tree/main
- Jinx: https://huggingface.co/jinofcoolnes/sksjinxmerge/tree/main
- Arcane Vi: https://huggingface.co/jinofcoolnes/VImodel/tree/main
- Lucy AI: https://huggingface.co/jinofcoolnes/Lucymodel/tree/main
- Gundam (full ema, non pruned): https://huggingface.co/Gazoche/stable-diffusion-gundam
- Starsector Portraits: https://huggingface.co/Severian-Void/Starsector-Portraits
- Evangelion style: https://huggingface.co/crumb/eva-fusion-v2
Embeddings
- Text Tutorial: https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Textual-Inversion
- Make sure to use pictures of your subject in varied areas, it gives more for the AI to work with
- Tutorial 2: https://rentry.org/textard
- Another tutorial: https://imgur.com/a/kXOZeHj
- Test embeddings: https://huggingface.co/spaces/sd-concepts-library/stable-diffusion-conceptualizer
- Collection: https://huggingface.co/sd-concepts-library
- Collection 2: https://mega.nz/folder/fVhXRLCK#4vRO9xVuME0FGg3N56joMA
Found on 4chan:
- Embeddings + Artists: https://rentry.org/anime_and_titties (https://mega.nz/folder/7k0R2arB#5_u6PYfdn-ZS7sRdoecD2A)
- Random embedding I found: https://ufile.io/c3s5xrel
- Embeddings: https://rentry.org/embeddings
- Anon's collection of embeddings: https://mega.nz/folder/7k0R2arB#5_u6PYfdn-ZS7sRdoecD2A
- Collection: https://gitgud.io/ZeroMun/stable-diffusion-tis/-/tree/master/embedding
- Collection: https://gitgud.io/sn33d/stable-diffusion-embeddings
- Collection from "friend" (might be malicious): https://files.catbox.moe/ilej0r.7z
- Collection from anon: https://files.catbox.moe/22rncc.7z
- WD 1.3 Embeddings: https://gitlab.com/rakurettocorp/stable-diffusion-embeddings/-/tree/main/embeddings/wd
- Kokomi/Nilou (25k), Kantoku
- Collection: https://gitlab.com/mwlp/sd
- Senri Gan: https://files.catbox.moe/8sqmeh.rar
- Collection: https://gitgud.io/viper1/stable-diffusion-embeddings
- Henreader embedding, all 311 imgs on gelbooru, trained on NAI: https://files.catbox.moe/gr3hu7.pt
- Kantoku (NAI): https://files.catbox.moe/j4acm4.pt
- Asanagi (NAI): https://files.catbox.moe/xks8j7.pt
- Asanagi trained on 135 images augmented to 502 for 150296 steps on NAI Anime Full Pruned with 16 vectors per token with init word as voluptuous
- training imgs: https://litter.catbox.moe/2flguc.7z
- DEAD LINK Asanagi (another one): https://litter.catbox.moe/g9nbpx.pt
- Imp midna (NAI, 80k steps): mega.nz/folder/QV9lERIY#Z9FXQIbtXXFX5SjGf1Ba1Q
- imp midna 2: mega.nz/file/1UkgWRrD#2-DMrwM0Ph3Ebg-M8Ceoam_YUWhlQWsyo1rcBtuKTcU
- inverted nipples: https://anonfiles.com/300areCby8/invertedNipples-13000_zip (reupload)
- Dead link: https://litter.catbox.moe/wh0tkl.pt
- Takeda Hiromitsu Embedding 130k steps: https://litter.catbox.moe/a2cpai.pt
- Takeda embedding at 120000 steps: https://filebin.net/caggim3ldjvu56vn
- Nenechi embedding: https://mega.nz/folder/E0lmSCrb#Eaf3wr4ZdhI2oettRW4jtQ
- Touhou Fumo embedding (57 epochs): https://birchlabs.co.uk/share/textual-inversion/fumo.cpu.pt
- Abigail from Great Pretender (24k steps): https://workupload.com/file/z6dQQC8hWzr
- Naoki Ikushima (40k steps): https://files.catbox.moe/u88qu5.pt
- Abmayo: https://files.catbox.moe/rzep6d.pt
- Gigachad: https://easyupload.io/nlha2m
- Kusada Souta (95k steps): https://files.catbox.moe/k78y65.pt
- Yohan1754: https://files.catbox.moe/3vkg2o.pt
- Fatamoru: https://litter.catbox.moe/xd2ht9.pt
- Repo for some: https://git.evulid.cc/wasted-raincoat/Textual-Inversion-Embeds/src/branch/master/simonstalenhag
- automatic's secret embedding list: https://gitlab.com/16777216c/stable-diffusion-embeddings
- Niro: https://take-me-to.space/WKRY9IE.pt
- Kaneko Kazuma: https://litter.catbox.moe/6glsh1.pt
- Senran Kagura (850 CGs, deepdanbooru tags, 0.005 learning rate, 768x768, 3000 iterations): https://files.catbox.moe/jwiy8u.zip
- Abmono (14.7k): https://www.mediafire.com/file/id2uh4gkzvavsbc/abmono-14700.pt/file
- DEAD LINK Deadflow (190k, "bitchass"(?)): https://litter.catbox.moe/03lqr6.pt
- Aroma Sensei (86k, "aroma"): https://files.catbox.moe/wlylr6.pt
- Zun (75:25 weighted sum NAI full:WD): https://www.fluffyboys.moe/sd/zunstyle.pt
- Kurisu Mario (20k): https://files.catbox.moe/r7puqx.pt
- creator anon: "I suggest using him for the first 40% of steps so that the AI draws the body in his style, but it's up to you. Also, put speech_bubble in the negative prompt, since the training data had them"
- ATDAN (33k): https://files.catbox.moe/8qoag3.pt
- Valorant (25k): https://files.catbox.moe/n7i9lq.pt
- Takifumi (40k, 153 imgs): https://freeufopictures.com/ai/embeddings/takafumi/
- 40hara (228 imgs, 70k, 421 after processing): https://freeufopictures.com/ai/embeddings/40hara/
- Tsurai (160k, NAI): https://mega.nz/file/bBYjjRoY#88o-WcBXOidEwp-QperGzEr1qb8J2UFLHbAAY7bkg4I
- Wagashi (12k, shitass(?)), no associated pic or replies so might be pickled: https://litter.catbox.moe/ktch8r.pt
- jtveemo (150k): https://a.pomf.cat/kqeogh.pt
- Creator anon: "I didn't crop out any of the @jtveemo stuff so put twitter username in the negatives."
- Nahida (Genshin Impact): https://files.catbox.moe/nwqx5b.zip
- Arcane (SD 1.4): https://files.catbox.moe/z49k24.pt
- People say this triggered the pickle warning, so it might be pickled.
- Gothica: https://litter.catbox.moe/yzp91q.pt
- Mordred: https://a.pomf.cat/ytyrvk.pt
- 100k steps tenako (mugu77): https://www.mediafire.com/file/1afk5fm4f33uqoa/tenako-mugu77-100000.pt/file
- erere-26k (fuckass(?)): https://litter.catbox.moe/cxmll4.pt
- Great Mosu (44k): https://files.catbox.moe/6hca0u.pt
- no idea what this embedding is: https://files.catbox.moe/2733ce.pt
- Dohna Dohna, Rance remakes (305 images (all VN-style full-body standing character CGs). 12000 steps): https://files.catbox.moe/gv9col.pt
- Gyokai / Onono Imoko / shunin ("gyokai-zen" v1.0 + dataset): https://mega.nz/file/67AUDQ4K#8n4bzcxGGUgaAVy7wLXvVib0jhVjt2wPS-jsoCxcCus
- Raita: https://files.catbox.moe/mhrvmk.pt
- Senri Gan: https://files.catbox.moe/8sqmeh.rar
- 2 hypernetworks and 5 TI
- Anon: "For the best results I think using hyper + TI is the way. I'm using TI-6000 and Hyper-8000. It was trained on CLIP 1 Vae off with those rates 5e-5:100, 5e-6:1500, 5e-7:10000, 5e-8:20000."
- om_(n2007): https://files.catbox.moe/gntkmf.zip
- Kenkou Cross: https://mega.nz/folder/ZYAx3ITR#pxjhWOEw0IF-hZjNA8SWoQ
- Rui Komatsuzaki: https://files.catbox.moe/3qh6jb.pt
- Baffu (~47500 steps): https://files.catbox.moe/l8hrip.pt
- Biased toward brown-haired OC girl (Hitoyo)
- Danganronpa: https://files.catbox.moe/3qh6jb.pt
- Hifumi Takimoto: https://files.catbox.moe/wiucep.png
- 18500 steps, prompt tag is takimoto_hifumi. Trained on NAI + Trinart2 80/20, but works fine using just NAI
- Power (WIP): https://files.catbox.moe/bzdnzw.7z
- shiki_(psychedelic_g2): https://files.catbox.moe/smeilx.rar
- Akari: https://files.catbox.moe/b7jdng.pt
- Embeddings using the old version of TI
- Takeda Hiromitsu reupload: https://www.mediafire.com/file/ljemvmmtz0dqy0y/takeda_hiromitsu.pt/file
- Takeda Hiromitsu (another reupload): https://a.pomf.cat/eabxqt.pt
- Pochi: https://files.catbox.moe/7vegvg.rar
- Author's notes: Smut version was trained on a lot of doujins and it looks more like her old style from the start of smut version of Ane doujin (compare to chapter 1 and you can see that it worked). 200k version is looking a bit more like her recent style but I can see it isn't going to work the way I hoped.
- By accident I started with 70 pics where half of them were doujins to give reference for smut. Complete data is 200 with again those same 35 doujins for smut. I realized that I used half smut instead of full set so I went back to around 40k steps and then gave it complete 200 picture set hoping it would course correct since non smut is more recent art style. Now it looks like it didn't course correct and will never do that. On the other hand recent iterations are less horny.
- Power (Chainsaw Man): https://files.catbox.moe/c1rf8w.pt
- ooyari:
- 70k (last training): https://litter.catbox.moe/gndvee.pt
- 20k (last stable loss trend): https://litter.catbox.moe/i7nh3x.pt
- 60k (lowest loss rate state in trending graph): https://litter.catbox.moe/8wot9a.pt
- TATATA: https://mega.nz/folder/zYph3LgT#oP3QYKmwqurwc9ievrl9dQ
- Kunaboto (195 images. 16 vectors per token, default learning rate of 0.005): https://files.catbox.moe/uk964z.pt
- Erika (Shadowverse): https://files.catbox.moe/y9cgr0.pt
- Luna (Shadowverse): https://files.catbox.moe/zwq5jz.pt
- Fujisaka Lyric: https://files.catbox.moe/8j6ith.pt
- Hitoyo (maybe WIP?): https://files.catbox.moe/srg90p.pt
- Hitoyo (58k): https://files.catbox.moe/btjsfg.pt
- kunaboto v2 (Same dataset, just a different training rate of 0.005:25000,0.0005:75000,0.00005:-1, 70k): https://files.catbox.moe/v9j3bz.pt
- Hitoyo (another, final vers?) (100k steps, bonnie-esque): https://files.catbox.moe/l9j1f4.pt
Found on Discord:
- Nahida v2: https://cdn.discordapp.com/attachments/1019446913268973689/1031321278713446540/nahida_v2.zip
- Nahida (50k, very experimental, not enough images): https://files.catbox.moe/2794ea.pt
Found on Reddit:
- look at the 2nd and 3rd images: https://www.reddit.com/gallery/y4tmzo
Hypernetworks:
- anon: "Requires extremely low learning rate, 0.000005 or 0.0000005"
WIP Rentry: https://rentry.co/naihypernetworks
Hypernetwork Dump: https://gitgud.io/necoma/sd-database
Collection: https://gitlab.com/mwlp/sd
Another collection: https://www.mediafire.com/folder/bu42ajptjgrsj/hn
Senri Gan: https://files.catbox.moe/8sqmeh.rar
Mogudan, Mumumu (Three Emu), Satou Shouji + constant updates: https://mega.nz/folder/hlZAwara#wgLPMSb4lbo7TKyCI1TGvQ
Big dumpy of a lot of hypernets: https://mega.nz/folder/kPdBkT5a#5iOXPnrSfVNU7F2puaOx0w
Collection of asanuggy + maybe some more: https://mega.nz/folder/Uf1jFTiT#TZe4d41knlvkO1yg4MYL2A
Collection: https://mega.nz/folder/fVhXRLCK#4vRO9xVuME0FGg3N56joMA
Found on 4chan:
- bigrbear: https://files.catbox.moe/wbt30i.pt
- Senran Kagura v3 (850 images, 0.000005 learn rate, 20000 steps, 768x768): https://files.catbox.moe/m6jynp.pt
- CGs from the Senran Kagura mobile game (NAI model): https://files.catbox.moe/vyjmgw.pt
- Ran for 19,000 steps with a learning rate of 0.0000005. Source images were 768x576. It seems to only reproduce the art style well if you specify senran kagura, illustration, game cg, in your prompt.
- Old version (19k steps, learning rate of 0.0000005. Source images were 768x576. NAI model. 850 CGs): https://files.catbox.moe/di476p.pt
- Senran Kagura again (850, deepdanbooru, 0.000006, 768x576, 7k steps): https://files.catbox.moe/f40el4.pt
- CGs from the Senran Kagura mobile game (NAI model): https://files.catbox.moe/vyjmgw.pt
- Danganronpa: https://files.catbox.moe/9o5w64.pt
- Trained on 100 images, up to 12k with 0.000025 rate, then up to 18.5k with 0.000005
- Also seed 448840911 seems to be great quality for char showcase with just name + base NAI prompts.
- Alexi-trained hypernetwork (22000 steps): https://files.catbox.moe/ukzwlp.pt
- Reupload by anon: https://files.catbox.moe/slbk3m.pt
- works best with oppai loli tag
- https://files.catbox.moe/xgozyz.zip
- Etrian Odyssey Shading hypernetwork (20k steps, WIP, WD 1.3)
- colored drawings by Hass Chagaev (6k steps, NAI): https://files.catbox.moe/3jh1kk.pt
- Morgana: https://litter.catbox.moe/3holmx.pt
- EOa2Nai: https://files.catbox.moe/ex7yow.7z
- EO (WD 1.3): https://files.catbox.moe/h5phfo.7z
- Taran Jobu (oppai loli, WIP, apparently it's kobu not jobu)
- Higurashi (NAI:SD 50:50): https://litter.catbox.moe/lfg6ik.pt
- by op anon: "1girl, [your tags here], looking at viewer, solo, art by higurashi", cfg 7, steps about 40"
- Tatata (15 imgs, 10k steps): https://files.catbox.moe/7hp2es.pt
- Zankuro (0.75 NAI:WD, 51 imgs, 25k+ steps): https://files.catbox.moe/tlurbe.pt
- Training info + hypernetwork: https://files.catbox.moe/4do43z.zip
- Test Hypernetwork (350 imgs where half are flipped, danooru tags, 0.00001 learning rate for 3000 steps, 0.000004 until step 7500): https://files.catbox.moe/coux0u.pt
- Kyokucho (40k steps, good at 10-15k, NAI:WD1.2): https://workupload.com/file/TFRuGpdGZZn
- Final Ixy: https://mega.nz/folder/yspgEBhQ#GLo7mBc1EH7RK7tQbtC68A
- Old Ixy (more data, more increments): https://mega.nz/file/z8AyDYSS#zbZFo9YLeJHd8tWcvWiRlYwLz2n4QXTKk04-cKMmlrg
- Old Ixy (less increments, no training data): https://mega.nz/file/ixxzkR5T#cxxSNxPF1KmszJDqiP4K4Ou8tbl1SFKL6DdQC58k6zE
- Grandblue Fantasy character art (836 images, 5e-5:100, 5e-6:1500, 5e-7:10000, 5e-8:20000 learn rate, 20000 steps, 1024x1024): https://files.catbox.moe/2uiyd4.pt
- Bombergirl (Stats: 178 images, 5e-8 learn rate continuing from old Bombergirl, 20000 steps, 768x768): https://files.catbox.moe/9bgew0.pt
- Old Bombergirl (178 imgs, 0.000005 learning rate, 10k, 768x768): https://files.catbox.moe/4d3df4.pt
- Aki99 (200 images , 512x512, 0.00005, 19K steps, NAI): https://files.catbox.moe/bwff89.pt
- Aki99 (200 images , 512x512, 0.0000005, 112K steps, learning prompt: [filewords], NAI): https://www.mediafire.com/file/sud6u1vb0gvqswu/aki99-112000.7z/filehttps://files.catbox.moe/6hca0u.pt
- Great Mosu: https://files.catbox.moe/mc1l37.pt
- mda starou: https://a.pomf.cat/xcygvk.pt
- Mogudan (12 vectors per token, 221 image dataset, preprocessing: split oversize, flipped mirrors, deepdanbooru auto-tag, 0.00005 learning rate, 62,500 steps): https://mega.nz/file/UtAz1CZK#Y5OSHPkD38untOPSEkNttAVi2tdRLBFEsKVkYCFFaHo
- Onono Imoko: https://files.catbox.moe/amfy2x.pt
- Etrian Odyssey (training rate 5e-5:100, 5e-6:1500, 5e-7:10000, 5e-8:20000,20k steps, 512 x 512 pics): https://files.catbox.moe/94qm83.7z
- Jesterwii: https://files.catbox.moe/hlylo4.zip
- jtveemo (v1): https://mega.nz/folder/ctUXmYzR#_Kscs6m8ccIzYzgbCSupWA
- 35k max steps, 0.000005 learning rate, 180 images, ran through deepbooru and manually cleaned up the txt files for incorrect/redundant tags.
- Recommended the 13500.pt, or something near it
- Recommended: https://files.catbox.moe/zijpip.pt
- Artsyle based on Yuugen (HBR) (Stats: 103 images, 5e-5:100, 5e-6:1500, 5e-7:10000, 5e-8:20000 learn rate, 20000 steps, 1024x1024,Trained on NAI model): https://files.catbox.moe/bi2ts0.7z
- Alexi: https://files.catbox.moe/3yj2lz.pt (70000 steps)
- as usual, works best with oppai loli tag. chibi helps as well
- changes from original one i noticed during testing:
-hair shading is more subtle now
-nipple color transition is also more subtle
-eyelashes not as thick as before, probably because i used more pre-2022 pictures. actually bit sad about it, but w/e
-eyes in general look better, i recommend generating on 768×768 with highres fix
-blonde hair got a pink gradient for some reason
-tends to hide dicks between the breasts more often, but does it noticeably better
-likes to add backgrounds, i think i overcooked it a bit so those look more like artifacts, perhaps with other prompts it will look better
-less hags
-from my test prompts, it looked like it breaks anatomy less often now, but i mostly tested pov paizuri
-became kinda worse at non-paizuri pictures, less sharpness. because of that, i'm also including 60000 steps version, which is slightly better at that, but in the end, it's a matter of preference, whether to use newer version or not: https://files.catbox.moe/1zt65u.pt
- Ishikei: https://www.mediafire.com/folder/obbbwkkvt7uhk/ishikemono
- Mogudan, Mumumu (Three Emu), Satou Shouji: https://mega.nz/folder/hlZAwara#wgLPMSb4lbo7TKyCI1TGvQ
- creator anon: "this will be the future folder where I will be uploading all my textual inversions. Mumumu hypernetwork is training now, Satou Shouji dataset has been prepped, now to scrape Onomeshin's art from Gelbooru"
- Mumumu: 109 images, 75k steps
- Curss style (slime girls): https://files.catbox.moe/0sixyq.pt
- WIP Collection of hypernets: https://litter.catbox.moe/xxys2d.7z
- DEAD LINK Mumumu's art: https://mega.nz/folder/tgpikL6C#Mj0sHUnr-O6u4MOMDRTiMQ
- Senri Gan: https://files.catbox.moe/8sqmeh.rar
- 2 hypernetworks and 5 TI
- Anon: "For the best results I think using hyper + TI is the way. I'm using TI-6000 and Hyper-8000. It was trained on CLIP 1 Vae off with those rates 5e-5:100, 5e-6:1500, 5e-7:10000, 5e-8:20000."
- Ulrich: https://files.catbox.moe/jhgsxw.zip
- akisora: https://files.catbox.moe/gfdidn.pt
- lilandy: https://files.catbox.moe/spzm60.pt
- shadman: https://files.catbox.moe/kc850y.pt
- anon: "if anyone else wants to try training, can recommend - 0.00005:2000, 0.000005:4000, 0.0000005:6000 learning rate setup (6k steps total with 250~1000 images in dataset)"
- not sure what this is, probably a style: https://files.catbox.moe/lnxwks.pt
- ndc hypernet, muscle milfs: https://files.catbox.moe/hsx4ml.pt
- Asanuggy: https://mega.nz/folder/Uf1jFTiT#TZe4d41knlvkO1yg4MYL2A
- Tomubobu: https://files.catbox.moe/bzotb7.pt
- Works best with jaggy lines, oekaki, and clothed sex tags.
- satanichia kurumizawa macdowell (around 552 pics in total with 44.5k steps, most of the datasets are fanarts but some of them are from the anime, tagged with deepdanbooru, flipped and manually cropped): https://files.catbox.moe/g519cu.pt
- Imazon v1: https://files.catbox.moe/0e43tq.pt
- Imazon v2: https://files.catbox.moe/86pkaq.pt
- WIP Baffu: https://gofile.io/d/4SNmm5
- Ilulu (74k steps at 0.0005 learning rate, full NAI, init word "art by Ilulu"): https://files.catbox.moe/18ad25.pt
- belko paizuri (86k swish + normalization): https://www.mediafire.com/folder/urirter91ect0/belkomono
- WIP: training/0.000005/swish/normalization
- Pinvise (Suzutsuki Kirara) (NAI-Full with 5e-6 for 8000 steps and 5e-7 until 12000 steps on 200 (400 with flipped) images): https://litter.catbox.moe/glk7ni.zip
- Bonnie: https://files.catbox.moe/sc50gl.pt
- Another batch of artists hypernetworks (some are with 1221 structure, so bigger size)
- https://files.catbox.moe/srhrn6.pt - diathorn
- https://files.catbox.moe/dytn06.pt - gozaru
- https://files.catbox.moe/69t1im.pt - Sunahara Wataru
- WiseSpeak (Rubbish Fox on Twitter): https://files.catbox.moe/kyllcc.pt
- Info: Uses 176 images that were preprocessed with splitting, flipping and mild touchup to remove text in Paint on about 1/4th of the images. I removed images from the Preprocess folder that did not have discernable character traits. Most images are of Tamamo since that is his waifu. Total images after split, flip, and corrections was 636. Took 8 hours at 0.000005 Rate at 512x512
Found on Discord (copied from SD Training Labs discord, so grammar mistakes may be present):
-
Art style of Rumiko Takahashi
Base: Novel AI's Final Pruned
[126 images, 40000 steps, 0.00005 rate]
Tips: "by Rumiko Takahashi" or "Shampoo from Ranma" etc. -
Amamiya Kokoro (天宮こころ) a Vtuber from Njiisanji [NSFW / SFW] (Work on WD / NAI)
(Training set: 36 Input images, 21500 Steps, 0.000005 Learning rate.
Training model: NAI-Full-Prunced
Start with nijisanji-kokoro to get a good result.
Recommend Hypernetwork Strength rate: 0.6 to 1.0 -
Haru Urara (ハルウララ) from Umamusume ウマ娘 [NSFW / SFW] (Work on WD / NAI)
Training set: 42 Input images, 21500 Steps, 0.000005 Learning rate.
Training model: NAI-Full-Prunced
Start with uma-urara to get a good result.
Recommend Hypernetwork Strength rate: 0.6 to 1.0 -
Genshin Impact [SFW]
992 images, official art including some game assets
15k steps trained on nai
use "character name genshin impact" or "genshin impact)" for best results- LINK: https://files.catbox.moe/t4ooj6.pt
- 45k step version: https://files.catbox.moe/newhp6.pt
-
Ajitani Hifumi (阿慈谷 ヒフミ) from Blue Archive [NSFW / SFW] (Work on WD / NAI)
Training set: 41 Input images, 20055 Steps, 0.000005 Learning rate.
Model: NAI-Full-Prunced
Start with ba-hifumi to get a good result.
Recommend Hypernetwork Strength rate: 0.6 to 1.0
1.0 Is a little bit overkill I thought about.
If you want to go different costume like swimsuit or casual, I think 0.4 to 0.7 is the best ideal rate. -
Higurashi no Nako Koro ni // ryukishi07's artstyle
Trained on Higurashi's original VN sprites. Might do Umineko's sprites next, or mix the two together.
8k steps, 15k steps, 18k steps included. -
Trained Koharu of Blue Archive. I'm not very good at English, so it's painful to read this describe.
Training set: 41 images, 20000 steps, 0.000005 learning rate.
Model: WD1.3 merged NAI (3/7 - Sigmoid) - queencomplexstyle (no training info): https://files.catbox.moe/32s6yb.pt
- Shiroko of Blue Archive. Training set: 14 images at 20000 steps 0.000005 learning rate. The tag is 'ba-shiroko'
-
Queen Complex
(https://queencomplex.net/gallery/?avia-element-paging=2) [NSFW]
"It's a cool style, and it has nice results. Don't need to special reference anything, seems to work fine regardless of prompt."
Base Model: Novel AI
Training set: 52 images at 4300 steps 0.00005 learning rate (images sourced from link above and cropped) -
Raichiyo33 style hypernetwork. Not perfect but seems good enough.
Trained with captions from booru tags for compability with model + art by raichiyo33 in the beginning over NAI model. Use "art by raichiyo33" in the begining of prompt to triggering.
Some useful tips:- with tag "traditional media" produce more beautiful results
- try to avoid too much negativ promts. I use only "bad anatomy, bad hands, lowres, worst quality, low quality, blurry, bad quality" even that seems too much. With many UC tags (especially with full NAI set of uc) it will produce almost generic NAI result.
- Use CLIP -2 (because its trained over NAI, ofc)
-
Genshin Impact [SFW]
992 images, official art including some game assets
15k steps trained on nai
use "character name genshin impact" or "genshin impact)" for best results
DEAD
Training
- Training guide for textual inversion/embedding and hypernetworks: https://pastebin.com/dqHZBpyA
- Hypernetwork Training by ixynetworkanon: https://rentry.org/hypernetwork4dumdums
- Training with e621 content: https://rentry.org/sd-e621-textual-inversion
- Wiki: https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Textual-Inversion
- Wiki 2: https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#textual-inversion
Use pics where:
- Character doesn't blend with background and isn't overlapped by random stuff
- Character is in different poses, angles, and backgrounds
- Resolution is 512x512 (crop if it's not)
- Manually tagging the pictures allows for faster convergence than auto-tagging. More work is needed to see if deepdanbooru autotagging helps convergence
- Dreambooth on 8gb: https://github.com/huggingface/diffusers/tree/main/examples/dreambooth#training-on-a-8-gb-gpu
- Finetune diffusion: https://github.com/YaYaB/finetune-diffusion
- Can train models locally
- Training guide: https://pastebin.com/xcFpp9Mr
- Reddit guide: https://www.reddit.com/r/StableDiffusion/comments/xzbc2h/guide_for_dreambooth_with_8gb_vram_under_windows/
- Reddit guide (2): https://www.reddit.com/r/StableDiffusion/comments/y389a5/how_do_you_train_dreambooth_locally/
- Dreambooth (8gb of vram if you have 25gb+ of ram and Windows 11): https://pastebin.com/0NHA5YTP
- Another 8gb Dreambooth: https://github.com/Ttl/diffusers/tree/dreambooth_deepspeed/examples/dreambooth#training-on-a-8-gb-gpu
- Dreambooth: https://rentry.org/dreambooth-shitguide
- Dreambooth: https://rentry.org/simple-db-elinas
- Image Scraper: https://github.com/mikf/gallery-dl
- Anon's Guide:
- Having good text tags on the images is rather important. This means laboriously going through and adding tags to the BLIP tags and editing the BLIP tags as well, and often manually describing the image. Fortunately my dataset had only like...30 images total, so I was able to knock it out pretty quick, but I can imagine it being completely obnoxious for a 500 image gallery. Although I guess you could argue that strict prompt accuracy becomes less important as you have more training examples. Again, if they would just add an automatic deepdanbooru option alongside the BLIP for preprocessing that would take away 99% of the work.
- Vectors. Honestly I started out making my embedding at 8, it was shit. 16, still shit but better. 20, pretty good, and I was like fuck it let's go to 50 and that was even better still. IDK. I don't think you can go much higher though if you want to use your tag anyway where but the very beginning of a 75 token block. I had heard that having more tokens = needing more images and also overfitting but I did not find this to be the case.
- The other major thing I needed to do is make a character.txt for textual inversion. For whatever reason, the textual inversion templates literally have NO character/costume template. The closest thing is subject which is very far off and very bad. Thus, I had to write my own: https://files.catbox.moe/wbat5x.txt
- Yeah for whatever reason the VAE completely fries and fucks up any embedding training and you can only find this from reading comments on 4chan or in the issues list of the github. The unload VAE when training DOES NOT WORK for textual embedding. Again, I don't know why. Thus it is absolutely 100% stone cold essential to rename or move your vae then relaunch everything before you do any textual inversion training. Don't forget to put it back afterwards (and relaunch again) because without the VAE everything is a blurry mess and faces and like sloth from the goonies.
So all told, this is the process:
- Get a dataset of images together. Use the preprocess tab and the BLIP and the split and flip and all that.
- Laboriously go through EVERY SINGLE IMAGE YOU JUST MADE while simultaneously looking at their text file BLIP descriptions and updating them with the booru tags or deepdanbooru tags (which you have to have manually gotten ahead of time if you want them), and making sure the BLIP caption is at least roughly correct, and deleting any image which doesn't feature your character after the cropping operation if it was too big. EVERY. SINGLE. IMAGE. OAJRPIOANJROPIanrpianfrpianra
- Now that the hard parts over, just make your embedding using the make embedding page. Choose some vector amount (I mean I did good with 50 whatever), set girl as your initialization or whatever's appropriate.
- Go to train page and get training. Everything on the page is pretty self explanatory. I used 5e-02:2000, 5e-03:4000, 5e-04:6000, 5e-05 for the learning rate schedule but you can fool around. Make sure the prompt template file is pointed at an appropriate template file for what you're trying to do like the character one I made, and then just train. Honestly, it shouldn't take more than 10k steps which goes by pretty quick even with batch size 1.
OH and btw, obviously use https://github.com/mikf/gallery-dl to scrape your image dataset from whichever boorus you like. Don't forget the --write-tags flag!
Vector guide by anon:
Think of vectors per token as the number of individual traits the ai will associate with your embedding. For something like "coffee cup", this is going to be pretty low generally, like 1-4. For something more like an artist's style, you're going to want it to be higher, like 12-24. You could go for more, but you're really eating into your token budget on prompts then.
Its also worth noting, the higher the count, the more images and more varied images you're going to want.
You want the ai to find things that are consistent thematics in your image. If you use a small sample size, and all your images just happen to have girls in a bikini, or all with blonde hair, that trait might get attributed to your prompt, and suddenly "coffee cup" always turns out blonde girls in bikinis too.
Common questions (CTRL/CMD + F):
Questions to add:
What model is the best?
How do i convert img1 to img2?
What is the abs easiest way to download this?
How do i speed up generation?
what is a tokenizer?
what is parsing?
what is float 16?
what is a vae?
How do I set this up?
Refer to https://rentry.org/nai-speedrun (has the "Asuka test")
AMD Guide: https://rentry.org/sdamd
- After setting stuff up using this guide, refer back to https://rentry.org/nai-speedrun for settings
What's the "Hello Asuka" test?
It's a basic test to see if you're able to get a 1:1 recreation with NAI and have everything set up properly. Coined after asuka anon and his efforts to recreate 1:1 NAI before all the updates.
Refer to
- https://github.com/AUTOMATIC1111/stable-diffusion-webui/discussions/2017
- Very easy Asuka 1:1 Euler A: https://boards.4chan.org/h/thread/6893903#p6894236
- Asuka Euler guide: https://imgur.com/a/DCYJCSX
- Asuka Euler a guide: https://imgur.com/a/s3llTE5
What is pickling/getting pickled?
ckpt files and python files can execute code. Getting pickled is when these files execute malicious code that infect your computer with malware. It's a memey/funny way of saying you got hacked.
What is difference merging/why is there a way to merge three models?
The first two models are merged using standard interpolation. The third model is for a difference merge.
- For models A, B, and C:
- The formula is A + (B - C) * (1 - M), where
- A is the model where the learning is going to be transfered
- B is the model that has been finetuned (trained) on a certain object
- C is the base model that was used to finetune B
- B-C is difference between B and C, which is added to A
- (1-M) is the multiplier > how much of the difference to add to A
- (1-M) is in the slider in the UI, where the slider being on the right makes (1-M) = 1
- The formula is A + (B - C) * (1 - M), where
How would distributed training work?
According to NeonTheCoder: "well a model trained ontop of another would be the same, plus added data, and slided data.
if you subtract the original from that you should be left with the difference, and the new data.
then if you add that ontop of another model, it should only be adding the difference it made from original SD to the target model, and the new data"
Basically: You train a model, subtract the original model so you only have the "trainings", then add the trainings to aonther model. This means you can delegate training tasks to different people and add up all the results.
Why doesn't my 4090 work?
You need to update your cuDNN or use an updated xformer.
Uploaded cuDNN files by anon (which means it might be pickled):
- Goes into stable-diffusion-webui\venv\Lib\site-packages\torch\lib if you're using venv, otherwise wherever your torch is installed.
What GPU should I buy?
Refer to https://docs.google.com/spreadsheets/d/1Zlv4UFiciSgmJZncCujuXKHwc4BcxbjbSBg71-SdeNk/. Generally, higher VRAM is better.
What does Stability AI's "no nudity" for their SFW model mean for us?
It's only speculation, but probably a loss in accurate anatomy and overall NSFW stuff. We can always train NSFW into the released model, though the quality will probably be worse than if Stability AI did it (thousands/millions of images vs billions of images).
What's the difference between an embedding and a hypernetwork?
By anon: Embeddings add new tokens to the vocabulary but leave the model unchanged, hypernet alters the behavior of the network itself within the layers - hypernet has a lot more capacity to change the behavior but you can obviously only have one active at once
Why does my output differ from someone else's output?
Check to see if your settings match theirs. Also, using an optimization such as lowvram, medvram, and xformers will cause variations in outputs.
Hi-res generations are affected by the video card used
Why do I keep getting/how do I fix a black output when using .vae with the NAI model?
Using --no-half-vae will fix the random black images when using the .vae
How do you add upscalers?
Put the files into stable-diffusion-webui/models/ESRGAN or GFPGAN, it should say on https://upscale.wiki/wiki/Model_Database
How do you add embeddings?
Make a folder in your webui install (next to webui-user.bat) named embeddings > put your .pt and .bin embedding files here
Why are my faces blurry/messed up/ugly/deformed/etc.?
This could be because of a variety of things. Generally, to fix this, try generating at a higher resolution, using hi-res fix, inpainting your face normally, inpainting your face at full resolution, editing a good face on top of your face and img2img-ing, adding pretty face (or some variant) to the positive prompt and ugly face (or some variant) to the negative prompt, and making the ai focus more on the face with a closer shot (e.g. "portrait shot").
What is textual inversion?
Textual inversion makes the ai brute forces tags that it thinks matches your imgs and creates an embedding. Doing this on a subject in many situations (e.g. different environments and poses) generally allows the AI to create better embedding
Stuff doesn't work/is outdated!
Git pull or do a fresh install by git cloning into another folder. You can also git reset --hard [commit id], but be careful of overwriting your outputs/embeddings/models
What is ENSD?
ENSD is eta noise seed delta (in the settings). It shifts your seed and does some eta/sigma stuff. NAI uses 31337
Is the leaked NAI model safe?
The risk isn't 0, but there hasn't been any reports of getting hacked/pickled yet. Only you can decide if it's safe enough for you to use.
Is anything here safe??
Similarly, the risk isn't 0, but no one has gotten hacked from any links here as far I ask know.
Help! I need a prompt and I don't know where to start
Find a prompt someone else used and repurpose it for yourself. Think if what you like and just start writing tags/descriptions. If you need a tag but don't know the Danbooru equivalent, you can usually find it by searching danbooru [write what tag you want here]
How do I make better pictures?
For a general workflow:
- paint something really crude, it can literally be blobs of color
- img2img with a prompt
- edit original img or prompt or output input
- reimg2img/inpaint
- repeat last few steps until you get what you want
Step 1 can be replaced with just starting with a txt2img if you want the AI to decide for you
What is no-half and full precision?
Most new GPUs will use half precision since it lowers VRAM. Only use no-half and/or full-precision if you want to get the absolute best quality (minor difference) or if you are running a 16xx card.
How to inpaint?
- Good guide: https://rentry.org/drfar
- TLDR: Mask > describe ONLY the part you're inpainting > generate
Why doesn't inpainting work?
- Try running in incognito/private browsing mode, adblockers and certain plugins/extensions break inpainting
- Try refreshing/restarting the webui
How do you get NAI (NovelAI) 1:1?
Does order of prompts matter?
Yes, the order = priority that the AI will put in your img
How do I setup NAIFU?
Read the text file that tells you how to in the download
By anon: (Windows):
- Make sure you install Python and check "Add Python to PATH": https://www.python.org/downloads/windows/
- Download the naifu torrent from this link:https://rentry.org/sdg_FAQ#naifu-novelai-model-backend-frontend.
- Inside of the naifu folder, right click program.zip and click "extract here" with 7zip or WinRAR.
- Run setup.bat and let it finish.
- Run run.bat and once it's running, open a new browser window/tab and make sure that you type in http://localhost:6969/ into the address bar.
- Bada bing bada boom you should have the site running locally on your PC.
What upscaler should I use?
I recommend SD Upscaler, it adds details as well as upscales. For a while LSDR was regarded as the best, this might've changed though. Some anons like swinir, some like esrgan4x, ymmv
How do I know if X is loaded?
Ususally, the console will tell you. It will not tell you if hypernetworks or v2.pt is loaded
How do I update?
open command prompt in auto's folder and type "git pull". Or, right click in the folder, git bash here, git pull. To make sure you have the requirements, run "pip install -r requirements.txt" in the same fashion.
Recommended Settings (need to update this)?
- default NAI negatives: 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
- Supposedly adding "artist name" into here improves results
- Prefix all prompts with masterpiece, best quality
- Apparently NAI adds another hidden "masterpiece" after "best quality", but this might've been debunked already
For non-NAI models: Clip skip 0, everything else is good (afaik don't use hypernetworks, v2, yaml, VAE)
What are (parentheses), [brackets], {this thing}, <>, and decimals?
() is more emphasis, [] is less emphasis, {} is NAI's "implementation" of (), <> is for embeddings, decimals specify the number of ()'s so you don't need to type in a bunch.
(boobs) would have more weight than [boobs] in the final result, (boobs:1.4) would increase the boobage by ~40% more than what they would've normally been, (boobs:0.6) will decrease it by ~40%.
([prompt]:[number less than 1]) = [using this syntax]
2 of {} = 1 of (), accurate with a difference of <1%
by anon: exceeding 3x () or [] is less predictable and can overcook your prompt
How do you escape/use () for series names (or whatever is in () that isn't supposed to be weighted) in prompts?
- https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#prompt-editing
- character \(franchise\)
What is prompt editing?
- https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#prompt-editing
- Follows the format of [P1:P2:[step # to change from P1 to P2]]
- Good for creating a base with P1 and adding details with P2
- Loads one prompt for x steps, then runs the next prompt
- If the number is between 0 and 1, it's a fraction (percentage) of the number of steps after which to make the switch. If it's an integer greater than zero, it's just the step after which to make the switch.
- Example: The prompt is "a [fantasy:cyberpunk:16] landscape"
The model will draw a fantasy landscape for 16 steps. After step 16, it will switch to drawing a cyberpunk landscape
- Example: The prompt is "a [fantasy:cyberpunk:16] landscape"
What is AND?
AND combines prompts together:
A good metaphor to remember when prompting: P1 AND P2 AND P3 for 10 steps = P1 step 1, P2 step 2, P3 step 3, P1 step 4, etc... P1 step 10. It's good for combining two different prompts together, such as a background prompt and a subject prompt.
By kind anon: each prompt creates a "guidance" vector saying how to change the image to "match" the prompt, whatever that is, and AND makes you have TWO prompts pulling the image in different directions (that get added together)
What are negative prompts?
By kind anon: this is also how negative prompts work-- it computes how to change the image to go towards the negative prompt, and SUBTRACTS that to move away from it
What are positive prompts?
- Positive prompts calculate how much each step should move toward the positive prompt. Adding weights increases how much towards (or past) the positive prompt the AI will travel
What's my best option if I want to imitate a specific artstyle?
You could try finding someone similar, doing textual inversion, or describing the artsyle (eg thick stroke, lineart, etc.)
What are hypernetworks, VAE, v2.pt, etc?
Hypernetworks are like styles for your generation
VAE's fix faces and eyes, is generally good, but seems to dull colors
- Disable if training
v2.pt censors and generally changes the whole composition. a lot of people don't like it
yaml doesn't seem to do anything except double ram usage
What is Deep Danbooru?
Deep Danbooru is an autotagger. The AI automatically finds Danbooru tags that it thinks matches the picture it's given. To activate it
- git pull, edit webui-user.bat
- add the --deepdanbooru argument to webui-user.bat so it looks like COMMANDLINE_ARGS=--deepdanbooru
- find the interrogation change in img2img.
How do I get NAIFU to automatically save images for me?
Edit run.bat. Ctrl + f to "export SAVE_files". Remove the "::" and change the word from export to set.
How do you load the VAE?
Rename it to [your model's name here].vae.pt and put it next to your model in the models/Stable-diffusion folder
How do you load hypernetworks?/How do you use hypernetworks?
create a hypernetworks folder in the models folder and place all the .pt files there
How do you load the v2.pt?
place the v2.pt in the same folder as your webui-user.bat file (the root folder) and add https://rentry.org/nai-prior-v2 into your scripts folder (rename the text file to [anything].py
How do you load the yaml?
It's not recommended to load the yaml because it doubles ram for no change in output, but if you really want to, rename it to [model name].yaml and place it next to your model.
Asukaimguranon: I will report that the yaml didn't double my vram usage outright, but i experienced something like a memory leak because it oom crashed after a dozen gens at most (compared to non-yaml for hundreds of gens no problem). the gens i did get matched non-yaml 1:1 so there's basically no reason to use yaml ever.
What are wildcards?
by anon: wildcard just lets you create a text file with a list of prompt words, and then you reference that text file to randomly pick from it, so you could randomize hair color, or pose, specific character, etc
Where do you get wildcards?
Got this info from a kind anon in hdg: Search archive or git for wildcard pastebin and copy what you want. Then, download wildcards.py from AUTOMATIC1111's wiki. Place script + pastebin text files (which are in a folder named wildcards, the text files are named [wildcard name here].txt) in /scripts. Activate wildcards in AUTO's gui. In a prompt, you would write [wildcard name here] to choose a random name from that txt file. To use weights: ([wildcards name here]:[weight amount])
- Example wildcards: https://github.com/jtkelm2/stable-diffusion-webui-1/tree/master/scripts/wildcards
- Dump: check links
What is interpolation when merging models?
It determines how much of each model is in the output model. if number is 40 for linear: 40% primary, 60% secondary. If number is 40 for sigmoid or inverse sig, this percent is weighted according to the graphs. sigmoid: primary checkpoint gets less weight than if using weighted sum. inverse sigmoid: opposite to sigmoid
- https://archived.moe/g/thread/89007676#89008490
- Calculate values yourself: https://github.com/AUTOMATIC1111/stable-diffusion-webui/commit/c250cb289c97fe303cef69064bf45899406f6a40#comments
- Graph + Info: https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/2658#issuecomment-1279581042
Can you make X?
If you're creative enough, probably. If it was trained on that, definitely
Rentrys + Link Dump, will sort:
TLDR of everything: https://rentry.org/sd-tldr
Current Issues: https://rentry.org/sd-issues
Info:
- Detailed 1:1 setup NAI + current news: https://github.com/AUTOMATIC1111/stable-diffusion-webui/discussions/2017
- Very easy Asuka 1:1 Euler A: https://boards.4chan.org/h/thread/6893903#p6894236
- Asuka Euler guide: https://imgur.com/a/DCYJCSX
- Asuka Euler a guide: https://imgur.com/a/s3llTE5
- Beginner's Guide: https://rentry.org/nai-speedrun
- SD NAI FAQ: https://rentry.org/sdg_FAQ
- general wiki: https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki
- general wiki 2: https://wiki.installgentoo.com/wiki/Stable_Diffusion
- setup guide: https://rentry.org/voldy
- Easy to setup Standard Diffusion: https://nmkd.itch.io/t2i-gui
- Another easy to setup SD: https://github.com/cmdr2/stable-diffusion-ui
- Models: https://rentry.org/sdmodels
- Japanese 4chan
- General info: https://rentry.org/sd-nativeisekaitoo
- Guide: https://github.com/Engineer-of-Stuff/stable-diffusion-paperspace/blob/main/docs/archives/VOLDEMORT'S%20GUI%20GUIDE%20FOR%20THE%20MENTALLY%20DEFICIENT.pdf
- NAI info: https://pastebin.com/cExyWkgy
- GPU buying guide: https://rentry.org/stablediffgpubuy
- CSP SD: https://github.com/mika-f/nekodraw
Boorus:
- Danbooru: danbooru.donmai.us/
- Gelbooru: https://gelbooru.com/
- AIBooru: https://aibooru.online/
- Booru Site: https://infinibooru.moe/
- Local (classic): hydrusnetwork.github.io/
- AI art here: https://e-hentai.org/g/2343153/b4ce2a4b0b
- Easy to setup booru/image gallery by anon, highly recommended: https://github.com/demibit/stable-toolkit
- History tab (extension): https://github.com/yfszzx/stable-diffusion-webui-images-browser
Upscalers:
- Big list: https://upscale.wiki/wiki/Model_Database
- anon recommended this: https://arc.tencent.com/en/ai-demos/imgRestore
Batch resize:
Git pull/revert guide:
Horde: https://stablehorde.net
A prompt dump:
https://pastebin.com/rbrtPCqZ
Part 1 NAI (with all the trackers I can find):
Part 2 NovelAI Leak: https://rentry.org/ewahd
not sure what this is: https://rentry.org/naifunya
UNPICKLER: https://rentry.org/safeunpickle2
Prebuilt xformers: https://rentry.org/25i6yn
img search: https://iqdb.org
Chinese NAI: https://ai.nya.la/
Guide to setting up local NAI by chinese NAI:
Rebasin (alternative merging models): https://github.com/samuela/git-re-basin
WD 1.3 Torrents: https://rentry.org/WDtorrents
learn ai (recommended by emad): https://www.fast.ai/
https://jalammar.github.io/illustrated-stable-diffusion/
- SDToolkit: all in one generator + upscaler
AMD Ubundo 20.04
Mac: try using invoke ai https://github.com/invoke-ai
Danbooru dump: https://www.gwern.net/Danbooru2021
Outdated training: https://rentry.org/informal-training-guide
Free browser SD: https://huggingface.co/spaces/stabilityai/stable-diffusion
https://promptart.labml.ai/playground
https://novelai.manana.kr/
https://boards.4channel.org/g/thread/89199040
https://www.mage.space/
https://github.com/TheLastBen/fast-stable-diffusion
AMD Guide: https://rentry.org/ayymd-stable-diffustion-v1_4-guide
Furry dump from SD Labs server: https://e621.net/db_export/
2.5 mill posts from e621 with source links and more detailed tag info>>
https://mega.nz/file/kxN0zZSC#DaGsogjU_pURYxm1T7ZB8MOvjetuU2tRJBGpJ5m8bK4
Furry model tag counts >> https://mega.nz/file/AgdHDLLD#vERcoYTWGJguTsXmysbLq1NL_xBS8txQhVvPI5E3QKE
some 4chan alt afaik, maybe loli stuff: https://2chen.moe/tech/1909555?#bottom
Japanese chan:
https://www.2chan.net/
Krita: https://github.com/Interpause/auto-sd-krita
cool showcase: https://www.thispersondoesnotexist.com/
Voldy to NAI ui: https://pastebin.com/0NTMWFtb
- save this to the root directory as user.css
Book: https://github.com/joelparkerhenderson/stable-diffusion-image-prompt-gallery
Celebs: https://docs.google.com/spreadsheets/u/0/d/1IqXkYDXux97aU8Y5kqqBrBvCn3CLRDhMZ7lEWsAtwUc
Multi GPU: https://hastebin.com/raw/labumiyiqo
Barebones SD: https://github.com/AmericanPresidentJimmyCarter/stable-diffusion
Deep Danbooru: https://github.com/KichangKim/DeepDanbooru
Explorer thing: http://cybernetnews.com/find-replace-multiple-files
Messy room: https://twitter.com/8co28/status/1583434494354210817
Video FPS interpolator: https://github.com/megvii-research/ECCV2022-RIFE
GPU speed comparison
* https://lambdalabs.com/blog/inference-benchmark-stable-diffusion/
Confirmed Drama
10/20 News
TLDR from reddit:
- RunwayML releases the v1.5 model on their repo
- Copyright takedown notice from StabilityAI
- RunwayML CEO releases a slightly passive agressive message reminding that they have the right to release the model, which was created by a RunwayML Researcher and a University researcher. "Thanks" StabilityAI for the offered processing power
- Emad (StabilityAI) responds on the Discord stating the copyright takedown notice was just a mistake. He states they have never prevented the release of a model, and they just want to make sure Stable Diffusion doesn't face legal issues. No word on the disagreement in itself, but it seems to imply that RunwayML disagreed on the way StabilityAI wanted to navigate the legal issues, and decided to just release the model.
- TLDR: https://www.reddit.com/r/StableDiffusion/comments/y99yb1/a_summary_of_the_most_recent_shortlived_so_far/
- Takedown notice: https://www.reddit.com/r/StableDiffusion/comments/y969ph/model_15_legal_investigation_and_takedown_warning/
- CEO Statement: https://www.reddit.com/r/StableDiffusion/comments/y97ya0/official_response_on_sd_15_model_by_chris_at/
- Link: https://www.reddit.com/r/StableDiffusion/comments/y960o8/stability_ai_issues_takedown_request_for/
Quick Rundown:
emad confirming censorship for 1.5, no more porn
Might cause anatomical issues in released model. Non-issue for NSFW though, especially with model merging
Debunked, SD will probably release a SFW model before their 1.5 model because of legal issues
drama between emad and automatic1111
Emad issued a private and public apology over it
AUTOMATIC v. StabilityAI:
- Summary: https://www.reddit.com/r/StableDiffusion/comments/y1uuvj/automatic1111_did_nothing_wrong_some_people_are/
- Funny, not sure if real, apparently it is: https://github.com/AUTOMATIC1111/stable-diffusion-webui/discussions/2509
- Control given back to community: https://www.reddit.com/r/StableDiffusion/comments/y1nc7t/rstablediffusion_should_be_independent_and_run_by/
- Mod's story: https://www.reddit.com/r/StableDiffusion/comments/y19kdh/mod_here_my_side_of_the_story/
- by anon: I think [StabilityAI] backpedaled a bit, offered to unban automatic. Offered to give control of community places back to the community.
- automatic1111's repo removed from pinned guide on r/stablediffusion
- all old mods on stable diffusion subreddit kicked and replaced by stabilityai members. Big discourse on corruption and true open-source training
Emad will supposedly not censor the expected Stability AI model release since SAI are only training their SFW model
- Conversation from AMA:
User: is it a risk the new models (v1.X, v2, v3, vX) to be released only on dreamstudio or for B2B(2C)? what can we do to help you on this?
Emad: basically releasing NSFW models is hard right now Emad: SFW models are training
User: could you also detail in more concrete terms what the "extreme edge cases" are to do with the delay in 1.5? i assume it's not all nudity in that case, just things that might cause legal concern?
Emad: Sigh, what type of image if created from a vanilla model (ie out of the box) could cause legal troubles for all involved and destroy all this. I do not want to say what it is and will not confirm for Reasons but you should be able to guess.
User: what is the practical difference between your SFW and NSFW models? just filtering of the dataset? if so, where is the line drawn -- all nudity and violence? as i understand it, the dataset used for 1.4 did not have so much NSFW material to start with, apart from artsy nudes
Emad: nudity really. Not sure violence is NSFW
By the question asker:
just want to clarify a misunderstanding that seems to have taken hold to do with 1.5 censorship
i was the person asking emad about the clarifications about "extreme edge cases" and the difference between their NSFW and SFW models
the context of that question was emad was speaking about how SFW models are easier to release right now because of potential legal issues with the NSFW models, and about training a separate set of SFW models
the "extreme edge cases" question was about 1.5 specifically; as far as i understood it, 1.5 is one of their NSFW models and the "extreme edge cases" that they want to censor are cp, not all nudity
the "SFW vs NSFW" question was about the distinction between two category of models that emad was referring to, the SFW models are separate and trained with most (all?) nsfw content filtered from the dataset, but not violence
of course i'm not trying to shill for them or anything, and we'll see the true extent of the censorship if/when they release the models, but at the very least this is what was actually said
Unconfirmed Drama
Quick Rundown:
drama around models supposedly trained on CP
Don't download every random model link you come across
Whether the fed bait is an actual fed bait or not cannot be confirmed
Some anons theorize that the fed bait wasn't due to the ckpt but was due to glowie anon's scraper downloading actual CP from a torrent somewhere using a DHT search engine
An anon claims to have tested the fed bait and said that the output a worse version of another existing model. Whether this is true or not cannot be confirmed
Another anon's theory: "if he truly did get his acct taken down, he mentioned auto-scraping torrents, then it's possible the fed did have a honeypot or tracking on that particular torrent (but they didn't make the content), that seems the most likely to me. if this was all a hoax to spread panic about a particular torrent, he chose a relatively unknown torrent to do it with, for example it would be explosive if he made these accusations about the original novelai torrent. he may be telling the truth, but he hasn't provided strong evidence backing up the full story, so there are a lot of grains of salt to be taken"
Fed Bait Information
Editor's note: I shortened the fed bait PSA because it was not officially confirmed by sources other than by the owner of SD training and the 4channer who got baited. It also took up too much space at the top. The fed bait info was a huge dump in the first place because it was a copy paste of the announcement from the SD training server and I got confirmation from the owner of SD training, and, if the announcement was true, it was a relevant and timely warning to delete/avoid downloading the pickle model. Even if this whole thing turns out to be a huge troll by both the owner and the 4channer, this situation showcases the danger of downloading random files from the internet.
Given the severity of the situation, the fed bait warning will stay a PSA (for now) to keep people wary of random ckpts/pts/vaes they download.
That being said, future drama on this rentry will be confirmed by multiple sources before being posted at the top. For the unconfirmed drama, refer to https://rentry.org/sdupdates#unconfirmed-drama.
TLDR: fed allegedly uploaded ckpt of CP as a honeypot, anon downloaded it and got a warning from their seedbox who got a warning from Child Exploitation and Online Protection Command
There are claims of a model trained on CP in the wild
It is alleged that these models were distributed by feds via torrents starting around October 11, 2022.
Similar (?) event last year: https://saucenao.blogspot.com/?view=classic
Original fed post:
Anon's statement: "one of our users was auto-scrapping every CKPT file on every tracker (pseudo) and they stumbled upon it, it had a weird name that literally nobody knew about until he searched on the 4chan archives and found what it was abt (pic related). then ofc he deleted it, and just a few minutes ago he told me he got a letter on his email from his seed box and it was abt "containing materials created and containing with sufficiently sexually suggestive images of minors" and it seems it was a fed bait"
Email from seedbox company:
Hall of Fame
AUTOMATIC1111/Voldy: Best webui, for the people, madlad gigachad
Leaker anon: Leaked NAI's imagen model + text gen
Asuka anon: Large 1:1 NAI efforts before all the updates
Booru anon: Self-hostable, intuitive, easy to setup booru
Asuka Test Imgur anon: easy to follow guides, helping out the rentry
Model anon: writing up https://rentry.org/sdmodels + helping out
Glowie'd anon: first public fed bait
Ixy anon: Good guide
todo:
Prune all discords and reddit for hypernets/embeds/dreambooths
Prompt Cheat Sheet Rentry: WIP
people to find: testers + prompters that want to contribute
author: questianon !!YbTGdICxQOw (malt#6065), ping or tag if I need to change anything or if you have questions