Training takes lots of time so sharing your best generations makes it much easier for me!
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FAQ
Comments (14)
Wtf is this style XDD, its too specific
Stevencarson. Worked out pretty well
@klikkeri1 noted with thanks, hope the suits can be isolated and transposed in other style
3.0 should have better positions.
I used dim 1 and alpha 0.1
Wow great to know that you can use super low dim and get those results, f*k 300Mb loras
@_1_ Most of people are too lazy to do some basic image normalization and removing useless tags. lol
I don't blame them tho. When I started creating hypernetworks and loras 1 year ago, I didn't care manipulating tags or images. Just removing batches of bad images from large datasets.
Recently I got interested in data manipulation because of probabilistic programming
@klikkeri1 what's normalization in this case?
@_1_ I use winsorization/winsorizing. I assume there is no important information in extreme values/colors.
@klikkeri1 Ok, very interesting - and did you find it improves outputs? Need to try it for my XL loras
@_1_ Not sure because if picture looks weird after normalization, I just delete it from the dataset.
@klikkeri1 what tool are you using for normalization? thx
@_1_ @_1_ I created a script with Julia language using Images.jl
@klikkeri1 Hi, could be possible know (in a general way) how do you do the normalization (winsorization/winsorizing) process? I would like (try) recreate it with python.
@Konoko There is so many different ways. Use ChatGPT to assist you. First try open an image with Python, then try saving copy of that image, then try winsorization.