Model Introduction
This image generation model, based on Laxhar/noobai-XL_v1.0, leverages full Danbooru and e621 datasets with native tags and natural language captioning.
Implemented as a v-prediction model (distinct from eps-prediction), it requires specific parameter configurations - detailed in following sections.
Special thanks to my teammate euge for the coding work, and we're grateful for the technical support from many helpful community members.
⚠️ IMPORTANT NOTICE ⚠️
THIS MODEL WORKS DIFFERENT FROM EPS MODELS!
PLEASE READ THE GUIDE CAREFULLY!
Model Details
Developed by: Laxhar Lab
Model Type: Diffusion-based text-to-image generative model
Fine-tuned from: Laxhar/noobai-XL_v1.0
Sponsored by from:
Collaborative testing:
How to Use the Model.
Guidebook for NoobAI XL:
ENG:
https://civarchive.com/articles/8962
CHS:
https://fcnk27d6mpa5.feishu.cn/wiki/S8Z4wy7fSiePNRksiBXcyrUenOh
Recommended LoRa List for NoobAI XL:
https://fcnk27d6mpa5.feishu.cn/wiki/IBVGwvVGViazLYkMgVEcvbklnge
Method I: reForge
(If you haven't installed reForge) Install reForge by following the instructions in the repository;
Launch WebUI and use the model as usual!
Method II: ComfyUI
SAMLPLE with NODES
Method III: WebUI
Note that dev branch is not stable and may contain bugs.
1. (If you haven't installed WebUI) Install WebUI by following the instructions in the repository. For simp
2.Switch to dev branch:
git switch dev
3. Pull latest updates:
git pull
4. Launch WebUI and use the model as usual!
Method IV: Diffusers
import torch
from diffusers import StableDiffusionXLPipeline
from diffusers import EulerDiscreteScheduler
ckpt_path = "/path/to/model.safetensors"
pipe = StableDiffusionXLPipeline.from_single_file(
ckpt_path,
use_safetensors=True,
torch_dtype=torch.float16,
)
scheduler_args = {"prediction_type": "v_prediction", "rescale_betas_zero_snr": True}
pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config, **scheduler_args)
pipe.enable_xformers_memory_efficient_attention()
pipe = pipe.to("cuda")
prompt = """masterpiece, best quality,artist:john_kafka,artist:nixeu,artist:quasarcake, chromatic aberration, film grain, horror \(theme\), limited palette, x-shaped pupils, high contrast, color contrast, cold colors, arlecchino \(genshin impact\), black theme, gritty, graphite \(medium\)"""
negative_prompt = "nsfw, worst quality, old, early, low quality, lowres, signature, username, logo, bad hands, mutated hands, mammal, anthro, furry, ambiguous form, feral, semi-anthro"
image = pipe(
prompt=prompt,
negative_prompt=negative_prompt,
width=832,
height=1216,
num_inference_steps=28,
guidance_scale=5,
generator=torch.Generator().manual_seed(42),
).images[0]
image.save("output.png")
Note: Please make sure Git is installed and environment is properly configured on your machine.
Recommended Settings
Parameters
CFG: 4 ~ 5
Steps: 28 ~ 35
Sampling Method: Euler (⚠️ Other samplers will not work properly)
Resolution: Total area around 1024x1024. Best to choose from: 768x1344, 832x1216, 896x1152, 1024x1024, 1152x896, 1216x832, 1344x768
Prompts
Prompt Prefix:
masterpiece, best quality, newest, absurdres, highres, safe,
Negative Prompt:
nsfw, worst quality, old, early, low quality, lowres, signature, username, logo, bad hands, mutated hands, mammal, anthro, furry, ambiguous form, feral, semi-anthro
Usage Guidelines
Caption
<1girl/1boy/1other/...>, <character>, <series>, <artists>, <special tags>, <general tags>, <other tags>
Quality Tags
For quality tags, we evaluated image popularity through the following process:
Data normalization based on various sources and ratings.
Application of time-based decay coefficients according to date recency.
Ranking of images within the entire dataset based on this processing.
Our ultimate goal is to ensure that quality tags effectively track user preferences in recent years.
Percentile RangeQuality Tags> 95thmasterpiece> 85th, <= 95thbest quality> 60th, <= 85thgood quality> 30th, <= 60thnormal quality<= 30thworst quality
Aesthetic Tags
TagDescriptionvery awaTop 5% of images in terms of aesthetic score by waifu-scorerworst aestheticAll the bottom 5% of images in terms of aesthetic score by waifu-scorer and aesthetic-shadow-v2......
Date Tags
There are two types of date tags: year tags and period tags. For year tags, use year xxxx format, i.e., year 2021. For period tags, please refer to the following table:
Year RangePeriod tag2005-2010old2011-2014early2014-2017mid2018-2020recent2021-2024newest
Dataset
The latest Danbooru images up to the training date (approximately before 2024-10-23)
E621 images e621-2024-webp-4Mpixel dataset on Hugging Face
Communication
QQ Groups:
427280545
677964513
852429527
914818692
635772191
870086562
Discord: Laxhar Dream Lab SDXL NOOB
How to train a LoRA on v-pred SDXL model
A tutorial is intended for LoRA trainers based on sd-scripts.
article link: https://civarchive.com/articles/8723
Utility Tool
Laxhar Lab is training a dedicated ControlNet model for NoobXL, and the models are being released progressively. So far, the normal, depth, and canny have been released.
Model link: https://civarchive.com/models/929685
Model License
This model's license inherits from https://huggingface.co/OnomaAIResearch/Illustrious-xl-early-release-v0 fair-ai-public-license-1.0-sd and adds the following terms. Any use of this model and its variants is bound by this license.
I. Usage Restrictions
Prohibited use for harmful, malicious, or illegal activities, including but not limited to harassment, threats, and spreading misinformation.
Prohibited generation of unethical or offensive content.
Prohibited violation of laws and regulations in the user's jurisdiction.
II. Commercial Prohibition
We prohibit any form of commercialization, including but not limited to monetization or commercial use of the model, derivative models, or model-generated products.
III. Open Source Community
To foster a thriving open-source community,users MUST comply with the following requirements:
Open source derivative models, merged models, LoRAs, and products based on the above models.
Share work details such as synthesis formulas, prompts, and workflows.
Follow the fair-ai-public-license to ensure derivative works remain open source.
IV. Disclaimer
Generated models may produce unexpected or harmful outputs. Users must assume all risks and potential consequences of usage.
Participants and Contributors
Participants
L_A_X: Civitai | Liblib.art | Huggingface
li_li: Civitai | Huggingface
nebulae: Civitai | Huggingface
Chenkin: Civitai | Huggingface
Euge: Civitai | Huggingface | Github
Contributors
Narugo1992: Thanks to narugo1992 and the deepghs team for open-sourcing various training sets, image processing tools, and models.
Onommai: Thanks to OnommAI for open-sourcing a powerful base model.
V-Prediction: Thanks to the following individuals for their detailed instructions and experiments.
adsfssdf
madmanfourohfour
Community: aria1th261, neggles, sdtana, chewing, irldoggo, reoe, kblueleaf, Yidhar, ageless, 白玲可, Creeper, KaerMorh, 吟游诗人, SeASnAkE, zwh20081, Wenaka~喵, 稀里哗啦, 幸运二副, 昨日の約, 445, EBIX, Sopp, Y_X, Minthybasis, Rakosz, 孤辰NULL, 汤人烂, 沅月弯刀,David, 年糕特工队,
Description
After a two-week interval, Laxhar Lab has updated the NoobAIXL-V pred version to 0.75S. We have noticed that NovelAI v4 is already in training, and we are very grateful for their work. This also indicates that our fans' urging for updates has yielded some results. Everyone is looking forward to something new for the anime model. Speaking of which, the new developments in version 0.75S are as follows:
(1) It has advanced 4 epochs on the H100 GPU from the previous version, and has strengthened the concept of not having a fixed number of images for EPS;
(2) The characteristic of having more background noise in version 0.65S has been essentially removed, and now you can generate cleaner images;
(3) The saturation adaptation for different samplings has been basically completed, making the colors more accurate;
(4) Learning from Cos and anime screenshots has had some effects, but more training is needed before reaching the ideal effect. Please stay tuned for subsequent versions.
FAQ
Comments (156)
Another pre-Sunday release? Epic.
very epic for the win
amazing!
As someone else mentioned, it'd be amazing if NoobAi trains on Gelbooru instead of Danbooru. Gelbooru has far more artists represented on their site than Danbooru does along with more arts for characters as well. I'd even vote to train on the Rule34 website because that, too, has a ton of artists that aren't even represented on Danbooru or Gelbooru. I'm hoping they switch to training with Gelbooru, but they'd probably have to restart all over since the entire NoobAi model has been trained on Danbooru and E621 :/
Chan Sankaku Complex has a lot of artists too, maybe even more than Gelbooru
@Zeivon The problem with Sankaku Complex is a lot of their art is hidden behind that stupid membership.
@madaraxuchiha88 No it's not hidden, you just need a free account and you can see everything, I have a free acount and I see everything, it's only hidden if you open a lot of tabs, but the dataset can be obtained in a different way, no?
Rule34 has a lot of garbage on it though. And I'm not talking about just the deluge of AI slop, there's a whole load of horrible quality human-generated art on there too. Lots of quality filtering would be needed.
@Zeivon Sankaku is filled with low quality, untagged furry and doujinshi pages. I'm pretty sure that'd be a detriment to the model and literally hell to sort through and fix.
@Boatr0t that's why there are filters of quality and I would say that Danbooru has a lot more images with low quality
@Zeivon That's the thing. If were tagged, there would be no issue. However, plenty of them aren't. Sankaku's quality control is much much lower and became worse after they added that damn furry bot that uploads all the furry images.
@Boatr0t I see, yeah maybe only the top quality ones are good but I guess it's not enough to train a model
Seconded to use Gelbooru instead. But because i think Danbooru is such a dogshit site, why the fuck Danbooru locked loli/R-18G stuff behind paywall and only limiting search to 2 keywords?! Fuck that , nobody should use that garbage site.
R-18G isn't locked and the loli lock doesn't apply to AI training because the datasets models like Noob use have that content in there. Also the payment option doesn't exist anymore but you can get access to censored content by uploading images to the site or winning one of the raffles they do pretty often. I do think that free users should have at least 3 tags to search, however.
Can someone explain why two types of models are being trained (v-prediction and eps-prediction)?
I don't know the official reasoning but eps has better compatibility with sd ecosystem while vpred can in theory achieve better training results.
NoobAI makes NovelAI look like noobs
not til NovelAI v4 release thou
Can i use v-pred model on SD WebUI Forge?
Yes, but not release version. You need git clone it.
@special_offer_ubik 方法1reForg 404了
@506291394340 他現在改成叫 dev2 枝
Please enable the 1.1 version for online image generation.
Ask Civitai not the uploader, they don't decide this.
This is my comparison test between v-pred 0.75 and v-pred 0.65
Comparison test between v-pred 0.75 and 0.65
In general 0.75 is more like a contrast strengthened version of 0.65. The bright part is brighter, the dark part is darker. Meanwhile 0.75 has a tend to make the graphic cleaner by not generating as many details as 0.65 does and making the main character more emphasized by drawing dark shadow or blurry background around. In cases of light & shadow contrast scenes, and character-emphasized portrait, 0.75 def has better performance, but in other bright cases it's hard to say which one is better. In my test 0.75 in many cases can have worse understandings of composition compared to 0.65.
Another sure thing is that 0.75 is better at face restoration than 0.65. It'll consider more about lighting when doing it and the line art is almost as clear as 0.5's.
My recommended combination of 0.65 (base image) + 0.5 (face restoration) can be updated to 0.75/0.65 (base image) + 0.75/0.5 (face restoration) now
Pretty helpful, btw, do you use natural language or you stay on tags?
@P_Universe tags
From your examples, I definitely prefer 0.65S. Though we might be using different settings overall, so who knows, how they'll perform on my setup. But thank you for the comparison!
Continuing background detail testing for v-pred 0.75s: https://civitai.com/images/44370110
Background detail seems to be coming out a lot better than previous versions now, though saturation has gone up quite a bit.
Previous comparisons:
0.65s: https://civitai.com/images/41816718
0.6: https://civitai.com/images/40600489
0.5: https://civitai.com/images/40437110
saturation is easily fixed through various cfg techniques but detail is not fixable so is a good job for me
i think gelbooru > danbooru mostly because it just has more images on all artists
Not just artists, it has more useful tags and better tagged images overall.
I always thought its the other way around :\
Gelbooru was my first imageboard, I do notice that some artists have a lot more artwork on it compared to Danbooru
More images does not mean it's better. I don't know why this has to be explained at all, but Gel in general is where the bad images that can't get uploaded to Dan go to be dumped. They're not good to train on. In general the only reason you're seeing more images is because those images were deleted on Dan. I'd rather not see the dataset filled up with garbage.
80% of Gelbooru is a direct scrape of Danbooru which doesn't get updated tags from Danbooru posts. The remaining 20% is content that would be rejected from Danbooru because of its quality or off-topic nature. Danbooru is a far more well curated dataset.
@lopi9999 But, some things have been deleted from dan, like artists with 1000+ pics who asked to have all their data removed, those still exist on gel, so gel is better as archive & where those artists pics can still be uploaded/etc.
@fizalpher So like... 1% of Gel is actually good to train on? What's even the point then? Train a LoRA if you're interested in those artists. Unless if you can compile a list of actually good artists who got banned from Dan but are still on Gel and only train on Gel with those artists, I don't think it'll help the model in any way to just train everything on Gel. Let's not even talk about how bad Gel tags are, they are some of the worst tags I've seen, the only site with worse tags is Sankaku. So many minimal tag posts and posts with just bad tags in general.
@lopi9999 sakimichan? 1000 posts but removed from danbooru for "DMCA"... yea no. Gelbooru keeps that shit up.
@fizalpher I think in case of deleted artists it would be better to add gelbooru images only for them. Not just blindly grab all gelbooru.
ah yes so Dan is much more organized after all haha 😅 but I do agree that some artist have their work deleted on Dan which is understandable, but then again if you are looking for those artist on Gel that aren't on Dan then lora is the only way to go about it I suppose..?
I am using reforge and trying to use v-pred on it and I am getting really bad results (I got CFG rescale and everything that is needed, at least I think). Not sure if it is just because or my prompts or a specific setting I am missing but can someone help out?
When I prompt for an artist, it doesn't not look anything like the style.
what's the difference between V-PRED and EPS?
"NoobAI-XL provides both noise prediction (or say epsilon prediction) and V-prediction versions. In short, the noise prediction version generates more diverse and creative images, while the V-prediction version follows the prompts more and generates images with a wider color gamut and stronger lighting."
v-pred doesnt run in A1111 while e-pred does, which is the main one.
@burnera679889 A1111 is the main one? Ahaha funny joke. A1111 is relatively dead.
@burnera679889 vpred models have worked on a1111 for over a year
@scringle Not in main branch, no. The model loads, but it gives bizzare results that dont produce anything remotely resembling a coherent image.
@burnera679889 you have to create a .yaml file from the safetensors model configuration, which includes the prediction type parameter, a1111 doesn't support the new standard but you can still load vpred models using the old format
I believe a lot of the complaints about incorrect colors come from users accidentally misusing the model and shouldn't be worked on if it has the slightest chance of compromising it. More accurately: Oversaturation and incorrect colors are a result of the CFG setting being set too high compared to what the model works well with. Most SDXL models work the best with CFG between 5 and 9, but Illustrious or at least Noobai works best with CFG set to 2 in my experience and the outputs are usually flawless with the right sampler settings (my current most commonly used parameters are dpm++ 2s ancestral sampler, normal scheduler, zsnr turned on for vpred models and Perturbed Attention Guidance set to 3)
You are actually using guidance equal to 5 and don't even know it. You see, since you are using PAG set to 3 - it is being added together with CFG to total guidance of 5 (that's just how it works), which is something that preview images here use too.
is PAG even working? I got the extension but turning it on and off made no difference on reforge...
There's some more settings you may refer to: https://d0xb9r3fg5h.feishu.cn/docx/YpOQdtHTDoetcZxIO9fc33onnee?from=from_copylink
@Euge_ Thx!
I finally got it working well with DPM ++ 2S ancestral, the PAG doesn't really work with it but I put the CFG at 1.7 and it works like a charm. It's very setting sensitive and it needs very specific prompting especially with artist styles. Small changes lead to huge differences - I think that's what a lot of people aren't used to.
@zendashi528 @munchkin I'm using ComfyUI PAG, could be why. Also quite sure PAG doesn't work like increasing CFG, it makes outputs more coherent but it never causes any saturation artifacting unlike CFG above 2 with these models
@atdc You need to read how PAG works, then. or you just didn't understood me. PAG doesn't increase CFG, it replaces it, and it can also work together with it like in addition.
It's specifically recommended to have lower CFG for PAG because its value and value of CFG are combined in one total guidance, which isn't the same as CFG. You can set CFG to 0 and then just set PAG to 5 or something, that would work too (not recommended to do so).
Since you're using ComfyUI, you can see it for yourself in the code even. Open custom node for perturbed attention, pag_nodes file, it has post_cfg_function with the next comments:
"""CFG+PAG"""
And after some code there is # Replace Self-attention with PAG comment and code for how it works.
I was going to comment somehow PAG works for the DPM++2s Ancestral CFG++ but yeah never mind still doesn't work for reforge
great model
0.75 seems to have resolved most of the issues which stopped me from updating from 0.6 to 0.65. The background noise is mostly gone and the colors are dialed in. Good job!
well, the actual 0.65 (non-s) that you could find on huggingface was just a direct upgrade of 0.6 more or less. but this one is like much more improved for sure.
@fizalpher I have been using the non-S versions, as I prefer to tweak the model myself. Base 0.65 also suffered from severe noise issues which made me skip out on it. I believe this was due to the addition of a good amount of data which the model did not have enough time to generalize.
Is there going to be a guide on v-pred about how to use it in forge and reforge? so far I have only seen guides on comfyui and not the others.
you can use it in forge like any other model
@ShencilLizard I have tried forge and reforge, both didn't give me good outputs compared to the preview images.
@AkioAI share your prompt, I'll upload one of my images now
Hi, you may refer to this: https://d0xb9r3fg5h.feishu.cn/docx/YpOQdtHTDoetcZxIO9fc33onnee?from=from_copylink
@Euge_ I think I have figured out the reason why it was giving me really bad images. Thanks for trying to help but I solved the issue. The reason was because I did a fresh install of reforge (the branch dev2) so the settings weren't set correctly to give me better results.
@AkioAI What settings did you change though?
@Xeno443 I recommend using forge, the outputs look way better. The two settings I changed was "ENSD: 0" to "31337" and enable "Always discard next-to-last sigma"
I much prefer 0.75 vPred over Epsilon 1.1 already
I can't wait to see the end result of vPred if it's already this good, thank you. (no pressure!)
i agree with you
Has anyone successfully trained a lora for noobai v-pred versions? I've tried the settings mentioned in the description in kohya-ss, but it isn't working for me. I might be messing up some other setting. If anyone has a json config, please share.
You might have to specify your problem. Overfit, underfit, NaN?
I'm currently training some LoRAs for Illustrious using the recommended settings on Civitai. At the moment they work even better on Epsilon-pred v1.0 and v1.1 than on Illustrious itself. My training params:
{ "unetLR": 0.0005, "clipSkip": 2, "keepTokens": 1, "networkDim": 32, "numRepeats": 7, "resolution": 1024, "lrScheduler": "cosine_with_restarts", "minSnrGamma": 5, "noiseOffset": 0.1, "targetSteps": 945, "enableBucket": true, "networkAlpha": 16, "optimizerType": "Adafactor", "textEncoderLR": 0.00005, "maxTrainEpochs": 12, "shuffleCaption": true, "trainBatchSize": 4, "flipAugmentation": true, "lrSchedulerNumCycles": 3 }@klikkeri1 Hello, I tried a lot of different configurations. First few were giving NaN, but even the one that completed didn't work properly and gave very noisy outputs when used in a v-pred workflow in NoobAI works. It's hard for me to pinpoint the problem, that's why I straight-up asked for a sample config.
@klikkeri1 and @TonyVan I'm sorry, I missed mentioning that I'm talking about the v-pred versions. I've edited my original comment to reflect that now.
@nymical Got it, hope you figure it out.
https://civitai.com/models/833294?dialog=commentThread&commentId=612391
all other settings same as normal models
ive trained some models with these params and got pretty good results
apparently you should also disable all noise related arguments (noise offset, min snr gamma, multires_noise_discount)
@Hugs288 Thank you! I'll look into it.
Please oppen no half vae.
hmm thats weird I can never get Euler sampling method to work even though it is the recommended sampler , but when I set it to Euler Ancestral..it works just fine...
Wonder if I did anything wrong? anyone mind telling me? I use Reforge by the way.
With Euler I try to use low CFG, but it depends on the results, it has worked well with 10, but with some artist it's better to use 5, it's a trial or error.
Hi, you may use Euler Ancestor with CFG=3~5
@Euge_ I use CFG at 4 though :\
it could be a bad install, I think I might want to reinstall Reforge
@Ainokura I'm on comfyui and Euler A 3.5-6 seems to work better for me too
With certain prompts, the images will always turn out with a heavy dark blue hue, you can even see from a few example images posted below.
Does anyone have a fix for this, other than keep changing the prompts?
Lower the CFG or try using Euler A or a CFG++ model.
Can someone tell me difference between epsilon 0.75, epsilon 1.1 and v0.75? why is only epsilon 0.75 illustrious and rest all sdxl?
I think it's mainly Civit-related SEO optimization, they're all based on Illustrious v0.1
@Machi Im sorry I didnt get the first part but its written SDXL as base model
请问我在使用v-pred-0.75s出图时,出现
NansException: A tensor with NaNs was produced in Unet. This could be either because there's not enough precision to represent the picture, or because your video card does not support half type. Try setting the "Upcast cross attention layer to float32" option in Settings > Stable Diffusion or using the --no-half commandline argument to fix this. Use --disable-nan-check commandline argument to disable this check.
的报错应该如何解决,是否与硬盘空间不足有关?
I finally figured out why it kept giving me bad images.
V-pred 0.75S has way better lighting and colors compared to NoobAi 1.1 Epsilon. Give it a try, you may need to figure out the best settings but once you do, you'll get pretty good images.
But you didn't mention what you actually did to fix it, tohelp others suffering from the same problem
I recommend using forge, the outputs look way better. The two settings I changed was "ENSD: 0" to "31337" and enable "Always discard next-to-last sigma" (copy & pasted from a different reply). For some reason for me at least, reforge wasn't producing not so great images compared to forge.
@Xeno443 Hi, for your reference: https://d0xb9r3fg5h.feishu.cn/docx/YpOQdtHTDoetcZxIO9fc33onnee?from=from_copylink
@Euge_ Thanks! Just getting info from some others that it seems to not work properly with reForge right now, while its fine with original Forge
Does this model works for training? Which version should I use?
Why not? These models work for LoRA training, You can use Epsilon-pred v1.0 or v1.1
Do someone of you could please share with me a comfyui example with loras for the v-pred?
Here's a simple example with only native nodes: https://imgur.com/a/r55otKR. However, using custom nodes with lora stackers is much easier, such as Efficiency Nodes or Comfyroll Studio.
@Lost_Meteor shouldnt u use a node that turns v-prediction or something?
@Haiigdso3 He should
@Haiigdso3 The current version of comfyui handles this automatically iirc. And I've already generated a lot of images on top of this set up with absolutely zero problems.
@Lost_Meteor thank u, good to know!
Nice work
nice
I am not sure if it is my prompt but when I prompt for an artist, sometimes it does not look anything like the artist (even the ones with over 100 images on danbooru and this is on v-pred, the latest one)
Is there a possible fix for this or do I have to wait for the next version to come out?
Hi, for the usage of artist tags, you may refer to this: https://d0xb9r3fg5h.feishu.cn/docx/YpOQdtHTDoetcZxIO9fc33onnee?from=from_copylink
@Euge_ 有中文版链接吗(
@Euge_ 谢谢!
You need to keep in mind a lot of artists have different art styles, and their art has evolved during time. And the model is trained in all their art available in Danbooru. So, keep that in mind, so unless the artist has had a really stable style for tens of pictures, you will get a good stable style, if not, expect some variation.
Also try to play with CFG, some artist work well with low CFG others with higher, same with their multiplier, try to loser it to 0.8 or so, testing is your best choice.
Even with the discrete sampling node for v-pred, my images for v-pred 0.75s come out much worse in comfyui than the on-site generator. Tried slightly lower CFG too and still no luck. Some images are passable but overall, they're way less consistent
im having this issue too, did you find a solution?
@karina5057 Nope! I messed around with 0.9R and my results suck. I'm getting very "incomplete" looking eyes, bad hands, etc.Tried low CFG, high CFG, Allign Your Steps, no Allign steps, Clip Skip 2, no Clip Skip...
Then I try Illustrious models and my results are ultra beautiful again.
Is there any Tile and Color controlnet for this model? I couldn't find one.
can i use illustrious loras in the new version?
yeah you can, some preform even better on noob ai, I recommend using eps prediction versions.
Stick to eps, quality seem to degrade on v-pred. Imo loras trained specifically on this checkpoint as base produce better results. But dont forget that you can use artist tags here.
Any tips for SD.next users to run illustrious?
Just simply doesn't seem to work and I have no clue why.
Woooooow
Did a guide for EPS1.1 on Forge with extensions parameters.
https://civitai.com/articles/9740
It also has inpainting tips.
Writing an article on it now, may wait at this point until a new V-Pred model is out to ensure nothing changes, but have some advice to generate better results.
Being a V-Pred model, the most minute cfg change can have a pretty profound impact. We’re talking changing cfg in 0.1 increments. So far the best results I’ve gotten for prompt adherence is by doing the following:
Alternate e621 and DanBooru tags. If you look at my recent images, I have posts utilizing different prompts. They’re the same prompts in actuality, they just use different tags as e621 and danbooru have separate tags that describe the same thing. Through experimenting, this model seems to work best when operating on an exclusively danbooru or e621 prompting dataset. I believe this is due to the weighting of e621 vs danbooru, or, a discrepancy in size between the e621 dataset and danbooru dataset. Using both in the negatives doesn’t seem to have the same impact however. Prompt adherence generally stays consistent if both are filtered out. Though, if you were to use a tag that filters out a huge amount of e621 images such as “mammal,” that could change.
However, there’s a way around this. It is by using alternating tags like so: [x|y]. I recommend using e621 tags first as it seems less heavily weighted than DanBooru. So, an example of one tag would be: [female|1girl]. Again, look at my latest images for a better full example.
That’s one piece to the puzzle. The other harder piece is which sampler/scheduler to use. That is something I’m still writing on, but I think most people are using schedulers that do not work as well with a V-Pred model. I don’t recommend using “automatic” or “normal” as most people do. Instead, Align Your Steps and Beta schedulers seem to work much much better. You can see this for example in Flux which also utilizes V-Prediction.
More to come soon, will do a whole write up eventually. I will likely release it though once the new version is out to be sure there are no major changes with the next update. As of the time writing this, V-Pred 0.75s is the newest model.
I hope this could be useful to some out there!
EDIT: Since the full version is coming soon and 0.9R is essentially a test model, I'll wait for the full version to release my findings! I think I have some pretty worthwhile info to share on getting consistent results, stay posted!
yeah, AYS and beta were the only schedulers that produced great results in my setup. The others output watery or noisy images, which seems to be a convergence issue.
@alter2611 Oh really? That’s interesting, personally I didn’t seem to notice noisy images, but I did notice more distorted subjects and worse prompt adherence for sure.
Euler SMEA DY CFG++ has been the best at adherence thus far from my testing. Beta and AYS still seem to have best results. I also recommend a large resolution as I’ve noticed this model can struggle fitting multiple subjects in a “normal” SDXL resolution. For example, 1792 x 1024 yields much better adherence for 7:4 aspect ratio than 1344 x 768. Because it’s v-pred, I was surprised but it seems like there are minimal if any artifacts from using a higher resolution.
While someone is developing a LCM/Turbo/Lightning Lora for this model, you can use ChromaXL Mix.
For LoRAs Epsilon 1.1 is still better.
I tried many settings for v-pred loras (except v-param and zero term snr) but it seems that v-pred is worse in details and it is brighter even on lower cfg (3-4).
V-pred is ok as "pure" checkpoint - it is smarter and listen your prompt better but LoRAs are worse - for styles, for characters. I did many comparisons.
The developers should make a guide for v-pred lora training so that everyone understands how to change the settings of their training (besides v-params and zero term snr).
ive trained several loras on v-pred snr and they all work perfectly fine, youre probably doing something wrong.
@Hugs288 what parameters did you use? I used the same as on epsilon except v-param and zero term snr. I even lowered my lr and enabled min snr gamma 5 (without this setting lora is totally garbage).
Has anyone managed to make this work on Draw Things? The results are green and yellow noise regardless of the prompts and settings. On the iPad (m1, 16gbram) I can’t think of anything that would make it work…
it works on my iphone. When importing the model, select v-prediction. Attention with Higher Precision remains off.
Why is no one talking about how ridiculous the license for this checkpoint is?
Not only is it poorly communicated, but it places huge limits on what people are able to do with the checkpoint. What's worse, it seems like currently there are many fine-tunes based on noob that are not correctly passing down this license which is sure to cause confusion.
As an example: the license requires that prompts MUST be shared. I don't have a problem sharing prompts at all but you've created a situation where anyone who posts a picture generated from this model ANYWHERE without the prompt included is seemingly in violation. That's just the tip of the iceberg with this.
Why impose these things? There is no way you are going to be able to enforce them and it creates unnecessary confusion because it goes against established community precedents. If I wasn't giving L_A_X the benefit of the doubt I'd expect it was an attempt to entrap the community.
Edit: Some clarifications.
Part of the problem and why I say it's "poorly communicated" is because NoobAI-XL appears to be licensed under two licenses. There's the license linked under "license" here on this page, and there's also the license terms provided in the description of the checkpoint. The terms described between them are different.
The license(s) put restrictions on how generated outputs are used outside of the norm:
From https://civitai.com/models/license/1116447
"Image Sales: Do not sell or license images generated by the Model. The following are a few examples of what is prohibited: selling or licensing a product such as a game, book, or other work that incorporates or is based on those generated images."
The license(s) makes prompt sharing a requirement:
From the description on this page [ https://civitai.com/models/833294?modelVersionId=1116447 ]
"III. Open Source Community
To foster a thriving open-source community,users MUST comply with the following requirements:
Open source derivative models, merged models, LoRAs, and products based on the above models.
Share work details such as synthesis formulas, prompts, and workflows.
Follow the fair-ai-public-license to ensure derivative works remain open source"
Again,
"...users MUST comply with the following requirements... ...Share work details such as synthesis formulas prompts, and workflows". User's MUST comply with the requirement: share prompts and workflows. It's unclear what this even means. Are users required to share all prompts they use with NoobAI-XL or just of the images they post online? What does compliance even look like?? It's not clear.
Where the hell did you find it? https://civitai.com/models/license/1116447 It bans sale of checkpoint and merges.
@Volnovik It's more than that. Part of the problem and why I say it's "poorly communicated" is because NoobAI-XL appears to be licensed under two licenses. There's the license you linked, and there's also the license terms provided in the description of the checkpoint. The terms described between them are different.
The license(s) put restrictions on how generated outputs are used outside of the norm:
From https://civitai.com/models/license/1116447
"Image Sales: Do not sell or license images generated by the Model. The following are a few examples of what is prohibited: selling or licensing a product such as a game, book, or other work that incorporates or is based on those generated images."
The license(s) makes prompt sharing a requirement:
From the description on this page [ https://civitai.com/models/833294?modelVersionId=1116447 ]
"III. Open Source Community
To foster a thriving open-source community,users MUST comply with the following requirements:
Open source derivative models, merged models, LoRAs, and products based on the above models.
Share work details such as synthesis formulas, prompts, and workflows.
Follow the fair-ai-public-license to ensure derivative works remain open source"
Again,
"...users MUST comply with the following requirements... ...Share work details such as synthesis formulas prompts, and workflows". User's MUST comply with the requirement: share prompts and workflows. It's unclear what this even means. Are users required to share all prompts they use with NoobAI-XL or just of the images they post online? What does compliance even look like?? It's not clear.
I honestly don't see how it'd be enforceable
The license is kind of invalidated because this is spun off from the Illustrious base model which states that everything allowed in that license must be allowed in any adopted license, thus it's more optimal to just not adopt a new license since it'd basically have to be the same thing. So no need to worry about being in violation of anything. Freedom of Development
Boycott Noobai until they stop with their foolishness.
Also you misinterpret the prompt sharing part. That's only for derivative models/merges/etc, you must share how you made the model and any accompanying details like pictures you provide alongside the model must have those details disclosed. Otherwise, as per BOTH licenses, outputs are pretty much unaffected by both licenses.
"Output
The output of this software is not covered by this license, and no contributor claims any rights to it."
This is the only website where their license was updated its still "fair-ai-public-license-1.0-sd" everywhere else, I noticed it a while ago and brought it to Jomcey's attention.
Everyone thinks its kind of weird considering their whole thing was about this model being an open sourced public service basically, so if I had to assume one of their team members likely went rogue and changed it without telling anybody. But we won't know for a few days.
But if you want to use the model to merge or whatever else just grab it off of hugging face
https://huggingface.co/Laxhar/
Information about it will likely be clarified in a few days.
@fizalpher I'm not sure that I am, and even if that's so, that supports my claim that the license is not clear. If I'm wrong, then the license should be more explicit so that there isn't room for misinterpretation. I think that's a reasonable ask.
The addendum part of the linked license (the OpenRail addendum) does put a limitation on outputs as laid out in my original post, so it's at odds with the Illustrious-XL license part you're quoting.
I need help, I tried every setting that supposedly works for this model but I still get fried images, not a single pattern that I can recognise, just noise.
It is not something that happens in the end, but it is constantly pure noise all the generation.
I must be missing something, some setting or whatever.
I am using A1111, SDXL Vae, Clip skip 2, CFG scale of 4.5, size of 832x1216, sampling method Euler, no LoRAs, a very simple prompt and nothing works.
Eps or v-pred?
https://civitai.com/articles/9740
@Volnovik vpred
@Nomad334 A1111 need test branch, main branch not support v-pred model
No clip skip. Use comfyui... a1111 never updates on time. Set ZTSNR on, euler ancestral beta cfg 4.2 works fine. (or euler ancestral cfg++ cfg 1-1.8 for better colors/etc)
skill issue
@Pxrpose Literally why he's asking for help, dog brain.
@hcommand68990 why so mad
@NTR_BLACK Thank you, I was very lost
@Pxrpose yes thats why I need help, I'm a casual
Anyone know if you can use illustrious-categorized loras with this in civitai generator? If not they should set this model’s category to illustrious (or civitai should just get rid of that unnecessary restriction)
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