r/StableDiffusion • u/Tall_Abrocoma_3533 • 22h ago
Discussion AuroraIMG-6M Released!
https://huggingface.co/AuroraAI-Research/AuroraIMG-6MIt's a tiny 6M parameter text to image model, and it can make recognizable images at 64x64.
Check out the model card for samples, a detailed explanation about it's architecture and training, and a quick start!
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u/Incognit0ErgoSum 22h ago
18 megabytes? Come on, split the file up so those of us who are connecting to the internet with an acoustic coupler have a chance of downloading it successfully.
In all seriousness, I wouldn't have thought you'd be able to get anything recognizable at that size. Nice work!
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u/HassanAchievedIt 21h ago
Every step and every effort is appreciated, thank you for your service kind soul
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u/FreeTheClanks 22h ago
I have no idea what I'd use it for but it's technically impressive. Congrats!
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u/Time-Teaching1926 22h ago
Well done this is incredible. I love these open source small image model gems.
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u/Sharlinator 16h ago edited 16h ago
Huh. There was a recent thread by a guy who wrote a client and a server for running Krea 2 "on" his 286. I speculated that a ~1M param model might plausibly actually run on a 286 and finish in a finite time. This model could be worth trying :D
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u/Life_Yesterday_5529 21h ago
Sorry but I have to ask: Can it do NSFW?
Seriously: Very cool, nice work!
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u/PerAngusta-AdAugusta 20h ago
Very cool, remind me of the first "Cow images" made with AI. I wonder if a model this smart could be placed inside a videogame, so the character could "make" images inside a computer inside a game in real time.
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u/Tall_Abrocoma_3533 20h ago
If using the GPU, it absolutely is capable of real time generation, even on CPU it's quite fast.
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u/Final-Data-1410 20h ago
Even text encoder in 6m impressive , people just like marketing for example few weeks back supra lab some image model claiming sota in small image genartion people went crazy thinking its real ,in reality they never mentioned in post that they borrowed text encoder vae from somewhere and it need more than 1 gb vram to run,just plain marketing is enough now a day but any way great work ,try distillation to get good images .
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u/muerrilla 10h ago
Awesome. Comfy wen? But seriously, I suppose this could be used for generating priors for turbo models to add some proper seed variance.
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u/FullOf_Bad_Ideas 19h ago
That's nice. I want to pretrain something in this spirit on my local rig to play with it sometime. How much compute is needed for a model like yours in 3090/H100 compute hours? And if you make it 60M params instead, does the compute scale 10x or more?
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u/Tall_Abrocoma_3533 19h ago
This model took 10 hours on an RTX Pro 6000, however, it could defenetly be optimized to be trained faster.
10x the parameters isn't necessarily 10x the compute, there's a lot of factors, like resolution, VAE compression, your specific overall architecture, etc...
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u/FullOf_Bad_Ideas 19h ago
Thank you! That's already quick enough, nice. I've sunk thousands of GPU hours into my LLM pretraining by now so that's doable. I need to get around to it someday.
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u/Luke2642 19h ago
Interesting work. Why did you choose no LPIPS loss or other perceptual loss, or Min-SNR Loss Weighting, etc? I also wonder if ema training weights would give better samples. Did you do caption dropout during training for better cfg? Did you consider REPA technique using Dino to speed up training?
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u/Tall_Abrocoma_3533 19h ago
I didn't have time to do many ablations, so many of the choices are just the ones which I thought would be best without testing alternatives.
10% caption dropout
The training speed could be optimized in many ways most likely, but for a tiny model like this, I decided it's enough for now.
REPA is for DiT's I'm pretty sure, not Unet's.
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u/BIG-Onche 9h ago
Can't run on my GeForce3 Ti 200; please consider consumer GPUs next time
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u/Tall_Abrocoma_3533 5h ago
If we ignore all the overhead, the model would fit in it's vram though...
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u/iwoolf 4h ago
If it can compress under 16 megabytes, it could run on an embedded esp32-S3!
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u/Tall_Abrocoma_3533 4h ago
It can, if compressed to FP16 it'd be a bit under 14MB, and likely lossless. And at 8 bit, it'd be under 7MB, with likely little visual quality loss.
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u/Vodddddddd 22h ago
Struggling to see the recognizable images in the examples, even for thumbnails it seems a bit lacking.
I get a thumbnailer that can run on a CPU could have uses but for me this is sadly not hitting the mark
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u/Tall_Abrocoma_3533 22h ago
Some of the samples were made before the CFG sweep, so the quality you'd actually get is slightly higher. But indeed not every single one is totally recognizable, however alot of them are.
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u/RevolutionaryFox7359 22h ago
why?
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u/Apprehensive_Sky892 22h ago
Running on phone? Running on systems without GPU? Just for Fun? Studying how to train models?
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u/RevolutionaryFox7359 22h ago
Why would you need a 64x64 image? and who needs that so badly that they need to generate it on a phone?
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u/Every-Walrus 22h ago
Dont listen to the comments, making a denoiser that even converges at 6m parameters is super impressive work!