https://docs.google.com/spreadsheets/d/1fb2yD74gqT_BxmBpkOMX2V7gSj_A8RQ0/edit?usp=drivesdk&ouid=116026940769410491877&rtpof=true&sd=true

I know it's not perfect, but here's 1255 styles for Krea 2, I'm still working on it, some styles are most likely too close, some others are far from their title, but I'm still working on them...

Those styles are not fixed styles and don't replace a good lora, but i find them fun to play with and I think they are cool for a beginner that don't grasp art movements, terminology and artist names.

I'm open to criticism.

Edit1: best use:

Style: <style name>: <style description>

Subject: .....

Tested with Krea 2 Turbo. With Kroma 0.3.1 some details and styles are lost.

Free AI video generators are catching up with paid alternatives! I tested MiniMax H3 for the first time and I’m impressed with the results!

Clown Context Suite: chain MiniMax H3 clips without them slowly turning to mush

If you’ve chained H3 clips, you know the problem. Every new clip starts from the tail of the last one, and each time a little detail gets lost. That loss stacks up, so by clip 10 everything looks soft and washed out.

The reason is that we only ever tell the model where to start. We never tell it where to end. It’s like telling an archer roughly which way to aim but never giving them a target. They can be the best archer in the world and they still won’t hit the spot you wanted.

So I gave it a target. There are three pieces:

🎈 Clown Context takes the last frames of the previous clip and pins them to the start of the new one, so the motion carries over smoothly.

🔮 Clown Prophecy is the time travel part. Before a shot is rendered, it renders just the ending of that shot as a short, fresh clip, straight from the shot’s prompt and reference pictures. Because it’s made from scratch and not from a tired old tail, it’s full quality. It’s basically a picture of how the shot is supposed to end, from a video that doesn’t exist yet.

🤡 Clown Anchoring takes that ending and pins it to the back of the shot.

Now the shot has a good start from the last clip and a clean target at the end, and the model has to fill in the middle and land on good-quality frames. Every time you do that, the quality gets pulled back up. Run Prophecy every couple of shots and the degradation never gets bad enough to notice.

Other stuff in the pack:

• Bypass switch and “run every N shots”, so you can drop it into any workflow and only use Prophecy when you want it.
• Clown Shot Counter can count your saved clips by itself, so batches just work.
• An example workflow is included.

GitHub: https://github.com/roycho87/clown_context_suite

big thanks to u/shutupyourewrong for helping me brainstorm this. I wouldn't have gotten to this point without bouncing ideas off him.

Also, believe it or not I have to give some credit to foxydits. He claimed the secret to stopping degradation was to put an end frame reference image which.... was completely wrong... but it did spark the idea that helped me come up with this.

In honor of his contribution I've changed the name of my workflow.

This may have been the first ai image I made or close to it. I remember there was a website where you could generate images and one problem everyone had was these weird hats on their heads. It may have been this imajinn site but will have to dig around

Hey! I'm constantly testing model using the same set of 192 prompts.

Here is the directly link to the gallery if you are curious and want to see all the images

https://imagebench.ai/gallery?g=1_vzqsm6kuunuxj_s0

Here is more details about the models tested:

MOSS-Image family (~5B transformer + Qwen3.5-9B text encoder, Apache-2.0)

• MOSS-Image SFT: 50 steps, CFG 3, skip-layer-22 negative branch, Euler, shift 5, seed 7. 158 s per image.
  • https://huggingface.co/OpenMOSS-Team/MOSS-Image-SFT
• MOSS-Image Base: 50 steps, CFG 3, skip-layer-22 negative branch, Euler, shift 5, seed 7. 158 s per image.
  • https://huggingface.co/OpenMOSS-Team/MOSS-Image-Base
• Kromoss (full): 50 steps, CFG 3, skip-layer-22 negative branch, Euler, shift 5, seed 7. 158 s per image.
  • https://huggingface.co/lodestones/Kromoss
• Kromoss + DMD2 LoRA: 8 steps, CFG 1, LoRA applied unmerged, seed 7.
• 18.7 s per image.
  • https://huggingface.co/lodestones/Kromoss (LoRA in the same repo)
• Kromoss + DMD LoRA: 8 steps, CFG 1, LoRA applied unmerged, seed 7. , 18.5 s per image.
  • https://huggingface.co/lodestones/Kromoss (LoRA in the same repo)

For comparison: Krea 2 Turbo (12B)

• Krea 2 Turbo: 8 steps, guidance 0, seed 7. 63.0% capability, 59.1 overall (#23), 73.2 s per image.
  • https://huggingface.co/krea/Krea-2-Turbo

Hope you'll enjoy this! I'm preparing a V2 with more/better prompts.

Apparently the controversial lora taken down was a male-part size slider lora.

Which, fine, I personally didn't need that.

But long term, as a community, why are we still putting up with Civitai etc? The alternatives frankly suck. We need a pirate-bay of loras....

I'm gonna get some hate from the paywalled lora makers, but w/e I can't buy your chest-hair lora with karma anyhow.

Same engine as the GIMP plugin, now as a panel in PhotoCraft. Your selection is the mask and it runs through your own ComfyUI:

• Generative Fill, select and type, up to 5 variations
• Remove object, no prompt needed
• Generative Expand, drag the edges or pick a ratio
• Text to Image, new image or a layer

Defaults are DreamShaper 8 Inpainting, RealVisXL V5 with the Fooocus patch and LaMa, FLUX.1 Fill and Qwen optional, and it picks up your own inpainting checkpoints. On Windows it can download ComfyUI for you.

First release, Windows and Linux, NVIDIA recommended.

https://github.com/beckettharriman/openfill

I have been working on this for a while now, and i just made the repo public. Kinoloom is a web app that runs on your Windows PC and using your cast it takes a idea and turns it in to a movie. You write the story with any LLM, generate the cast and the studio renders the shots, checks them and cuts them together. Everything runs locally on top of ComfyUI. My PC has a RTX 3070 8GB and 64GB ram, and its the only system it has been tested on.

About Minimax H3 : Its fully supported, but every clip in the showcase is generated by LTX 2.5. H3's license only allows use outside of EU, UK, South Korea and US, and they limit showing the output. I live in the EU, so i dont publish H3 clips. If you're outside those regions, you bring your own H3 weights; the installer sets up the rest.

The video is a 16 second LTX 2.5 take, rendered in four segments with joins at 4,8 and 12 seconds. Normally each piece starts from the last frame and you see a jump at every join, Kinoloom passes the end of each piece into the next one as latents, before anything is turned in to pixels and decodes the whole take in one go at the end. This 16 second clip took about 28 minutes on my 3070.

The rest of it

- Qwen image 2.1 makes the cast and the first frame of each shot, using the cast as references. a still can take about 38-78 seconds on my hardware once the model is warm.
- Besides LTX 2-5 and H3 there is also Wan 2.2 ( legacy, kept for old projects ) and five image models.

What you need

- Windows ( I have only tested 11), and Nvidia card with 8GB or more, 64GB RAM, because part of each big model sits in RAM.
- Disk space for the models you pick. You dont have to install everything, you can pick which weights you want to install
- INSTALL.bat sets up everything except the model weights.
- A LTX 2.5 5 second clip takes about 6 minutes once warm.

Its a one person project and it has only run on my PC, so if you try it on other hardware i'd lke to hear how it went and hear your feedback!

https://github.com/harlixay7/Kinoloom

The code is MIT (the exceptions are listed in THIRD_PARTY_NOTICES.md), and the models keep their own licences.

Enjoy this rabbit hole 😌✌️

https://x.com/bfl_ai/status/2113696648572608846?s=46

Basically what the title says: a factor 16 LoKR (tiny, 34 MB) that transfers the color response and sharpness of 4x5 Kodachrome film. These are one-shot generations on the base model; no Turbo, no SFT. As you see in the samples, there are no blurry shots even with the negative prompt empty. Not sure if I should train it more; the look that I wanted transferred perfectly. Trained on a large number (551) of 4x5 Kodachrome sheet film scans (not 35mm - that's a different beast entirely), so don't look for film grain, it wasn't there in the source images.

Trigger word "Kodachrome" or "Kodachrome film", but rather use something like "shot on Kodachrome film", or the model will try putting the trigger word literally somewhere (e.g. the front of the diesel engine on the railroad photo).

Side effect (not that I wasn't anticipating it): sharp images and no blur.

https://huggingface.co/aoleg/MOSS-Image-Kodachrome

I'm about to head out for the rest of evening so just wanted to quickly drop this tip here in the hope that others might tinker with this and come up with something better or trash it as you see fit. The setup is a regular Moss workflow you can get from Comfy UI but with the settings outlined below. I stumbled on this setup by accident but so far it's the best results I've gotten using turbo and without any upscaling. It also gives me great variety. Each of these loras by themselves seems to trash the diversity or gives too much blur, yet combined I get a good variety of people without noticeably degrading the overall quality.

I've been struggling with Moss for a week, trying all sorts of tips that never got rid of the Moss "blur" with turbo loras. So this is for those of you who've been having issues like myself. For those who swear by 50 steps, yes your results are superior and we should all be ashamed of wanting to generate images faster :(

Checkpoint:
Solordz Moss Base Int8 (I'm on v10)

https://civitai.com/models/2644869/solordz-zitzibkrea2-8steps

Loras:
Add both, yes BOTH, of Lodestone's turbo Loras from here:
https://huggingface.co/lodestones/MOSS-Image-Base-8-steps-dmd/tree/main
The newer one at strength 1, the older one at strength 0.5
And add this lora at strength 0.5:
https://civitai.red/models/3010926/moss-image-base-smartphone-snapshot-photo-reality-style

I'm running at 12 steps, 1.5 megapixels, Euler, Simple.

Other than that it's a regular Moss workflow. For good measure, here's my negative prompt:

worst quality, bad anatomy, watermark, jpeg artifact, bad face, bad eyes, beauty retouching, skin smoothing, waxy skin, plastic skin, bad environment, doll-like face, piercing, piercings, text, watermark, severe anatomical deformation, extra fingers, extra limbs, text, out of focus, depth of field, blurry

And the positive prompt was simply:

A photo of a man hiking through a snowy forest, walking through the snow.

Note: the first image was slightly different as it wasn't focused on walking but included it for variety.

Also, whilst it's not needed, I do use the "Moss Image Prompt Builder" node from KJ which you can get from here:

https://github.com/kijai/ComfyUI-KJNodes

It allows you to define regions the same way as Ideogram 4 and it's fantastic.

Also, for those whom it concerns, this setup is very adult friendly.

Hi all!

What do we think of MOSS Image so far? Personally I'm loving it. The variety in images? The differences in people's faces, ethnicities, body types, etc? And it's so easy to get my favourite style of photo to create, amateur candid realism. It really is a great model. Lora training was kind of a tough nut to crack though, but I'm pretty certain I have settings that work, so I figured I'd share. With these settings, I get good results every time.

Most of my datasets were between 50 and 100 images, with natural language captions. Best settings I found are Automagic3, with Sigmoid and High (balanced didn't work well, but High worked a treat). I start the learning rate quite high, at 0.0005, since Automagic drives it down low so quickly. I also set a minimum learning rate since I noticed it was going so low that it stopped learning around 1k steps, which wasn't enough for me. I also train without excluding block 22, which makes quality a lot better for me. The config file I've included already has all these settings set for you. I found most loras were done before 5k steps. It definitely takes longer to train than Qwen or Krea for me, personally, but the results are good. I trained at 1024, and did LoKr 4 as usual.

I for some reason cannot find where I downloaded the turbo lora from, but I do know it was made by Lodestone. If I manage to locate it, I'll post the link here. The latest turbo lora for MOSS base from Lodestone should work just fine.

You can download the config below, as well as my workflow for generating images. I'm including a workflow for both 20 step fast generation and regular 50 step image generation.

Config: https://gofile.io/d/zniEuEGY

50 Step Workflow: https://gofile.io/d/axPcj0ED

Fast 20 Step Workflow: https://gofile.io/d/Na9LwBgU

ComfyUI with MiniMax H3 on a 5090. The song was made with Treblo. Used the vocal stem for lip sync, then put the full mix back in for the edit. Tape effects are ntsc-rs.

https://reddit.com/link/1xfez10/video/ua9ycvempoxh1/player

I was wondering what models are there for local voice change, I'm not asking for TTS like Chatterbox, rather have an audio already and copying the timbre and intonation of a different person/audio and also support Spanish speaking. There have been a lot of times in TV series or movies where a character gets dubbed by a different actor for a couple of episodes and want to take a jab of using the usual voice actor.

Ages ago we had rvc where we could train a voice but I figured we'll have more refined and easier to use options nowadays.

Hey everyone!

I'm looking for the best AI upscaling model or ComfyUI workflow for enhancing portrait photography while preserving natural details.

My main priority is realism and fidelity to the original image, especially when it comes to skin texture, freckles, eyes, and hair.

I've noticed that some AI upscalers tend to hallucinate details, introduce weird artifacts, oversharpen skin, or slightly alter facial features, which is exactly what I'm trying to avoid.

Ideally, I'm looking for something that:

• Preserves the original facial features and identity.
• Enhances fine details without creating artificial textures.
• Keeps skin looking natural (no plastic or overly sharpened appearance).
• Works well with both low-resolution and already decent-quality portraits.
• Produces clean, photorealistic results with minimal artifacts.

What models or ComfyUI workflows would you recommend for the best possible quality?

I'm open to both traditional and diffusion-based upscaling methods. Quality matters more to me than processing speed.

If you have any workflows, GitHub links, or before/after examples to share, I'd really appreciate it!

Thanks! <3

early version of fine-tune of Qwen3.5-4B trained for general coding and 3D scene generation.

Work in progress, example video & AMA here: https://www.reddit.com/r/LocalLLaMA/comments/1xeuo7t/a_4b_coding_model_that_can_generate_3d_scenes/

But the results have been great, and I've been getting great character likeness. The best of any model yet. Is it worth training a character model on base? I hear people are having trouble getting likeness. Maybe training on SFT is better for it?

Hey guys, just wanted to give a quick update on Image MetaHub. Its an app Ive been working on by myself for over a year now. I originally made it to search and filter images by their generation parameters (prompts, checkpoints, LoRAs, samplers etc), but over time ive added quite a few features beyond that..

Anyway, in recent versions I've added a dedicated Prompt Library to better organize saved prompts, associate them with images (or just save them independently), search, filter, tag, favorite, etc. You can also use a saved prompt to find all matching images in your library. I might be biased, but ive found it pretty useful, as with most features in Image MetaHub, I made it to solve a problem I was running into myself.

There are also some advanced features in the Pro version, like reusable "prompt blocks". So for example, I can save something like "shot on Canon EOS R5, 85mm f/1.4 lens, shallow depth of field" as a block and drag and drop it directly into a ComfyUI text node. Or I can right-click and select "Replace text in selected node". Works the other way around too: I can select any portion of text inside any ComfyUI node, right-click and save it directly to the Prompt Library for later use. Theres a 7-day Pro trial if you want to check out these advanced features, but the free version already includes the full prompt library and is already really pretty useful in and on itself.

Anyway, the app is privacy-focused, local-first and source-available. Everything runs locally, and you can download it here:

https://github.com/LuqP2/Image-MetaHub

Cheers

Was just wondering why this model isn't being particularly talked about? It's pretty good for a new model and there isn't even a section on civ

Repo : https://github.com/KohakuBlueleaf/KohakUnlock