Verified: 3 months ago
SafeTensor
Type | |
Stats | 2,529 2,512 1.6k |
Reviews | (243) |
Published | Jun 10, 2025 |
Base Model | |
Usage Tips | Clip Skip: 2 |
Hash | AutoV2 785B4B6DD8 |
5.7k
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License:
Images hidden due to mature content settings
Introduction
For version 1.0:
This model is based on 'Illustrious XL 1.0' with some minor modifications and was trained on the Danbooru2023 along with the dataset I previously used for training my LoRA models.
For version 2.0:
This developed model is intended to allow everyone to experience the v-pred version of Illustrious XL, instead of having to spend a large amount of STARDUST to unlock the Illustrious XL v3.0 v-pred and v3.5 v-pred versions.
I independently researched and developed this version based on various existing XL model architectures. However, due to the many modifications I made, I’m not sure it can still be considered 'Illustrious XL'.
The model was trained on the danbooru2024, danbooru_newest-all datasets, as well as a custom dataset (which I collected and labeled using natural language with GPT-4.5, and later manually verified by me).
I put a lot of time and effort into developing this version, so if you don't mind, please consider bidding on it so that others can use it through the CivitAI generator. Thank you all very much!
For version 3.0:
With this version, the model was created with the purpose of adapting to as many styles as possible, while also balancing detail stability in the generated images. This model includes styles and artist styles (from Danbooru and e621).
Although it is oriented towards being a pre-trained model, you can use it normally. However, to achieve optimization, I suggest you combine it with LoRA or fine-tune it to create the style you desire.
The model was trained on the danbooru2024, danbooru_newest-all datasets, e621 as well as a custom dataset, with 40% of this data annotated using both tags and natural language.
This model is an epsilon-prediction model that can easy to use.
For version 3.1:
This version improves the issues encountered in version 3.0. In addition, it also enhances image quality related to styles and artist styles (from Danbooru and e621).
This model was trained on the same dataset as version 3.0, but I re-annotated it, added many new anime characters, and improved the quality of existing ones.
The model improves stability when generating images at a resolution of 1536x1536.
This version will have two variants: one for v-pred and one for e-pred (the e-pred version will be released first).
For version 3.2:
This model is a refined version of 3.1, incorporating hotfixes and enhancements. It features improved detailing in the eyes and more accurate anatomical proportions for the character.
Additionally, the model demonstrates enhanced creativity and a better ability to accurately understand prompts
This model is also capable of generating images at large resolutions, e.g., 1024x2048 (I tested it and found the image quality to be quite decent). (Note: during training, I only trained it with images at a resolution of 1536x1536).
For version 3.5:
This model was trained on the Danbooru dataset, updated as of May 9th, 2025, with image sizes of 1536x1536.
It fixes an important bug that appeared in version 2.0 of the v-pred variant.
The model also improves stable style, anatomy, and prompt understanding compared to the previous version.
Important Note
This is the first base model I've created, so any feedback is welcome. Feel free to share your thoughts so I can improve it in future versions.
Version 2.0 is a V-prediction model (unlike epsilon-prediction), and it requires a number of specific parameters.
Version 3.0 should be set with a low CFG value, around 2 to 4. When you encounter images generated with high contrast (I don't know why CFG affect this, i will investigate and find the solution :v)
Currently, the model is not available for use via Civitai Generation. You can visit the following website to use it:
Suggested settings:
All example images were generated using the following settings:
Positive prompt: masterpiece,best quality,amazing quality
Negative prompt: bad quality,worst quality,worst detail,sketch,censor, simple background,transparent background
CFG: 5-7 (For version 3.0 i suggest you should set this lower from 2-4 )
Clip skip: 2
Step: 20-30
Sampler: Euler a/DPM++ 2S a
Note: I don't use any post-processing and Lora to enhance the example images. I only use these settings and a custom prompt with my base model to generate.
Acknowledgments
Thanks to narugo1992 and Nyanko for sharing such valuable data.
If you'd like to support my work, you can do so through Ko-fi!
Suggested Resources
Checkpoint
NAI
Checkpoint
NAI
Discussion
@duongve13112002 You are blocking comments calling you out, you're a liar and your text is generated with an LLM as poor as your ability to lie. You're a liar and you're stealing others work and calling it yours. I hope you get reported, because I surely did.
I have no intention of defending anyone's stance in this dispute between @Minthybasis and @duongve13112002 . According to @Minthybasis , this model can generate chibi-style images similar to their own model. However, @duongve13112002 has shared the workflow used to create this model, and from their explanation, it seems evident that knowledge from the Rouwei model is inherently present in this one. That said, in order to objectively determine whether this model is truly different from Rouwei, we need to make a direct visual comparison.
I’ve been testing both models since this morning and found that, for many prompts, the two produce noticeably different outputs. Occasionally, the generated images may look similar at first glance, but the details within them differ significantly. I’ve uploaded comparison images, all generated using the same settings, with the only variation being the two different base models. You can view them here: https://civitai.com/posts/18275913. It's clear that the two models do not consistently produce identical images, and at times, the differences are quite pronounced.
i love testing models ... but sry what in the hell is this 3.5 version ? pls explain that some images turns in to a horror genre @_@
It looks like author did training over different models (including unknown version of rouwei). And then merged different models he trained and some extra models. Names of merged models in metadata indicate training of rouwei model (2 models in 2 different directions).
If model can generate content of watermark-tag and have different style - it's most likely training. His v3.2 model contains less than 55% power of "tuned" rouwei models. If they were merges there is a very small chance watermark can actually survive, so most likely they are real trained models, but over rouwei. Not Illustrious 1.0.
There are merge recipes for the IllumiYume XL series.
v3.2 v-pred
https://civitai.com/images/83184782
v3.1 v-pred
https://civitai.com/images/83186295
v3.1 e-pred
https://civitai.com/images/83187293
v3.0
https://civitai.com/images/83187844
v2.0
https://civitai.com/images/83188267
v1.0 metadata
https://files.catbox.moe/j7qp2g.json
You can view them by dropping the model file into ComfyUI with comfy-mecha installed.
In v3.5 there was no metadata at all. It may have been lost in the process of adding the v_pred and ztsnr keys.
The v1.0 metadata does not contain anything about comfy-mecha, but does contain information about other merge tools, such as "webui", "sd-webui-supermerger", "sd-webui-model-mixer" and "merge-models-chattiori".
Among the merged models, there may be a model that you trained yourself, but I would publish these models as "CHECKPOINT MERGE" rather than "CHECKPOINT TRAINED".
It cannot possibly be a fine-tune of Rouwei 0.8 vpred for one simple reason:
Rouwei v0.8.0 (epsilon):
"createdAt": "2025-05-25T17:56:29.844Z"
Rouwei v0.8.0 (v-pred):
"createdAt": "2025-06-08T23:32:42.554Z"
IllumiYume XL v3.5 (v-pred):
"createdAt": "2025-06-10T07:32:34.084Z"
It's simply not feasible to produce a fine-tune just one day after the base model's release. You'd need significantly more time just to study the nuances of the original model.
And let's not forget: Rouwei 0.8 epsilon itself was released just two weeks before IllumiYume XL v3.5 v-pred. That's barely enough time to analyze the base, develop a training setup, adapt this custom distillation mechanisms to this specific checkpoint, debug it, run a full training cycle, and validate the output, which makes the claim of a personal fine-tune even more dubious.
What we're looking at here is clearly a merge of Rouwei 0.8 with some quality-enhancing LoRAs, may be with weights from other checkpoints, what caused loss of full vpred range from original. May be small finetuning that can be done in short time between the release of models. And there's absolutely nothing wrong with that - after all, the majority of models on Civitai are exactly that. Just like many users preferred AutismMix over using PonyDiffusion v6, even though most of the original work was done by Astralite in his Pony model.
The real issue lies elsewhere: duongve13112002 deliberately misled the community by claiming this was his own personal fine-tune. Even after being caught, he tried to deflect, dodging direct questions and hiding behind technical jargon to appear more credible.
If this really were a distilled model, then I'd love to hear a credible explanation for how watermark patterns - previously unknown and never publicly disclosed - ended up in his version.
And to top it all off, he has the audacity to keep asking for money for future "training" work.
The sheer nerve is astounding!
When people like this start asking for donations, it becomes clear: this isn't just dishonesty - it's fraud. Had he been upfront with his audience, there wouldn’t have been any controversy.
There are two types of checkpoints on this site, ‘trained’ and ‘merged’, and I don't think anyone would be too hard on a merged model.
Labelling a model as merged conveys the attitude that my model's knowledge is largely derived from others (whether by complex or simple means), and I'm willing to admit it.
The trained model conveys a different message: more or less, a significant portion of the knowledge in that model is derived from my efforts as an author. (Whether that knowledge is added or optimised)
v3.1/3.2 is pretty good work, but it couldn't have been done without Illustrious 1.0 behind it, and even though Illustrious itself was starting to turn into a farce, Illustrious 1.0 did improve in high resolution, and they did at least release 2.0 according to the donation schedule, and to be honest, I'm not excited about Illustrious v3.5 was no longer expecting much, oh - and what a coincidence, the same farce provoking and disappointing v3.5.
The base model info for IllumiYumev 3.5 shows Illustrious , but if you dig deeper, what model is the base of it's fine tuning? I don't think it's Illustrious 1.0 ,
Would it be Illustrious 0.1 ? I don't think so.
Based on the results we got from our testing, we can actually declare that the base model for v3.5 is RouWei0.8 because it improves on RouWei0.8 - we should declare that it's based on RouWei0.8, which is based on Illustrious 0.1.
If you want to say that. Please make it clearer.
To your response, I'd like to make it a little more prominent in the comments - @oioioicola
That said, if it were actually based on Illustrious 2.0, then instead there wouldn't be any problems. After all, v3.5 does improve on its fine-tuned base, and who wouldn't be happy to see a better model?
(Translated with DeepL)
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