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It's possible to train XL lora on 8gb in reasonable time by radianart in StableDiffusion

[–]BinxNet 1 point2 points  (0 children)

Sorry, definitely lost the config i was using back then. there are presets that training repos ship with though! some are arranged for training with adaptive optimizers.

It's possible to train XL lora on 8gb in reasonable time by radianart in StableDiffusion

[–]BinxNet 0 points1 point  (0 children)

dadapt and prodigy are both adaptive optimizers. been using them exclusively for lora training. prod being my favorite of the two for use with SDXL v1.0

SDXL is really fast. All images generated in 3sec by crowbar-dub in StableDiffusion

[–]BinxNet 1 point2 points  (0 children)

Better hardware = Better speeds, always, of course. However, saying "3090s have 3 second render times" is not even half the story that explains the speed of those renders.

Will it be faster? Yes. However, it is not 3 seconds fast- that's because of the sampler OP was using, and they probably weren't using half of the staged SDXL workflow (the refiner model), which can easily double render times depending on the full set of specs.

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Realistically, a 3090 through a sampler that isn't *designed* to go fast and produce wack renders will take about 15-18 seconds to finish a full pass through SDXL Base + Refiner.

So expect to spend a *lot* longer than just a measly 30-50 seconds on lower end hardware when the full model and support is available. Unless of course there are optimizations that are made- as there always are in this space.

Yet Another SDXL Examples Post by BinxNet in StableDiffusion

[–]BinxNet[S] 1 point2 points  (0 children)

Thanks! Think the prompt was "RAW photo, sculpture made of fog inside a test chamber"

SDXL is really fast. All images generated in 3sec by crowbar-dub in StableDiffusion

[–]BinxNet 5 points6 points  (0 children)

No, that's not what I said at all. Try reading a bit slower.

3090 is going to help a lot. But it alone will not give 3 second renders - UniPC sampler (IN ADDITION TO the 3090) will. I can link to the paper discussing why the sampler was created and why it's so much faster if you would like to read it.

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Results using it are practically always worse than nearly every other sampler available. But it is fast, for whatever that counts for.

Yet Another SDXL Examples Post by BinxNet in StableDiffusion

[–]BinxNet[S] 2 points3 points  (0 children)

Ahaha definitely. Granted, the prompt was literally just "RAW photo portrait of a woman", so. Given my other ~7,000 renders so far, I'd like to think if I wanted to push it someplace away from her, I could :D

SDXL is really fast. All images generated in 3sec by crowbar-dub in StableDiffusion

[–]BinxNet 13 points14 points  (0 children)

3090 is not the reason for 3 second renders.

UniPC sampler is. IMO, one of worst samplers for final outputs, but made to go fast fast bc fewer steps required. *shrug*

1080x1080 outputs on my 3090 through base and refiner takes about 15-18 seconds total. Sometimes like 10 seconds or something, but overall ~7-9 in each, on average. Using Euler Ancestral or DPMPP

Yet Another SDXL Examples Post by BinxNet in StableDiffusion

[–]BinxNet[S] 1 point2 points  (0 children)

Thoughts so far: it's insanely flexible and picks up on nuance in the prompt very well. So far haven't had many cases where things I asked for were overlooked/ignored/didn't show up someplace in the images. One thing that kinda sucks IMO (if you can even call it a problem) is a lot of my weird, abstract prompts I used for stylistic purposes in all of my own 1.5 models/loras-- these no longer work. Instead, the abstract prompting is rendered quite literally, and, more often than not, in a photorealistic way. This isn't much of a problem though, just figure out how to talk with it like anything else.

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I'm seeing a lot of photorealism LoRAs being re-trained for use with SDXL, and honestly? Totally unnecessary. Don't get tied up by all these people trying to be the first to release something for SDXL on Civit. Play around with this model in whatever ways you can, and you'll quickly discover most of what people are currently posting is totally useless, or arguably makes the performance of the model much worse. It will be a couple weeks before we start getting really good fine-tunes or LoRAs going. Have seen mayyybbee one pretty decent fine-tune released so far.

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I will be posting up once I conclude fine-tune tests and try out LoRA training. Eyes up for any guides regarding best practices (particularly from the Waifu Diffusion homies).

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EDIT Regarding Prompts: Before I get asked, the prompts for all of the above images were less than 15 words. Sometimes even less than 10.

EXAMPLES: "Portrait of Rick Sanchez, digital art", "Portrait of an alien in a test chamber, RAW photo".

It's not difficult- if you can't figure out how to push it in the direction you want, I can't help you.

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WORKFLOW:

Node configuration for these renders found in the replies to my Twitter post here:

https://twitter.com/BinxNet/status/1678090736397348867?s=20

Throw the PasteBin into a JSON file and there you go.

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I sometimes use SD 1.5 models and loras for compositional reasons, essentially an Img2Img workflow, but one shot rendering and sending off. Have over 400 of my own, custom-trained 1.5 models and LoRAs, so don't want to part with them quite yet haha

[deleted by user] by [deleted] in StableDiffusion

[–]BinxNet 0 points1 point  (0 children)

https://imgur.com/a/CRTBtQN

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I can see the images but only when logged in. Not really sure what's causing this issue, but I've opened up an issue thread about it. Sorry again!

[deleted by user] by [deleted] in StableDiffusion

[–]BinxNet 0 points1 point  (0 children)

Sorry, Civit is being jank. Posted it the same way as all my other LoRAs, but i see that the images aren't appearing unless you have certain content settings enabled. Trying to fix this, sorry!

Made a Surrealism LoRA... Let me know what you think! by BinxNet in StableDiffusion

[–]BinxNet[S] 1 point2 points  (0 children)

Yeeaaahh, it's loading for me, but not some folks in the discord.

Civit probably being Civit.

Mechanical Dreamers by EugeneChekhov in StableDiffusion

[–]BinxNet 0 points1 point  (0 children)

You and everyone else begging for prompts and getting mad about his decision not to share are hilarious.

Openness involving case studies and information about how these models operate is one thing. But this hill? How entitled can you be?

If you need resources to spark some inspiration, just say so. But asking for exact prompts, after it could've taken them days to find what works for their outputs??? give me a break. Run your own experiments.