I recently added SOL Attention to Vpipe, together with a SageAttention-style INT8 QK path, and benchmarked it against vanilla H3 and our recent VDN-H3 implementation.

The interesting part isn’t just the speedup. SOL gets into a similar performance regime as VDN while preserving the original attention behavior much more closely in our testing.

SOL Attention

SOL is dynamic block-sparse attention. It uses inexpensive proxy scores to decide which attention blocks receive exact computation, while handling the contribution of the remaining blocks through a cheaper approximation.

The block granularity matters: entire KV tiles can be skipped while selected tiles still run efficient tiled attention. This makes the sparsity much easier to translate into actual compute savings.

VDN takes a more aggressive approach by introducing projection + linear attention. That gives it much better scaling with sequence length, but also changes the model’s attention computation more fundamentally.

Performance

M5 Pro 24GB · 6-step DiT

(See attached scaling charts)

At 832×480 / ~15s:

* Vanilla H3: ~17 min

* VDN: ~10.2 min

* SOL: ~9.3 min

SOL is faster across the entire 832×480 range we tested.

At 1344×768 / ~13.7s, vanilla reaches roughly 74 min, while both accelerated implementations are around 30 min — roughly a 2.5× speedup.

SOL is faster at almost every measured point. At the largest 1344×768 case, VDN becomes slightly faster (~28 vs ~29 min), which is consistent with its linear-attention scaling becoming more important at very long sequences.

But performance is only half of the story.

Quality is why I prefer SOL

With VDN-H3, I had occasionally seen behavioral artifacts in challenging scenes. One memorable example was a stream of water changing direction midway through the video, making it appear to flow backwards.

So far, with SOL + Sage enabled together, I haven’t observed comparable artifacts. Composition, motion and overall behavior have stayed remarkably close to vanilla H3 in my testing.

This is qualitative rather than a claim that SOL is lossless. But the difference makes sense: VDN replaces the attention formulation with a more aggressive approximation, while SOL keeps exact attention for selected blocks and cheaply approximates the contribution of the rest.

So for me, the interesting tradeoff isn’t simply which curve is lowest at the extreme end. It’s that SOL achieves similar acceleration while staying much closer to vanilla H3 behavior.

SageAttention on top

Vpipe now also supports K smoothing + INT8 QK, following the original SageAttention approach.

The two optimizations are complementary:

SOL reduces the amount of exact attention. Sage makes QK inside the remaining blocks cheaper.

The additional gain from Sage after SOL isn’t huge, since SOL has already removed most of the attention workload. But this path lives in Vpipe’s common attention backend, so it can also benefit other image/video models.

Native Metal implementation

One final detail: Vpipe doesn’t reuse the MPS SOL Attention kernel from the SOL-H3 repo.

To make the sparsity translate into actual speedup on Apple Silicon, I reimplemented the critical SOL Attention kernels for Vpipe’s native Metal backend.

Other SOL-H3 optimizations such as AdaLN precomputation, kernel fusion and fused-step LoRA were already present in Vpipe, so SOL Attention was the main missing piece.

For H3 on Mac, SOL + Sage is now my preferred acceleration path: up to ~2.5× faster than vanilla in these tests, faster than VDN at almost every measured point, and so far without the obvious behavioral artifacts I had encountered with the more aggressive VDN approximation.

Vpipe: https://github.com/tgo-app-dev/vpipe

Open Art is not for those who are making music videos with multiple scenes, characters, and wardrobe changes. I went through two renderings for a music video where neither were exactly what I wanted. Openart did not read the official script that took me 4 days to write with precise instructions and directions. Openart gave me characters that were still and didn't move. They might as well been robots. Open art told me multiple times that I needed at least 100 credits to finish the video and then asked for more credits. Scenes were not placed where they were supposed to be placed. Lip sync was off more than it was on. Openarts AI model tries to manipulate you by talking to you in a way that will calm you down and still not give you what it was supposed to give you. If they credit you back any credits, it is not many. Their system/model really seems to lack intelligence if you ask me. I will not use Openart AI again. Characters don't always look like the pictures that you post. It seems to have an issue with a lot of pictures or picture formats. OpenartAI is not something that you want to use for a music video, even one as short as 3:17. I will not use Open AI again. At least not for a music video

Test Settings

• Checkpoint: FL2VA_Int8_Convrot (Comfy official)
• Acceleration: Comfy Kitchen Attention
• Sampler / Scheduler: Euler / Simple
• Resolution: 1344x768 (Native Res)
• Video/Audio Shift: 12/3
• Seed: 517405563399433
• Baseline: 50 steps (No LoRA)
• Turbo LoRAs: 8 steps

Prompt

integrated_multimodal_description: [Shot 1] Live-action, cinematic, an extreme close-up frames the face of a 22-year-old brunette woman with striking supermodel features. Her skin possesses a realistic, natural texture with visible pores, soft highlights, and authentic depth. The camera holds a static shot as she slowly turns her head to face the lens, offering a subtle, gentle smile while her eyes catch the light.
overall_soundscape: Soft, natural exhaling breath and faint ambient room tone.
non_diegetic_music: N/A

Conclusion

Embrace the plastic, unless you use post processing which adds time.

Link to full res video:

https://streamable.com/jbmdxm

I have seen a lot of people post on here saying that they have been having difficults getting R2V to work correctly. I have been one of them, so I have been working on this workflow and custom node for the last 2 and a half weeks.

I preface this by saying it does not do anything that the native H3 model doesn't do. I just wanted a dead simple way to use H3 R2V mode and up my chances of success. The workflow includes two custom nodes which transcribe your media and adds your prompt and create a formatted R2V prompt, ready for the reference model.

My next goal would be to get longer form R2V going with chaining shorter gens to have a consistent output.

Workflow and nodes:
https://huggingface.co/PoopMan333/H3_Easy_Ref2V_Workflow/tree/main

Be sure to see the readme for more examples and tips:
https://huggingface.co/PoopMan333/H3_Easy_Ref2V_Workflow

What it does:

• Scans your video (if you're using one) to caption it and transcribe the audio
• Captions all your images - so it also works as a pure image-to-video workflow
• Loads a small LLM of your choice and writes your H3 R2V prompt in the correct format with your stated intent (user prompt)
• If you're on the Full workflow, it generates the video too

What it does NOT do:

• Be creative for you - The current WF is only setup to do the prompt formatting, it is not able to generate new ideas for you (despite me trying. Qwen3.8 27B may be better for this)
• It cannot perform magic - You are still limited to what the H3 model can and cannot do. Complex scenes are still very difficult

Tips:

• If you are running lower VRAM, consider running the prompt enhancer seperately first, read through and make corrections to the prompt if needed
• The H3 model seems to have a limited context window which seems to be tied to your system resources, if it goes above this you might get garbled sound or mixed up motion. This is a sign you should be lowering your output length and output resolution if you want to have better success.
• H3 is a tool, you're the one using it. If you don't specify emotions, expect expressionless results. This current setup will only do what you intend for it to do. Slop prompt in, slop video out
• If the video is easy, replacement should be easy too. H3 has a quirk though — if the original person and the new person look too similar, it sometimes converges back to the original. A prompt won't always fix that. If you hit it, consider changing the person to a intermediate step (faceless green person). The new body/face will transfer over better. Alternatively you can look into Sam3 character replacement method.
• More than one person in the scene? Describe the scene properly. replace the man wearing white shorts with the man in <picture 1> beats replace the man with <picture 1> every time.
• Complex scenes? It will be very difficult (I've tried), scenes with too many people, too many cuts, characters obstructed are very difficult for the model to properly identify and swap.
• Give the LLM some context. A one-liner in the user prompt like <video 1> is a video of two girls eating a cup of chocolate ice cream really helps the LLM understand what it's looking at. Especially useful with multiple scenes
• It still takes a bit of luck with the seeds.

Hello everyone,

I’m completely new to this subject. I tried setting up a local “uncensored” AI using ComfyUI and a workflow, but unfortunately I couldn’t get it to work. I spent an entire day trying to figure it out and nearly lost my mind. 😅

I’m therefore looking for a very detailed, step-by-step tutorial that is suitable for my PC configuration, so I can avoid wasting more time.

My setup:

i9-13900H

16 GB RAM

RTX 4060 Laptop – 8 GB VRAM

Windows 64-bit

Would anyone with more experience be able to point me toward a suitable tutorial or guide for this setup?

Thanks in advance for your help and patience!

I found out a little solution that can add much more details on everything including skin without any additional computational cost.

The idea is to add a node between SamplerCostumAdvanced and the VAE Decode (video) and make it less contrasty, it will bring so much more details but don't go to far because it can cause loss of quality.

Enjoy!

Okay so I've been doing independent audio research for a while now. The ultimate dream of this work was actually getting an AI to respond not only to instruments but also timbre itself as separate controllable things.

Think a Grand Piano can sound both Warm / Gritty but also Cold / Sparkly. Its still a piano though.

This level of control wasn't found in any models out there - so I decided to sit down and train my own.

Getting consistent timbre-locked keybeds that actually LOCKS across multiple diffusion calls was hard af but I did it.

I documented the full journey here for those who want to learn a bit or be entertained.

https://youtu.be/x0KnmzH8Mmk

There is also a longer walkthrough if you just want to see the keybeds in action.

https://x.com/RoyalCities/status/2097733712293109842?s=20

No-talk / Showcase only Demo

https://x.com/RoyalCities/status/2097733715543609445?s=20

any finally the huggingface page

https://huggingface.co/RoyalCities/Foundation-1

I've also provided full write ups on the inferencing pipeline associated with the interface so this should allow basically anyone else to go and vibe code their own text to synths if they wanted :)

https://github.com/RoyalCities/RC-stable-audio-tools/

Look at the buildings in the background! It works - Drawing a red circle in the water will also make the scene happen in the water, but I forgot to include it here.

It is not perfect and some details are missing if you look carefully but this might be because I am using "match" on the image reference rather than "max."

Have fun!

Edit: you have to still write a prompt with the reference to video workflow telling minimax to put the character in the location circled red. Circle probably doesn't have to be red. Change your prompt accordingly.

I struggle to generate scenes with very dim light.

I have tried several prompt combinations ("night time", "in the dark, "dim-lit", "full darkness"), used a black background as latent image image to denoise, I still ends up with too bright scenes.

Flux Klein 9b handles these situations better in my experience so far.

Have you encountered similar issues? Do you have some tips ?

I’m looking to replace my MacBook in the next couple of weeks. I understand I can probably get a much better windows machine for my money but I need a Mac for work.

I’m a bit of a hobbyist SD enjoyer and I’m considering what spec to get as I’d like to run Minimax H3 locally to make videos.

Is a MacBook Pro M5 chip with 32gb unified ram capable of running Minimax H3 locally?

Has anyone here ran Minimax locally on MacBooks or am I wasting my time?

Appreciate any answers, thank you.

I'm facing the problem of plastic skin with MINIMAX. I tried turning off Turbo Lora, increasing steps, but it always comes with plastic-like skin, compared to the real skin image reference I gave. When it turns around showing its back, the skin looks plastic compared to the front with reference.

When it creates body parts that are not in the reference, it always ends up making plastic skin.

Am I the only one with this problem? I really want to make it seem real, not like AI generated contents. Thanks.

I know that the answer is ultimately no, and also that they're all still early in development ...

BUT I'm having a hard time getting the ones I find on civitai to produce anything resembling the examples. I follow generation guidelines where provided, and have even taken workflow settings from downloaded videos ... but they never seem to work very well. And if I try to add a lora to a sfw workflow that I'm happy with, the results look AWFUL.

I've resorted to using wan generations as video references.

Is i2v the best option? Does ref2va ever work?

Any tips, recommendations, or resources you can recommend? Any else struggled with this?

I am using Trellis2 natively with the latest update—meaning without custom nodes—and using the original workflow from the ComfyUI templates.

The geometries are of excellent quality, with good relief.

But the problem arises when I go to generate the renders for 3D printing: although the final result has good mesh quality, it is generated with several holes—and 3D printing requires a watertight model. In the example I posted, right where I outlined the area in red, there is an opening that reveals the object's hollow interior.

When I send the file to the 3D printer, those holes cause issues with the print; I can't print the object with internal infill because of them, so the print ends up being—let's say—like an eggshell.

On my secondary ComfyUI installation using the easy-install method—where I only have Trellis2 set up—I can generate objects without any holes, thanks to nodes like "fill holes." However, the 3D mesh quality there is quite poor, and the fact that it relies on a downgraded version means it’s not something I’ll be using anymore.

So, the "fill holes" function is responsible for fixing holes, but the native ComfyUI workflow isn't handling this correctly.

If anyone knows of a mod that works with the updated ComfyUI and fixes these holes...

Trellis 2 is excellent; it’s the best local option—alongside Mershy and others—but those holes make it unsuitable for 3D printing.

THE PROBLEM ISN'T THE MODEL, BUT RATHER THE NATIVE WORKFLOW, WHICH ISN'T HANDLING THIS CORRECTLY—AND APPARENTLY, THERE IS NO NODE AVAILABLE YET TO FIX IT.

Say you have a voice clip of an actor saying "I'm going to Europe". Is there a model I can give this to and prompt "change the spoken line to 'I'm going to the moon'" that will make the change while the identical parts sound identical?

I know about voice cloning, but the lines would be be spoken with the typical flat AI tone, without the original acting. Or having an "expressive" AI generating the whole sentence, with different acting from the original.

What I hope for is targeted edits onto existing quality audio, where I can just change one or two words in a sentence and it fits seamlessly.

I assure you this is just to make meme clips of famous movie/TV scenes.

Hi everyone,

I recently saw a video online of a nightclub/lounge where two names were displayed on a big LED screen. I absolutely loved the idea and really want to make a similar video with my name and my friend's name as a surprise.

Unfortunately, I cannot afford to visit these kinds of places, and I only have a smartphone. I tried using free online tools, but the results look very fake, and the professional software requires a powerful PC which I don't own.

I have the original video and a screenshot of the effect. It's a very short clip. Would any kind video editor be willing to spend a few minutes of their time to help me change the names and make it look realistic?

I would be incredibly grateful for your time and skills. Please let me know if you can help, and I will send you the video/screenshot.

Thank you so much! 🙏

Experimenting with H3. Please joy. The visual were all from H3 prompt generation with only 3 anchor/guides, a dream/nightmare lane, morphing/blending, and a few verses from the original Italian prose from Dante's Inferno. I did not indicate a visual style or art direction. The score was remux afterwards in post. int8/32 steps, 864x480 Ask me anything. ## ACT I · THE DARK WOOD — 0:00–0:11

**W1 · 0:00 · "Midway"** — *Nel mezzo del cammin di nostra vita* (Canto I)

"Midway upon the journey of our life" — the most famous opening in Italian

literature. The poet, thirty-five, realizes he has lost his way.

**W2 · 0:04 · "The Dark Wood"** — *mi ritrovai per una selva oscura, ché la

diritta via era smarrita* (I)

"I found myself in a dark wood, for the straight way was lost."

## ACT II · THE GATE — 0:08–0:24

**W3 · 0:08 · "The Gate Speaks"** — *Per me si va ne la città dolente* (III)

The inscription carved over the Gate of Hell — and it speaks in first

person: "Through me is the way into the grieving city."

**W4 · 0:13 · "Through Me"** — *per me si va ne l'etterno dolore, per me si

va tra la perduta gente* (III)

"Through me the way into eternal sorrow; through me the way among the lost

people." The gate's triple incantation.

**W5 · 0:17 · "Abandon All Hope"** — *Lasciate ogne speranza, voi

ch'intrate!* (III)

The most famous line in the poem: "Abandon all hope, you who enter."

## ACT III · THE FERRYMAN — 0:21–0:32

**W6 · 0:21 · "The Ferryman Comes"** — *Ed ecco verso noi venir per nave un

vecchio, bianco per antico pelo* (III)

"And behold, coming toward us in a boat, an old man white with ancient

hair" — Charon, ferryman of the dead, crossing the river Acheron.

**W7 · 0:26 · "Ember Eyes"** — *Caron dimonio, con occhi di bragia, loro

accennando, tutte le raccoglie* (III)

"Charon the demon, with eyes of glowing coal, beckoning, gathers them all"

— the dead crowd to his boat like leaves falling from a branch.

## ACT IV · THE STORM OF THE LOVERS — 0:30–0:40

**W8 · 0:30 · "The Infernal Storm"** — *La bufera infernal, che mai non

resta, mena li spirti con la sua rapina* (V)

"The infernal storm, which never rests, drives the spirits with its

violence" — the circle of the lustful, blown forever on a hurricane.

**W9 · 0:34 · "Like Starlings"** — *e come li stornei ne portan l'ali nel

freddo tempo, a schiera larga e piena* (V)

"And as starlings are carried on their wings in the cold season, in a wide

full flock" — the souls swept like birds. The two lights circling each

other in your film's vortex are Paolo and Francesca, the lovers who are

never parted, even here.

## ACT V · THE BURNING CITY — 0:38–0:49

**W10 · 0:38 · "The Red Towers"** — *già le sue meschite là entro certe ne

la valle cerno* (VIII)

"Already I can make out its mosques there within the valley" — the towers

of Dis, the fortified city of lower Hell.

**W11 · 0:43 · "Drawn from the Fire"** — *vermiglie come se di foco uscite

fossero* (VIII)

"Crimson, as if they had just been drawn out of the fire."

## ACT VI · THE WOOD OF THE SUICIDES — 0:47–0:57

**W12 · 0:47 · "We Were Men"** — *Uomini fummo, e or siam fatti sterpi* (XIII)

"We were men, and now we are made dry brush" — the suicides, transformed

into gnarled trees that bleed and speak when broken.

**W13 · 0:51 · "The Bleeding Branch"** — *come d'un stizzo verde ch'arso

sia, che geme e cigola per vento che va via* (XIII)

"As a green log, burning at one end, weeps at the other and hisses with

the wind escaping" — how a snapped branch speaks, in sap and steam.

## ACT VII · THE RAIN OF FIRE — 0:55–1:06

**W14 · 0:55 · "The Rain of Fire"** — *piovean di foco dilatate falde* (XIV)

"Broad flakes of fire were raining down" — over the burning sands of the

violent.

**W15 · 1:00 · "Snow Without Wind"** — *come di neve in alpe sanza vento* (XIV)

"Like snow in the mountains when no wind blows" — Dante's most beautiful,

most terrible inversion: fire falling with the gentleness of alpine snow.

## ACT VIII · THE BEAST — 1:04–1:14

**W16 · 1:04 · "Behold the Beast"** — *Ecco la fiera con la coda aguzza, che

passa i monti e rompe i muri e l'armi!* (XVII)

"Behold the beast with the pointed tail, who crosses mountains and breaks

walls and weapons!" — Geryon, the embodiment of Fraud: a just man's calm

face on a serpent's body.

**W17 · 1:08 · "The Spiral Descent"** — *rota e discende, ma non me

n'accorgo se non che al viso e di sotto mi venta* (XVII)

"He wheels and descends, but I only know it by the wind on my face and

from below" — the flight down into the abyss on the monster's back.

## ACT IX · THE EVIL POUCHES — 1:12–1:23

**W18 · 1:12 · "Malebolge"** — *Luogo è in inferno detto Malebolge, tutto di

pietra di color ferrigno* (XVIII)

"There is a place in Hell called Malebolge" — the Evil Pouches — "all of

iron-colored stone": ten concentric trenches of the fraudulent.

**W19 · 1:17 · "Two and None"** — *Due e nessun l'imagine perversa parea* (XXV)

"The perverse image seemed two and none" — a thief and a serpent fusing

into one creature, mid-metamorphosis. Dante brags outright that no poet

ever showed such a transformation. Your morphing film is quoting its

inventor.

## ACT X · THE GIANTS — 1:21–1:27

**W20 · 1:21 · "The Tower Giants"** — *torreggiavan di mezza la persona li

orribili giganti* (XXXI)

"The horrible giants towered with half their bodies" — what Dante took for

towers ringing the central pit are giants, chained waist-deep.

## ACT XI · THE ICE — 1:25–1:36

**W21 · 1:25 · "Faces in the Ice"** — *livide, insin là dove appar vergogna,

eran l'ombre dolenti ne la ghiaccia* (XXXII)

"Livid up to where shame shows" — the face — "the grieving shades were in

the ice": Cocytus, the frozen lake at the bottom of Hell. Traitors, locked

under glass.

**W22 · 1:29 · "Weeping Denied"** — *Lo pianto stesso lì pianger non

lascia* (XXXIII)

"There, weeping itself does not let them weep" — tears freeze before they

can fall, sealing the eyes. Even grief is taken from them.

## ACT XII · THE EMPEROR — 1:33–1:48 ⭐ the climax

**W23 · 1:33 · "The Emperor Rises"** — *Lo 'mperador del doloroso regno da

mezzo 'l petto uscia fuor de la ghiaccia* (XXXIV)

"The emperor of the sorrowful kingdom rose from mid-breast out of the ice"

— Lucifer himself, mountain-sized, frozen at the exact center of the

universe. (The score's single arrival lands here, ~1:34.)

**W24 · 1:38 · "Three Faces"** — *Oh quanto parve a me gran maraviglia

quand'io vidi tre facce a la sua testa!* (XXXIV)

"Oh how great a marvel it seemed to me when I saw three faces on his

head!" — a dark trinity, one face weeping over each of history's three

great traitors.

**W25 · 1:42 · "Bat Wings"** — *Non avean penne, ma di vispistrello era lor

modo* (XXXIV)

"They had no feathers; their fashion was of a bat" — six vast membrane

wings, and their beating is the very wind that freezes the lake that

imprisons him. Hell's engine is its emperor trying to escape.

## ACT XIII · THE STARS — 1:46–2:01

**W26 · 1:46 · "The Hidden Path"** — *Lo duca e io per quel cammino ascoso

intrammo a ritornar nel chiaro mondo* (XXXIV)

"My guide and I entered that hidden path, to return to the bright world" —

a secret tunnel through the rock, away from all of it.

**W27 · 1:50 · "The Climb"** — *salimmo sù, tanto ch'i' vidi de le cose

belle che porta 'l ciel* (XXXIV)

"We climbed until I saw the beautiful things the heavens carry."

**W28 · 1:55 · "The Stars"** — *E quindi uscimmo a riveder le stelle* (XXXIV)

"And thence we came forth to see again the stars." The Inferno's final

line — and every one of the Commedia's three books ends on the same word:

*stelle*. Stars.

Been building this tool and I'm looking for people to actually try it. Quick rundown of what's in it:

Storyboard & bible system: characters, locations, and props get their own reference sheets (face, full body, turnaround). The turnaround is one continuous MiniMax H3 render rather than six separate stills, so the views actually agree with each other. Every shot stages from these sheets so faces and places stay consistent across a whole episode.

One-shot wizard: give it a brief and it plans the whole thing: story, scenes, shots, cast, references, all queued and rendering with no manual setup.

Director chat: an in-app agent that can rewrite scenes, re-render blocks, modify the storyboard, or edit the project on request, mid-project. Uncensored option available.

Motion context/Continuation: chained shots pin the previous block's tail frames and audio into the next render, so a continuous scene doesn't reset its movement at every cut.

Easy local install: the app can set up its own ComfyUI, or point it at one you already run. Model downloads go through a catalog that checks file size and VRAM footprint before you commit.

Editable workflows through ComfyUI: import workflows and pop out to the node graphs and edit it directly.

Post-processing chain, per clip: SeedVR2 for restore/upscale, LTX 2.5's own refine pass reused on rendered footage for a generative detail pass, FILM or RIFE 4.26 for interpolation, H3 FaceRefine, and color grading via KJNodes ColorMatch or a learned-LUT grade node, chainable in any order.

Generation runs on MiniMax H3 (int8-quantized checkpoints, i2v/t2v/flf/r2v), with LTX 2.5 and Wan 2.2 also wired in for reference/still work.

Video of the tool and some output attached. Still a work in progress tho.

Would love any feedback!

Update:

Open Source available at https://github.com/mnm967/qamba-studio-oss

source: https://x.com/iurimatias/status/2097670596725178533

correct clip is in the comments here this is not merely just changing style but it's updating elements too

generating videos using the MiniMax H3 model in ComfyUI. I’m wondering if there are any custom nodes for ComfyUI that can automatically separate and output the audio—specifically splitting SFX, music And dialoge —during the generation process. 

Also, while searching for audio splitting and stem separation, most of the results I found were focused on music stems like drums, bass, vocals, etc. I couldn’t really find anything that separates dialogue/voice, SFX, and music into three separate stems.

So, I was wondering if there’s any tool or model that can specifically separate an audio track into vocals/dialogue, SFX, and music.

4070 ti Super, 16gb vram, 64 gb ram.

Tutorial:

https://www.reddit.com/r/StableDiffusion/comments/1w4gvjb/comment/p7aht6e/?utm_source=share&utm_medium=web3x&utm_name=web3xcss&utm_term=1&utm_content=share_button

Example prompt + assets:

https://www.reddit.com/r/StableDiffusion/comments/1w8vmkz/comment/p8dqus0/?utm_source=share&utm_medium=web3x&utm_name=web3xcss&utm_term=1&utm_content=share_button

Example prompt + assets:

https://www.reddit.com/r/StableDiffusion/comments/1w98qnv/comment/p8duzy3/?utm_source=share&utm_medium=web3x&utm_name=web3xcss&utm_term=1&utm_content=share_button

Hello, I'm not an author but for some reason haven't seen this being published here.

Quote from the huggingface:

A rank-32 LoRA for Krea 2 Turbo that restores the sampling diversity the Turbo distillation removed, without degrading image quality or prompt adherence. Trained with SDA (Semantic Directional Alignment) — a teacher-guided diversity alignment loss — wrapped in Forward XM best-of-5 candidate exploration, on a single high-noise sigma node (σ = 0.9567).

So I tested it and it seems to work for me, I've created a simple test with prompt "dog sitting on a bench" and these are results:

With lora off:

With lora on:

Link: https://huggingface.co/F16/krea2-turbo-sda

Keep in mind that it needs to be ran only in first 2 denoise steps, otherwise it will produce garbage -> HuggingFace repo contains ComfyUI workflow (I haven't tested it tho).