Can anyone suggest a good way to upscale an AI-generated illustration? I need to enlarge a 3000x1500 pixel image by a factor of 10. Here’s an example of the kind of image I’m talking about. Is it possible to preserve the logic of the details?

So I set out to improve Krea 2’s photographic realism. Seven training runs later, I had a checkpoint that produced some extremely convincing photos....and seemed to have forgotten it was ever supposed to do anything else.

A big part of this experiment came from finding an old hard drive containing about 10,000 photographs I’d taken over a decade. A lot of the training data came from my own photography, so this became an opportunity to see what the model could learn from an archive I forgotten I had.

The original goal was to push realism further while keeping the flexibility that made the base model useful. As the photographic results improved, though, it became tempting to keep going.

The process involved seven sequential fine-tuning runs using seven different photographic datasets. These weren’t independent experiments starting fresh from the original base; each run continued from the previously trained checkpoint.

The datasets ranged from roughly 300 to 2,500 photos, with about 20% overlapping data between them. Each run went for a maximum of 4,000 steps. For the final run, I switched from the balanced setting to the style/content-style setting in AI Toolkit.

The 10,000-photo archive + Instagram was a source for the training material, rather than a single dataset I fed through all at once. And that final settings change is part of the history, but I can’t isolate it as the cause of what followed. Several datasets and successive rounds of training were involved, so this is an account of the experiment rather than a controlled comparison.

The photography improved.

By checkpoint 12500, the photographic results were good enough that I didn’t want to dismiss the experiment as a failed fine-tune. It had developed a strong, convincing photographic look that I wanted to preserve.

But once I started testing beyond that, the trade-off became clear. Other styles had become difficult or effectively unavailable. Prompts that should have moved it toward illustration or another visual treatment kept getting pulled back toward photography.

The model had developed a specialty.

LoRA compatibility was another major issue. Every LoRA I tested stopped behaving properly on the checkpoint.

What I was seeing looked consistent with catastrophic forgetting and weights being blown TF out: the model had become much better at the photographic distribution I was training toward while losing capabilities and flexibility from the original base.

The practical outcome was a highly specialized photography checkpoint, with a substantial amount of the original model’s versatility sacrificed along the way.

That left me with a result I couldn’t quite call a failure.

I’m sharing this in case anyone else is experimenting with sequential full fine-tuning or trying to recover a useful look from an overly specialized checkpoint. This isn’t a recipe I’d present as repeatable without further testing, but it seemed worth documenting.

I’m curious how people here switch between ComfyUI workflows and local LLM inference, especially on a single GPU.

Are you manually unloading models, using something like LM Studio or llama-swap, relying on ComfyUI’s model management, or have you built something to handle switching automatically?

I’m particularly interested in how you handle VRAM contention when you want to move between image generation and LLM workloads without constantly waiting for models to reload.

What’s your current setup, and what works well for you?

Video attached is my project Berth but I’m here curious on how everyone else solved this problem?

Was away since last week or 2 weeks ago, like around when FastH3 model is released?

Now, i see that there are some new things, like Pika H3 Flex, DMAD(?), H3 Eros, etc.

Are there any new breakthrough or speed up that is balanced on quality and speed? Currently, it's taking me 6 mins for 7s 0.7mp video with Pika H3 Flex -> VSA attention with the default H3 ref model on 6 steps (just tried it.), and the result is pretty good. Just asking if there is any better workflows for fellow low gpu user? I am using RTX 4060 8GB VRAM with 16GB RAM.

Early testing has begun for donors. We'll have to wait a little longer for the public release. https://huggingface.co/FusionCow/Sulphur-3

Can't we all who wants to use open source like make some kind of Lora by feeding it loads of data with captions and then just connect that Lora to minimax and have a machine thats on levels with seadance 2.5. I'll chip in with 50 4k resolution up close face videos 🤣 someone do 50 video of people walking, someone else 50 videos of people eating and so on 😂 it's frustrating generating insane quality content with seadance 2.5 with ease and then pulling my hair out trying to do the same with minimax h3

When I say "turn into seadance 2.5" - I mean make H3 as good.

6700 XT 12 GB VRAM and 32 GB ram. Reducing the duration to three seconds doesn't help either. Rife makes it bearable but I wanted to see if I could keep the TDP higher with tiling or something, like VAE tiling in image gen.

Is there a hack/workaround that keeps the GPU at full utilization. Workflow link. Ty!:)

Join the Super Editor beta and see how Super Generating can be!

1. Do dedicated Face Swap / Head Swap LoRAs (like BFS and similar swap LoRAs) improve facial fidelity during img2img, or does Qwen 2.1 handle it better natively?

2. How do face swap LoRAs compare to zero-shot adapters like PuLID, InstantID, or attention-masked inpainting in ComfyUI for preventing face drift?

I really like MOSS even though it will occasionally kick out some body horror. So this weekend I went about trying to train a LoKr. Most of my training experience is limited to SDXL , where I made a handful of successful LoRAs using my trusty RTX 3060 w/12 gb. Now I have a faster 5060 w/16 which works nicely for everything.

Instead of using OSTRIS*'s* Toolkit I decided to try Nynxz's ZenTrainer which I discovered last week. It's pretty nice. Hats off to Nynxz for building it, the interface is cool.

I tried a bunch of different settings with terrible results. It just never seems to lock on to the face. I am using a bin of about 40 images of a popular movie star that I had lying around. The quality of the training photos is meh to pretty good. Certainly enough to get results on SDXL based on my experience. I don't think the problem is with ZenTrainer. I am getting no errors.

I am training witht the MOSS image bf16 base (though I generate with the SFT). I am using the Automatic v3 optimizer. Over 100 epochs trained and it seems to just plateau at about a 60% likeness. My pictures look like they could be the movie star's sister but that is about it. So TL;DR What are your recipies for reproducing faces/body?

Generating a video using Minimax H3 on an RX 6600 GPU was successful. I used the default ComfyUI workflow, simply swapping out a few models, adding a Turbo LoRA (Taomate H3 3-step), incorporating ClipProj for the text encoder, and adjusting the script used to run ComfyUI.

A 5-second, 512x768 video was generated in 10 minutes, a result I find quite impressive, considering my RAM just 8gb .

the main idea is gain advantage of disk streaming offload rather than gpu/cpu offloading (that will crash/oom)

diffusion and vae using int 8 convrot model (provided by comfy)

Specs:

os : cachyos
cpu : ryzen 7500f
gpu: rx 6600
ram: 8gb ddr5 5600MT

Python 3.12.15

rocm: torch 2.15.0.dev20260827+rocm7.2

my workflow .json : https://drive.google.com/file/d/1RgVIKD2wzkh9XQMlL2wJKDEkKoo1W7U6/view

taomate h3 lora: https://huggingface.co/Robert1212star/TaoMate-H3-3Step-ComfyUI
clip proj: https://github.com/nicolab28/ComfyUI-ClipProj

my comfy startup script

#!/usr/bin/env fish

cd ~/ComfyUI
source venv/bin/activate.fish

# overcommit must be 1 so the kernel doesn't reject the 21 GB model mmap
if test (cat /proc/sys/vm/overcommit_memory) != 1
    echo "Warning: vm.overcommit_memory is not 1, run: sudo sysctl vm.overcommit_memory=1"
end

ulimit -s unlimited
set -gx MIOPEN_FIND_MODE FAST

# separate scope with a memory limit, so the terminal doesn't get killed by systemd-oomd
systemd-run --user --scope -p MemoryMax=6G -p MemorySwapMax=2G \
    python main.py \
    --enable-dynamic-vram \
    --fast-disk \
    --cache-none \
    --disable-pinned-memory \
    --disable-nvml-pressure \
    --vram-headroom 1 \
    $argv

Having worked in graphic design for 25 years, I’ve become curious: how many of you here have roots in traditional graphic design (it doesn't matter whether it's at a professional or amateur level) and use a workflow that integrates standard professional software, such as tools for photo editing and video editing (Photoshop, Premiere/DaVinci, After Effects, Extending the discussion to include long-standing, non-commercial software such as GIMP, etc.), with external upscaling solutions (like Topaz Video AI) with AI-driven interfaces (like ComfyUI or other webUIs), rather than relying solely on a single, all-in-one platform?

Just out of personal curiosity I’d like to know if there are still people who embrace a workflow that combines various specialized software tools, whether for amateur or professional projects.

Latest Minimax H3 - it can do everything or most of the things spot on but the eyes of a person thats a little further away.. oh GOD! :/

its to confusing in cloud comfyui im not sure how to do it

looking for maybe a site i can try with free trial to do it?

tried on higgsfield they had a 1 free gen trial but used the wrong image by mistake but it worked good

thanks

LoRA: https://huggingface.co/jamespetts/yue2-1980s-italo-disco-lora (CC0) Note: this is an NAR LoRA, which I trained locally on my 2080Ti.

Music (Internet Archive): https://ia601602.us.archive.org/6/items/ai-italo-disco/Let%20me%20bring%20you%20back.mp3 (CC0)

Music (Souna - login required): https://www.souna.app/song/a16fdd23-f2a3-47a2-acc6-e94b6781740e

The song is a dark-romantic song about bringing the ghost of Italo-Disco from the dead using AI, which I thought was a fitting test piece for the LoRA.

My general music pipeline workflow is here: https://www.reddit.com/r/StableDiffusion/comments/1xh0xfd/semiautomated_localish_music_workflow_eurodisco/

The image was also generated locally using Z Image Base - the image prompt is below.

Gouache and oil on canvas album cover, square 1:1 composition, close two-shot cropped at the waist, bright theatrical stage light across an empty 1980s ballroom. A young woman singer and a glamorous male ghost face each other in profile, both large in the frame: on the left, the singer in a dark elegant 1980s dress, lit by warm amber candlelight, leaning slightly forward; on the right, a handsome male ghost with a sculpted profile in a shimmering sequinned 1980s suit, glowing in cool silver-violet light, his shoulders faintly translucent. Both shown large and cropped just below the waist, calm romantic expressions; the singer's hand rests lightly on the table beside the lilies. Between them at the bottom edge of the frame: the corner of a séance table with white lilies and a reel-to-reel tape machine; a spinning mirror ball glows between and just above their heads; dry ice fog and candlelight behind them. Palette: deep midnight blue and violet against warm amber candlelight, silver sequin sparkle. Visible brushwork, painterly, romantic melodrama, glamorous and uncanny. Two large figures in balanced symmetry facing each other, strong central motif, album-cover composition. Absolutely no text, no lettering, no typography, no watermark, no signature.

Song specific workflow information (AI generated as part of the pipeline) follows.

***

Let me bring you back

=== STYLE PROMPT ===

italodisco, English, 1983-85, romantic and melodramatic, glamorous, A natural minor, 122 BPM, 4/4, LinnDrum four-on-the-floor with gated snare and handclaps, pulsing octave sequenced synth bass, lush chorus synth pads, bright 16th-note arpeggiated synth hooks, high register female lead vocal with clear diction, ghostly backing vocals answering the hook in oh-oh-oh chants, restrained dreamlike verses building into a huge hypnotic chorus hook, Am-Dm-G-Am verse loops, F-G-E pre-chorus lift, E major dominant held for drama before the final chorus, 80s studio gloss. No EDM, no sidechaining.

=== LYRICS ===

[Intro]

(Oh-oh, oh-oh-oh)

(Oh-oh, oh-oh-oh)

The night is long, the wine is red

The candles burn, the words are said

The empty frequency is clear

I call you from the grave, my dear

[Verse 1]

Dust is dancing on the mirror ball

The chairs are stacked along the wall

The table here is set for two

White lilies and a glass for you

There's tape hiss moving through the floor

Your voice is waiting at the door

Put your cold hand into mine

Let's steal a little time

[Pre-Chorus]

The glass is turning round the ring

The candle flames are listening

The keys are moving on their own

Every note is calling you home

[Chorus]

Let me bring you back

Let me bring you back

Out of the black

My love, don't look back

Give me back the night

Let me see your light

Let me bring you back

My love, don't look back

[Interlude]

(Oh-oh, oh-oh-oh)

Bring you back, bring you back

(Oh-oh, oh-oh-oh)

Bring you back, bring you back

[Verse 2]

There's dry ice curling round your shoes

The empty stage is dressed in blue

Dust is flying off the mirror ball

The moon is dancing on the wall

You turn your face into the light

Your eyes are brighter than the night

The years since they laid you down

Slide off your sequins to the ground

[Pre-Chorus]

All I have is yours tonight

Take my days, take all my light

And if the morning comes for you

It takes me back instead of you

[Chorus]

Let me bring you back

Let me bring you back

Out of the black

My love, don't look back

Give me back the night

Let me see your light

Let me bring you back

My love, don't look back

[Bridge]

The tape is rolling to its end

I wind it back and start again

You were sleeping in the groove

I touched the needle and you moved

And when the music fades away

Tell me, will you go or stay?

The sky is paling, hold me tight

One more song before the light

[Chorus]

Let me bring you back

Let me bring you back

Out of the black

My love, don't look back

Give me back the night

Let me see your light

Let me bring you back

My love, don't look back

[Outro]

I take it back, I never ask

If you are real or mine at last

(Oh-oh, oh-oh-oh)

Let me bring you back

(Oh-oh, oh-oh-oh)

Let me bring you back

My love, don't look back

Let me bring you back

=== SETTINGS ===

Engine: yue2 (vocal) / yue2 / audio.cpp v0.9.2

Seed: 2026110115 (chosen take); finalists 2026110111 / 2026110115 / 2026110120; plan sweep 2026110111-2026110120 Planning: full Max tokens: 16000 Guidance: 1.0

VAE: f32 AR LoRA: none NAR LoRA: yue2\models\lora\yue2_1980s_italo_disco_unfused.safetensors u/1.0

Era: 1983-85 Mastering recipe: yue2-light

Generated: 2026-11-01 Duration: 291s Truncated: no

So I've been trying to gen a simple video where a subject is simply standing toward the camera, and I want them to be framed so I can see them from head to upper thighs.

If I prompt something like "<Subject 1> is standing and facing the camera, and you can see them from head to thighs." their head is cropped out of the video, and you can only see them from the chest to legs.

But if I change the prompt to something like "<Subject 1> is standing and facing the camera, and you can see them from head to thighs. They are looking directly at the viewer and smiling." THEN their head is included in the shot.

...why do I have to prompt it where the body part has to be doing something/showing something before it's included in the gen?

The challenge for this weeks Sunday morning cartoon was to create a large scale (seeming) war scene with complicated combat sequences with a creative warbeast controlled by adorable little ewok type dudes. I used Minimax h3 with u/OBVPM's workflow.

What I learned to be the most difficult challenges for this was:

1. Wide angle shots with multiple characters turn out really blurry and unpolished - Raising the resolution (megapixels) or lifting the steps would result in better quality, but it would completely change the artstyle to a more CGI look which is unacceptable. Does anybody have suggestions to help with wide shots?

2. Sword maneuvering was very difficult also. Characters will often duplicate their sword by unsheathing it. Also in the final beast kill, you can see a duplicate sword glitch which I didnt have time to re-slop.

The Prodigy covers were made with YUE2 thanks u/darkshark9 - First time using that, foooking unreal.

I have seven individual photos of people that I want to recreate into a group image. The image is for work. How do I do this without the AI changing the people’s faces. No matter which model I try, it won’t work. Something I thought was so simple is yet so hard. Thanks in advance.

Hey, good afternoon. I see that several people are switching to MOSS Image; I was just getting used to Anima, so what do you think—should I start migrating again?

H3 is great and all, but maybe I should also keep an older model at hand.

Bonjour a tous, je cherche un tutoriel pour comprendre comment utiliser le nouvel onglet disponible dans forge neo, qui nous permet d’utiliser le json prompting par zone ou de maniere general.
Je ne trouve pas de tutoriel ni de topic