and do you need regulatisation images to train these?
and 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
Fbut yeah, probably one prompt for each text encoder
Fthat's not possible. it's just a concatenation then
Fit's like sending "A painting of a cat a dog barking"
Dyou can add more than 4 prompts, control the weight for each 1 seperatly.
Fanyway, all apps have that
Fit's called prompt weighting
Dhttps://platform.stability.ai/sandbox/multi-prompting have a look here i think you will be able to generate free images
F(A painting of a cat:0.8) (a dog barking:1.4)
Fthat's how you do it in a1111
Fthere is also other types of blending
FFFThe syntax is ("prompt part 1", "prompt part 2").and(). You can have more than one part, and you can also weight them, eg ("a man eating an apple", "sitting on the roof of a car", "high quality, trending on artstation, 8K UHD").and(1, 0.5, 0.5)
FF
F@Dr. Furkan Gözükara I would like to know what your secret is to make videos with so much work and also having time to make those scripts and posts for Patreon 
VDoc has superpowers. Don't you know..
Skebab power
Fkebab indeed has powers. you order it and save 30 mins cooking + 10 mins cleaning
Dhis day is 48 hours 
Vcomfy ui allows multiprompting i think.... you can make custom nodes in there .. so it should be possible??
Di am trying to do the node but am not good in coding, trying to reach the target
Vi was playing around in comfy ui.. it indded is better than once you master it
DI tested it out, the results are not similar.
Vi can share json file for workflow
Dusing all available LLama to code xD !
D
Vlearning curve is more steep but once you master it comfyui has much better overall control over the final image
Di agree, i have made complex models but based on available node, i just started trying to code it
Vwhy are you coding it? isnt it drag and drop
Fin comfyUI what happens if you attach 2 prompt nodes to the text encoder ?