SDXL is the same, if promp following and the architecture is good we can let it learn
SDXL is the same, if promp following and the architecture is good we can let it learn
Ftraining on SDXL was cripped badly
Fi get an error if i try to do stage 2 upscale in supir without doing stage 1 first
Ayou need to upload to stage 1 image
Ayour base image
Fkk
Finteresting, even with an upscale value of 1 (and default settings otherwise/no prompt) putting the image in stage 2 and running stage 2 sharpens and cleans the image up a bit
Ayea
Aand if you smooth it out first, the gun would start looking strange
Fso looks like you can use it to denoise and add detail at same res
![Dazzastrous [4090]](https://cdn.discordapp.com/avatars/871389071686135838/c4a5f4d81d9eeb18d856295d692e2c07.webp?size=40)
Dyeh the metal pops , little extra detail nice one
Fbe canceling my magnific subscription soon then lol
Ai was never realy a fan of magnific. It kept adding details i didnt want haha
Fyes but sometimes thats a good thing, it can repair faces in SDXL renders
Fand for BG characters
Fso the thing you dont like is the only reason to still use it lol
Ayea, but i think if you tamper with the settings of supir, you should be able to do the same
Fye it works better in some images depends on taste
Ai hope supir gets faster in further development. Its currently really slow :/ even on a A6000
Atakes around 10 mins to upscale to 3000x3000
FAdmiral Furkan, do any of your videos deal with multi concept checkpoint training and how to tag those images and whether regularisation images are needed for concepts rather than people
GScripts eror.I can't Running on local URL Please advise me?.I'm a new member. And then started learning the basics. Please give me some advice.
VDo did you see this EMO thing... Looks wild right? It can be the open source alternative of heygen..but better ...examples looks promising...
https://www.reddit.com/r/StableDiffusion/comments/1b25pbk/emo_emote_portrait_alive_is_based_on_sd_15/
https://www.reddit.com/r/StableDiffusion/comments/1b25pbk/emo_emote_portrait_alive_is_based_on_sd_15/
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Fdafuq....
Fit is public?
Fno
VNot as of now..but it it better than heygen..it captures better facial expressions and micro expressions..lip movement and mouth movements..even the eyes as well
VHello doctor, I am using your kohya configuration and A5000 acceleration instructions. The fineturn speed is 1.78s/it. Is this a normal speed? It takes about 5 hours to fine-tune 35 pictures. My goal is to fine-tune a 10k data set. This Time is scary.
@Dr. Furkan Gözükara
@Dr. Furkan GözükaraFcurious what kinda images in the dataset
Vinterior design images
Fwhat are you using to tag?
Fand do you need regulatisation images to train these?
VI also observed that the results were overfitted very early
Vcog
VThe original resolution has reached 1024
Fnot sure i follow?
Twhat about this error:
c:\Supir\SUPIR\venv\lib\site-packages\open_clip\factory.py:213 in create_model │
│ │
│ 210 │ │ │ │ │ f'Pretrained weights ({pretrained}) not found for model {model_name} │
│ 211 │ │ │ │ │ f'Available pretrained tags ({list_pretrained_tags_by_model(model_na │
│ 212 │ │ │ │ logging.warning(error_str) │
│ ❱ 213 │ │ │ │ raise RuntimeError(error_str) │
│ 214 │ │ │ pretrained_loaded = True │
│ 215 │ │ elif has_hf_hub_prefix: │
│ 216 │ │ │ logging.info(f'Loading pretrained {model_name} weights ({pretrained}).') │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
RuntimeError: Pretrained weights (models/open_clip_pytorch_model.bin) not found for model ViT-bigG-14.Available pretrained tags
(['laion2b_s39b_b160k'].
c:\Supir\SUPIR\venv\lib\site-packages\open_clip\factory.py:213 in create_model │
│ │
│ 210 │ │ │ │ │ f'Pretrained weights ({pretrained}) not found for model {model_name} │
│ 211 │ │ │ │ │ f'Available pretrained tags ({list_pretrained_tags_by_model(model_na │
│ 212 │ │ │ │ logging.warning(error_str) │
│ ❱ 213 │ │ │ │ raise RuntimeError(error_str) │
│ 214 │ │ │ pretrained_loaded = True │
│ 215 │ │ elif has_hf_hub_prefix: │
│ 216 │ │ │ logging.info(f'Loading pretrained {model_name} weights ({pretrained}).') │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
RuntimeError: Pretrained weights (models/open_clip_pytorch_model.bin) not found for model ViT-bigG-14.Available pretrained tags
(['laion2b_s39b_b160k'].
VWell, non-native English speaker, you know ha ha
FI figured ha, all good
VIt seems like you are also interested in fineturn instead of dreambooth, right?
Ftbh i dont know what's the advantage of either, i thought dreambooth was for finetuning!
VWell, I'm also in the exploratory stage
5Here for history, congrats @Dr. Furkan Gözükara your post is going virtal on twitter
Vwhich one share the link
D@Dr. Furkan Gözükara i am surprised no application has multi prompts for SDXL, its an amazing function which gives much more control on the images. I Used it on through SD official API . By sending 2 positive prompts and one negative. If anyone seen this function please let me know
Fmulti prompts?
Fyou mean one prompt for first text encoder and another prompt to the second text encoder?
Fis not that powerfull!
Dimport fs from "fs";
const options = {
method: "POST",
headers: {
Accept: "application/json",
"content-type": "application/json",
Authorization: "Bearer YOUR_API_KEY"
},
body: JSON.stringify({
samples: 1,
height: 1024,
width: 1024,
steps: 40,
cfg_scale: 5,
textprompts: [
{
"text": "A painting of a cat",
"weight": 1
},
{
"text": "a dog barking",
"weight": 1
},
{
"text": "logo, ",
"weight": -1
}
],
})
};
const response = await fetch(
"https://api.stability.ai/v1/generation/stable-diffusion-xl-1024-v1-0/text-to-image",
options
)
if (!response.ok) {
throw new Error(
}
const responseJSON = await response.json()
responseJSON.artifacts.forEach((image, index) => {
fs.writeFileSync(
`./out/txt2img${image.seed}.png`,
Buffer.from(image.base64, 'base64')
)
});
const options = {
method: "POST",
headers: {
Accept: "application/json",
"content-type": "application/json",
Authorization: "Bearer YOUR_API_KEY"
},
body: JSON.stringify({
samples: 1,
height: 1024,
width: 1024,
steps: 40,
cfg_scale: 5,
textprompts: [
{
"text": "A painting of a cat",
"weight": 1
},
{
"text": "a dog barking",
"weight": 1
},
{
"text": "logo, ",
"weight": -1
}
],
})
};
const response = await fetch(
"https://api.stability.ai/v1/generation/stable-diffusion-xl-1024-v1-0/text-to-image",
options
)
if (!response.ok) {
throw new Error(
Non-200 response: ${await response.text()})}
const responseJSON = await response.json()
responseJSON.artifacts.forEach((image, index) => {
fs.writeFileSync(
`./out/txt2img${image.seed}.png`,
Buffer.from(image.base64, 'base64')
)
});
Fthat doesn't answer
Dboth prompts are flowing through both encoders