whats the easiest way to search the patreon, it seems like when you type anything it can be one of m
whats the easiest way to search the patreon, it seems like when you type anything it can be one of many posts
FGitHub
Stable Diffusion, SDXL, LoRA Training, DreamBooth Training, Automatic1111 Web UI, DeepFake, Deep Fakes, TTS, Animation, Text To Video, Tutorials, Guides, Lectures, Courses, ComfyUI, Google Colab, R...
Fyou dont need it for training a person usually
VIs the workflow for training an object or a concept basically the same? Captioning? A bunch of images? How many?
Also, what kind of thing are you training for a client - any interesting thoughts about how to get that kind of work - good potential industries for clients?
Also, what kind of thing are you training for a client - any interesting thoughts about how to get that kind of work - good potential industries for clients?
![Digital [Starburst]](https://cdn.discordapp.com/avatars/220961909447458817/8ecbbb3132fc6e44312f3d6d2ae3df69.webp?size=40)
DI think this is the second class in your Udemy course on SD
Fi am trying to train a comic style certain
![Digital [Starburst]](https://cdn.discordapp.com/avatars/220961909447458817/8ecbbb3132fc6e44312f3d6d2ae3df69.webp?size=16)
Fyes accurate
Fcaptioning effect is experimental
Fbefore going to sleep started this
Fwith llava captions
F
DPlease help with kaggle error. Dreambooth training ends with error
Fshow the error here. i got to go though. private message me
Falso use latest notebook
Fand follow this video
FYouTubeSECourses
Master Stable Diffusion XL Training on Kaggle for Free! Welcome to this comprehensive tutorial where I'll be guiding you through the exciting world of setting up and training Stable Diffusion XL (SDXL) with Kohya on a free Kaggle account. This video is your one-stop resource for learning everything from initiating a Kaggle session with dual ...
Master Stable Diffusion XL Training on Kaggle for Free! Welcome to this comprehensive tutorial where I'll be guiding you through the exciting world of setting up and training Stable Diffusion XL (SDXL) with Kohya on a free Kaggle account. This video is your one-stop resource for learning everything from initiating a Kaggle session with dual ...DThis
Fit doesnt tell teh reason
Fstart from beginning
Fwatch tutorial
DGive me a sec
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Dusing latest only : kohya-sdxl-lora-training-on-a-free-kaggle-notebook_v12.ipynb
Dstarted fresh.. caching going on.
D
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Dok there was slight variation of size of my training images , some were 1024 and few were 512.. will rectify and try it again..
GHas anyone played with stable-fast yet? I'm getting decent results in SDXL (crap with 1.5) and it's 2x as fast as a1111/sd.next (sd.next claims it is in their latest build but I only get results when I gen using python scripts)
Nhi everyone, I have a question about my xl controlnet models. for some reason even when I updated them from the patreon file in my runpod, it's still not working.
N
Nit shows it in the preview, but it's not showing in my generated image
Gthat is an SD1.5 model .. it will break control net
Gneed the XL models
Gor if you have them already hit the down arrow on models and choose an XL compatible one
N
NI send the wrong photo sry, it's not working with xl controlnet models
EYes, I'm running a 4090 at the moment. I'm just wondering which version of Dreambooth I should use in terms of the ones listed here https://github.com/d8ahazard/sd_dreambooth_extension/tags , because it seems like the version I got from the "extensions" tab is just not working properly, or I have something set very wrong & nothing is fixing it for some reason.
I mentioned before, when I first watched your original Tutorial on training LoRA through Dreambooth, my Dreambooth looked the same as yours & everything was decent enough, but then my SD broke when I was trying to get TensorRT working the first time, so I had to reinstall it from scratch, and since then, my Dreambooth looks very different from the one in the tutorial, so I'm not sure if I'm missing a setting, have something wrong, or what the issue is.
I've tried training the same face off as many as 60 & as few as 25 images, with quite a few different settings ranges (I've literally tried to train this face 10 times now lol), and it keeps coming up as barely any different than if I put the person's name in with no LoRA loaded, in terms of how they look, on a given Checkpoint.
I mentioned before, when I first watched your original Tutorial on training LoRA through Dreambooth, my Dreambooth looked the same as yours & everything was decent enough, but then my SD broke when I was trying to get TensorRT working the first time, so I had to reinstall it from scratch, and since then, my Dreambooth looks very different from the one in the tutorial, so I'm not sure if I'm missing a setting, have something wrong, or what the issue is.
I've tried training the same face off as many as 60 & as few as 25 images, with quite a few different settings ranges (I've literally tried to train this face 10 times now lol), and it keeps coming up as barely any different than if I put the person's name in with no LoRA loaded, in terms of how they look, on a given Checkpoint.
GitHub
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Edepending on how hot you're getting, and what GPU we're talking about, it should be fine. I cranked my 4090 at one point when rendering batches of 4x4, and it was actually getting warm enough to thermally throttle the clocks slightly, but that was with a +150 core or so offset, with the voltage maxed & the power slider maxed, and that's on an air cooled card in a well ventilated case, the GPU Hotspot in HWInfo was showing 87.6C 
it was kinda warm in here since it's winter, but yeah. If you're not overclocking and you have a well ventilated case, I would say don't worry about it.
You can also try Undervolting, because rendering in SD uses VRAM more than the Core, so undervolting/downclocking your core a bit will actually save a lot of heat by lowering your power draw. I've been running my 4090 @ 2600MHz core with 900mV & the difference in render time between that & stock is less than 3 seconds on a 16-image batch - but that runs literally 10C cooler on the core & draws ~120W less power while rendering.
Quoted the wrong post but that was in reference to you asking about liquid cooling your GPU.
it was kinda warm in here since it's winter, but yeah. If you're not overclocking and you have a well ventilated case, I would say don't worry about it. You can also try Undervolting, because rendering in SD uses VRAM more than the Core, so undervolting/downclocking your core a bit will actually save a lot of heat by lowering your power draw. I've been running my 4090 @ 2600MHz core with 900mV & the difference in render time between that & stock is less than 3 seconds on a 16-image batch - but that runs literally 10C cooler on the core & draws ~120W less power while rendering.
Quoted the wrong post but that was in reference to you asking about liquid cooling your GPU.
NI have used the CN py from patreon to update:
python CND_runpod.py
still having issues
python CND_runpod.py
still having issues
Nthis is my extension tab:
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Dfor time being will train new image batch with lora. Last time there were too many repeating images which made lora inherit certain aspect of dress/color into it and was making output with repative features of the images
Fjust run cell again
Fload and hit again
Fit will cache the remaining images
Fwhat(): [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=3, OpType=ALLREDUCE, Timeout(ms)=1800000) ran for 1802130 milliseconds before timing out.
Fcaching taking too long thus failing
For reduce repeating count
Flike half it and double the epoch
Fhi you need to show cmd output
Fdid you kill previous instance and started yourself?