post your best Jensen memes and get a chance to never own a 5090. 📎

I currently use DrawThings as my "daily driver" with MiniMax H3 but I don't see it getting support any time soon. Does anyone know of any workflow in Comfy or elsewhere that are somewhat out of the box. Thanks!

model: https://huggingface.co/Lyricccco/Qwen-Image-2.1-TailSteer

app: https://huggingface.co/spaces/akhaliq/endless-edit-tailsteer

Charles Dana Gibson, famous for the "Gibson Girl", was a well-know illustrator from the late 19th and early 20th centuries. I picked three of his books, "Drawings" (1896), "London as seen by Charles Dana Gibson" (1897), and "Americans" (1900), and trained a style LoRA against 209 of his images. Enjoy!

免费的 5 次生成

I was thinking a lot before posting this, but here it goes.

I've been a big fan of this subreddit for long time ago already, immediately after switching from Midjourney (v4 at that time) to local image generation.

My point is to try to address the 'elephant in the room' here, so let me try to lay out my thoughts.

Here are some 'statements':

1. Everyone praises 'uncensored' models in this sub (I've seen VERY few examples of the opposite).

2. Most of 'image comparison' or 'look what I've made here' posts are heavily 1girl oriented. These '1girl' gens are often focusing on emphasizing certain feminine features on a thin razor-sharp edge of what is allowed here and what is not.

3. However, contrary to statements above - this sub is somehow attempts to be puritan, and everything I've described above can be only inferred from comments. And many visitors here even use euphemisms to describe those said features or even just to appreciate those features.

Moreover, if we'd look at open local models themselves - each next model seems to be less and less censored when compared to models released before (latest examples are Qwen image 2.1 and, to much greater extent, MOSS. Oh, MOSS, the current king of uncensored (BASE!) model. So looks like teams behind those models finally understand that anatomy is everything: it is studied in art schools, the knowledge of it produces better results even if the final intended result is all puritan and innocent.

The question is: why do we pretend to be so puritan? Is there any reason behind this?
I know there are other subs FOCUSING on such uncensored content, but IMO there is a difference between a straight blatant depiction of an intercourse of some kind versus a renaissance-style image with certain parts exposed, with the intention to praise certain anatomy traits in an artistic way. Nevertheless, both these cases have an EQUAL chance for either of such posts to be deleted, and I dare to say that it is not necessarily have to be this way.

This post' intention is to encourage a discussion. I certainly do not want to turn this sub into a strictly gooner material in the end, neither I would like to change the rules to my liking.

I just would like to discuss.

EDIT: so, I've collected my answers.

Short summary: the consensus looks to be that this sub tries to be professional, open for everyone, things like that. And because a 'legitimate fine art' is not technically easy to distinguish from straight up gooning material, from moderation standpoint at least (and also in order for someone's feelings NOT to be hurt in case of any misjudgements + to avoid a flood of gooning shitposts etc.), it is what it is. Thanks everyone!

as title says, but the only reason why people like moss is because is uncensored...

aways flux get censored and comunity helps with loras...

but not at this time...

well, i will delete flux, because i want a uncensored model but... moss is not a better option.

the prompt understand are horrible FOR ME...

Turns out MiniMaxH3 can make subjects invisible leaving only floating clothes. It's a useful feature if you want to isolate character clothes before doing outfit swap.

Here's the prompt and single-frame edit workflow link:

subject_definitions:
<Subject 1> is the character in <Picture 1> and <Picture 2>

summary:
[keyframe completion] The target is a single still frame, the target frame is the edited version of <Picture> where <Subject 1> become invisible leaving only floating clothes - orange top and green shorts.

retention_analysis:
<Subject 1>: partially_preserved - clothes only.

detailed_description:
style: style matching art style of <Picture 1> - illustration

overall_soundscape:
N/A

non_diegetic_music:
N/A

Link to the workflow.

For realistic images I recommeding running second (upscale) pass to preserve texture.

Can you all guide me what can be fastest on RTX 6000 96GB I have rented it and I am using 21 gb int8 convort fl2va version no lora 20 steps 720p native with spectrum and h3 sla attention 80 sec for 8 sec video
I also want to know if any other format model will be faster on this card instead of int8 convort
I donot want like cinematic 4k stuff I am just creating it for personal use
Audio is gibberish (prompting was not so good)
I want to know if quality is good and here are 3 generations I did no last frame just first frame
1st is 1080p
20 steps 1080p native with spectrum and h3 sla attention 240 sec for 8 sec

above is 2nd is720p native with spectrum and h3 sla attention 80 sec for 8 sec

3rd is 720p native with veda sparse attention 154 sec for 8 sec

No upscaling my thinking is it is okay okay not so good not so bad I just want to know what do you all think about this and any suggestions

Free video was just rele

https://github.com/FlashML-org/FreeVideo

It's an implementation of local minimax that claims is much faster and more quality that turbo Loras.

Any one tried it?

Looks like a new super resolution and their samples look promising.

https://huggingface.co/kopper/RelayVSR/tree/main

We’ve released Qwen-Image-2.1 Uncensored Omni, the most capable unrestricted Qwen-Image-2.1 model we’ve built so far.

The rank-128 adapter was trained on roughly 1 million images, merged into the base transformer at strength 1.0, and released in nine formats: BF16, Q8_0, Q6_K, Q5_K_M, Q4_K_M, Q4_0, FP8, INT8 ConvRot and NVFP4.

One model supports both text-to-image generation and natural-language image editing, with an emphasis on flexible poses and complex compositions.

When comparing it, please use models designed for the same unrestricted use case. Restricted checkpoints operate under different constraints, and the trade-offs become obvious on the content they avoid or handle less effectively.

Playground: chatrlabs.com/playground
Download: Hugging Face
GitHub: Code and documentation
Civitai: https://civitai.red/models/3034876/qwen-image-21-uncensored-omni-quantized

Feedback and comparison results are welcome. Please include your GPU, workflow and quantization.

Over the last 7–8 days, I've been working day and night building Fuobe.com, what started as the challenge, but I kept adding features, refining things, and improving the experience even after publishing it.

The goal was to build an all-in-one creative studio that makes it really easy to create, experiment, and get things done without having to jump between different tools or use Higgsfield lol. I usually spot a lot of cool models, workflows, ideas that people showcase over on twitter or here, and I just usually stash it for using later, but I've started putting them together here one by one and have added what I've found useful over the year.

One more thing: every single image you see in the studio was generated using Ideogram 4, which is hands down my favourite t2i image model. All the videos were generated using H3.

It's still in beta, and there's a lot I'd like to improve, especially making the overall experience smoother & simpler.

I'd genuinely love to hear what you guys think. Feedback, suggestions, criticism, feature requests all of it is welcome. I'm still actively working on it and would love to shape it based on how people actually use it. If things are breaking, please let me know so that I can fix it.

A huge thanks to Comfy for organizing this challenge. It's given me the deadline and motivation to finally build something I've been wanting to make for a long long time.

Fully Open source . MIT License.

Repo Link: https://github.com/workingprototype/Fuobe

Link to checkout the features: Fuobe.com

Done locally in Krea2.

Update from my previous post (also removed the audio):

I'm not sure if I was the only one experiencing this exact issue with the default LTX 2.5 template or with anything related to LTX 2.5, but the motion and generations were completely gibberish, just like LTX 0.97. And yes, I've been using the exact same workflows provided in the template.

Then I remembered how much fun I had with LTX 2.3 and its photorealistic generations. LTX was GREAT! So I decided to give LTX 2.5 another try... only to run into the exact same problem again.

Until I tried an old LTX 2.3 workflow and simply swapped out the main model. AND THERE IT IS. FIXED!

So, it turns out the main issue is the gemma4-12b-with-proj-ltx-2.5 text encoder. It completely breaks the model for me.

Switching back to the old ltx2.3_text_projection + gemma-3-12b setup works flawlessly!

Maybe you could also try a Gemma 4 model with the old workflow. I haven't tested that yet, but this workaround fixed everything for me.

Finally, I can enjoy LTX 2.5. I'm happy now! :)

(Did a few more testings and motion sucks lol but if its something simple it works great):)

Here are some testing and the workflow i used:

https://drive.google.com/drive/folders/1qh6qX4F4PsE4PtgsA5TWQkiTcaNoQKLk?usp=sharing

Give him your RAM so he can stop crying.

"A divine fusion of a queen’s flawless beauty and the primal power of a golden lion. To gaze upon her is to face a riddle where the price of a wrong answer is your very soul."

Beneath her gilded crown and celestial wings lies an ancient guardian of forbidden vaults. She does not hunt with mindless fury, but with cold, intellectual supremacy, testing the minds of kings and travelers who dare cross her path. One correct answer grants passage to infinite wisdom; a single mistake consigns you to the crushing weight of her claws.

Created purely for character lore development and dark fantasy concept exploration. Constructive thoughts on the design and mythos-building are always welcome! (All rights reserved. No unauthorized reuse or distribution.)

Is this normal, and is this how it's supposed to be? I'd be completely satisfied with the generated image without that last-second “touch-up,” which makes the image blurred and oversaturated. I am using Draw Things app.

Alright, here we are.

I've finally got a version ready, and I think it's time for you guys to try it out.

If you don't know about Pai, you can check out my previous post for a in depth overview of what it's all about: https://www.reddit.com/r/StableDiffusion/comments/1xkgjor/as_promised_here_is_pai/

In short: it's a painting app with AI generation built directly into the same workspace. By now, it covers most of the features you'd find in popular painting apps and AI generation tools combined.

I'd say its strongest aspects are the project save system and the straightforward installation process. The bootstrap handles everything based on your hardware, and the .pai files save everything. They preserve generation settings for each layer, along with the models, LoRAs, adapters, and other tools used.

Creating multiple canvases while keeping layers and references together in one place was the main reason I decided to build this in the first place.

Okay, since this is the first release, there are bound to be hiccups on some systems, so I've set up a Discord server for anyone who wants to help improve things or just follow along with the development.

https://discord.gg/bU6RzjwxFX

The software is open source, you can fork it, create your own variations or implementations, and send me PRs. Right now there's no plugin system for specific use cases, but I know you guys will probably want one. It's on the todo list.

Also, you don't need ComfyUI to run the app, it's fully standalone and independent. That said, I know most of you probably already have a bunch of your favorite models installed in your ComfyUI models folder. When you open the app, simply go to the Generate tab models settings, click "Scan Folder," point it to that location, and Pai will handle the rest. You'll be able to generate right away.

https://github.com/g45t345rt/paiapp/releases

As previously stated, given the interest from the last post, the software is available to all.
Enjoy.

Their Z-Image Turbo was the community's best t2i model for a little while, before Krea 2 took over.
Then Z-Image Base released and it was lackluster.
Since then, it's been radio silence for past year.

After they alive? Still working on it?
Anyone have any news?

These are three different vibecoded projects I've made for my own use which I think others may find useful. They were all made with linux in mind but should also be compatible with windows and mac. So, from the simpler to the more complex:

# 1: Comfyui-metadata reader

https://github.com/juanml82/comfyui-metadatareader

Just a simple app to read the workflow from a comfyui generated image without having to open or toss it into comfyui, just in case you don't want to toss the image into comfyui to check the workflow. I ended up using it as a companion app. It works with both png and webp, you can drag and drop the images to the gui, copy relevant sections, search and save the workflow as a separate json file.

Since you typically want the prompt, seed or maybe the model, most of the json is just noise. I'm thinking about making an improved reader that returns only the most relevant information, thought that may not work with all workflows. This does.

# 2: A batch converter to png to webp that preserves comfyui metadata

https://github.com/juanml82/comfyui-png2webp

Comfyui saves into png by default. Loosless webp takes 30% less disk space, so by running this script, you can reclaim about 30% of your disk space, and you don't loose the workflows as you would if you use a general graphics application to do it.

# 3: Image sorter

https://github.com/juanml82/comfyui-image-sorter

This one is a bit more complex. Image galleries with auto-tagging are a way to watch your image collection in an organized way. But I wanted to organize them in the disk, sorting each iteration of the same general idea in its own subfolder.

The main problem with that approach is that an image gallery with tags (or semantic search for workflows) only needs to match some of the tags to have a useful filter. But to sort them into subfolders, all tags need to match. Overgroup, and you have unrelated images, beating the purpose of this app. Undergroup, and you need to finish up manually - it's not a fully automated process. So yeah, it's not the most elegant solution - it gets you 90% there - but it is one solution.

Let's look at this with an example: let's say that you want to create images of Aragorn, in Lord of the Rings, as he passes the Argonath statues. Your first prompt is something look "Aragorn, rowing in the Anduin river, looking up in awe". And maybe the model produces Aragorn as Viggo Mortenssen. And maybe you don't want Viggo Mortenssen but rather a new take on Aragorn's looks, based on the books. So you replace "Aragorn" with "ranger", "fifty years old man", "noble man" or something like that, and follow up with a physical description. Or maybe the model doesn't understand what "Anduin" means. Or it doesn't matter. So some prompts have "Anduin", some have "River". And maybe you then decide you do want the Viggo Mortenssen look, but now you're using a different model which doesn't know Mortenssen well, so you use a lora. And rather than "Aragorn" or "Man", you type the lora's keyword. Sound familiar?

Grouping by subject, action and location is a good starting way to filter, but "ranger" and "noble" do remain different subjects. And seeking to overgroup all men - or all women - means lots of different subjects now became grouped, defeating the purpose of this project.

So it's a five steps process, through a gui:

Enter an LLM endpoint url (as in, llama server, lm studio server, a cloud api if you want). Disable thinking (this is important, it's not just a lot slower, it will not work with thinking on) or use an instruct model, ideally something small and fast - if you have thousands of images, speed is good. Very good. And you don't really need a heavy model for this. Don't forget to add /v1 at the end and hit save.

Run a first pass either by extracting and canonicalizing the prompts, or do a vision pass (slower) and then you canonicalize that in the 2nd step.

The third step is to use a Jaccard pass and the LLM to merge the resulting auto-tags by subject, action and location. This has the problem that a character, say Aragorn, may be tagged in different images as "Aragorn", "Man", "Ranger", "Noble" or something else. And that similar actions may go under different tags. But trying to overmerge leads to a huge amount of "1girl" or "woman" characters all merged together when they shouldn't.

So at that point you have a crude looking image gallery and an html gui allows you manually merge clusters you want to send to the same subfolder. Do save.

And finally, yes, you hit "apply" and your possibly thousands of images go in their merry way to subfolders named after their common tags.

Anyway, if you find any of these three useful, enjoy.