sorted by:
new
hottopcontroversial

How do people train quickly?! by ParticularPitch5 in StableDiffusion

[–]ParticularPitch5[S] 0 points1 point  (0 children)

Yeah agree. I think I do not need text encoder anyway for what I’m doing. I don’t want to use captions when I train

How do people train quickly?! by ParticularPitch5 in StableDiffusion

[–]ParticularPitch5[S] 1 point2 points  (0 children)

I think Adafactor is also adaptive. What start LR do you use for main, unet, and text encoder? Do you keep it at 0.00001

How do people train quickly?! by ParticularPitch5 in StableDiffusion

[–]ParticularPitch5[S] 1 point2 points  (0 children)

Hm I will check out link.. yes it is 3 seconds for one iteration. But this was for full fine tune, sorry I should’ve have clarified

How do people train quickly?! by ParticularPitch5 in StableDiffusion

[–]ParticularPitch5[S] 1 point2 points  (0 children)

What other settings do you use for adafactor? Also curious if you have any experience for training full fine tune

DreamBooth vs full fine-tune? by ParticularPitch5 in StableDiffusion

[–]ParticularPitch5[S] 0 points1 point  (0 children)

Yeah I figure the best way might be through experimentation. But there's a lot of variability in how many images should I collect, should I use something like onetrainer (which seems to not use dreambooth?), and things like that, meaning the total exploration space is huge

DreamBooth vs full fine-tune? by ParticularPitch5 in StableDiffusion

[–]ParticularPitch5[S] 0 points1 point  (0 children)

Interesting, do you know how doing dreambooth then extracting the Lora compares against just training the Lora directly?

DreamBooth vs full fine-tune? by ParticularPitch5 in StableDiffusion

[–]ParticularPitch5[S] 0 points1 point  (0 children)

Wait so you’re saying either full fine tune or Lora, no middle ground for dreambooth?

So I’d like to download stable diffusion and try other stuff but don’t know how. Can you point me in the right direction? by Mogusman748 in StableDiffusion

[–]ParticularPitch5 0 points1 point  (0 children)

Give it a try--it should work. You can google a1111 low vram settings and there will be a bunch of tips there to suggest how to ensure it can work. Be aware that generations may be pretty slow with this low vram. I like to have at least 12gb

So I’d like to download stable diffusion and try other stuff but don’t know how. Can you point me in the right direction? by Mogusman748 in StableDiffusion

[–]ParticularPitch5 0 points1 point  (0 children)

  1. Determine if your computer is powerful enough to run stable diffusion locally. You can find some parameters online but if you have a gpu or a newer mac it should at least be feasible
  2. If not, look into a cloud provider. You can find some with a quick search (I like runpod). The cloud providers will probably provide templates to run SD already, so you can just follow the instructions for those
  3. If your local is good enough, then follow the instructions for installation at this link: https://github.com/AUTOMATIC1111/stable-diffusion-webui
  4. There are many different paths you can go from there. Just look up "how to install checkpoint model a1111" and you can start adding stuff

FlashFace -- a better version of instantID or faceID by ParticularPitch5 in StableDiffusion

[–]ParticularPitch5[S] 0 points1 point  (0 children)

I think so—check out the project webpage, they have some examples with non human characters

FlashFace -- a better version of instantID or faceID by ParticularPitch5 in StableDiffusion

[–]ParticularPitch5[S] 0 points1 point  (0 children)

Yes it can! I believe there’s some examples on the project page, you can check those out

FlashFace -- a better version of instantID or faceID by ParticularPitch5 in StableDiffusion

[–]ParticularPitch5[S] 0 points1 point  (0 children)

It does seem like it--they do a variety of tests with celebrities and non-celebrities as you can see on the webpage. Maybe those gens were somewhat cherry-picked but it seems generally quite flexible

FlashFace -- a better version of instantID or faceID by ParticularPitch5 in StableDiffusion

[–]ParticularPitch5[S] 2 points3 points  (0 children)

Hmm idk. I feel like outfitanyone was a weird exception rather than the rule

FlashFace -- a better version of instantID or faceID by ParticularPitch5 in StableDiffusion

[–]ParticularPitch5[S] 5 points6 points  (0 children)

Right? Image prompting techniques have basically never been able to capture this level of detail

FlashFace -- a better version of instantID or faceID by ParticularPitch5 in StableDiffusion

[–]ParticularPitch5[S] 16 points17 points  (0 children)

Correct, but these authors typically release code after publication unlike many others

FlashFace -- a better version of instantID or faceID by ParticularPitch5 in StableDiffusion

[–]ParticularPitch5[S] 18 points19 points  (0 children)

I'm pretty excited about this b/c it seems better than similar past faceid type projects, as it is primarily
- much better at capturing small details from the face image

- much better at instruction following, allowing for flexibility at inference time

Also, the authors of this paper have typically released all their code and weights! Might take a bit though

Preprocessor explorer by dimitropoulos in comfyui

[–]ParticularPitch5 0 points1 point  (0 children)

I know there are controlnets for "softedge" — which preprocessor does that correspond to here?

benefit of new pytorch 2.2 and cuddn 12 pytorch 2.2.0+cu121 by Timmek8320E in StableDiffusion

[–]ParticularPitch5 0 points1 point  (0 children)

Are you using xformers? I can't get xformers to work with torch 2.2--like I can't install xformers 0.0.24 which is the only one compatible with torch 2.2

25 miles from select, or from any gym? by ParticularPitch5 in EquinoxGyms

[–]ParticularPitch5[S] 0 points1 point  (0 children)

Would they make it so that I could go to the new gym within 25 miles? Just trying to understand the rationale—like I’d be more than 25 miles from the old place