Software Engineering Courses (SECourses)•15mo ago

Hi everyone, I'm not sure which chat to post this in, but can someone explain to me how to properly

Hi everyone, I'm not sure which chat to post this in, but can someone explain to me how to properly use wildcards in swarm ui? I have a weird issue with. I have a wildcard file with 10 lines for shirt color in it but when I try to generate 10 images, it will choose one color from those 10 and generate 10 images with that color

IIWishIWereGood Hi everyone, I'm not sure which chat to post this in, but can someone explain to...

Furkan Gözükara SECourses•10/18/24, 2:11 PM

swarm internalk

Furkan Gözükara SECourses•10/18/24, 2:11 PM

check those parameters

Furkan Gözükara SECourses•10/18/24, 2:11 PM

IWishIWereGoodOP•10/18/24, 2:15 PM

Hmmm I will look for it

IWishIWereGoodOP•10/18/24, 2:15 PM

Thank you

FFurkan Gözükara SECourses you can convert model to fp8

Nick44•10/18/24, 5:04 PM

that worked thanks

dsienra•10/18/24, 5:08 PM

Update https://huggingface.co/nyanko7/flux-dev-de-distill training. LR 0.0001 vs 0.00003, much better results with lower LR, may be a little undertrained. Less class bleeding, but the class on training captions seems to decrease resemblance in non de-destilled models, I think that adding the class is a problem, I will remove the class from the captions I think that it will eliminate class bleeding completely. You can always add the class on inference if you wish, but removing it from the captions will protect the class from bleeding. flux-dev-de-distill learns very different than regular flux-dev it learns the caption tokens much better. I will update tomorrow-

nyanko7/flux-dev-de-distill · Hugging Face

Ddsienra https://huggingface.co/nyanko7/flux-dev-de-distill Unet LR 0.0001 vs 0.00003 the...

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𝗡𝗶𝘁𝗶𝗻 𝗣𝗮𝗿𝗲𝘃𝗮•10/18/24, 5:11 PM

Can you share some images from your trainings comparing the normal dev vs de distilled one?

�𝗡𝗶𝘁𝗶𝗻 𝗣𝗮𝗿𝗲𝘃𝗮 Can you share some images from your trainings comparing the normal dev vs de dis...

dsienra•10/18/24, 5:18 PM

Not from my training because is from family and friends I can't share, The quality on inference is identical, the advantage is that you can train multiple people on the same lora, I trained 11 people in one lora. I'm perfecting the technique to avoid concept bleeding completely not only between the people I'm training that is fixed, but fix the class bleeding to a minimum too.

Ddsienra Not from my training because is from family and friends I can't share, The quali...

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𝗡𝗶𝘁𝗶𝗻 𝗣𝗮𝗿𝗲𝘃𝗮•10/18/24, 5:19 PM

Okay thanks for all your updates here

�𝗡𝗶𝘁𝗶𝗻 𝗣𝗮𝗿𝗲𝘃𝗮 Okay thanks for all your updates here

dsienra•10/18/24, 5:20 PM

you welcome.

Ddsienra Update https://huggingface.co/nyanko7/flux-dev-de-distill training. LR 0.0001 vs...

druhl•10/18/24, 5:35 PM

My training on de_distill just completed (dreambooth on a single person). The ability to control cfg helps you create a far greater image than CFG 1 @ flux_dev. The results are absolutely amazing. You can create more noisier (and less plasticky images) which seem more realistic. The ability to use negative prompts and the prompt adherence is very, very good.
Only downside is: Time! It sure takes helluva lot of time to generate (Minimum Steps 70 imo), and there are extra inference parameters to deal with.

druhl•10/18/24, 5:36 PM

My training on dev2pro with the same parameters (same concept) would also be completed soon.