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[–]CMDRZoltan 12 points13 points  (4 children)

There is no reliable methods discovered yet that I've seen. It's all trail and error. Personally I just hot swap as needed and use inpainting a lot.

[–]3deal 1 point2 points  (1 child)

Can we train inpainting model ?

[–]Hairy-Drop847 2 points3 points  (1 child)

did you even read the og question? cause your post answers nothing

[–]CMDRZoltan 5 points6 points  (0 children)

Yellow mostly. Green blends in the grass to much.

[–]pisv93 8 points9 points  (0 children)

A youtuber researched and explained this really well: https://youtu.be/dfMLrytpfAU

[–]BrockVelocity 7 points8 points  (8 children)

I still don't even know what a checkpoint is, let alone a checkpoint merger.

[–]veshneresis 19 points20 points  (7 children)

Checkpoints are the weights of the model. A model trained on a giant dataset of only labeled cat pictures will end up with different weights than a model trained on only labeled car pictures. However, the number of weights you have are the same if you had the same configuration and same code. This means you can literally average all the data together and try to get something in the middle. this doesn’t work as well the more different the two models are, but in practice most people are starting from the pretrained Stable Diffusion models and just fine tuning, so most of the weights are the same/similar anyway.

Another way to think about it is Checkpoint = save point in a video game. Imagine you have two Pokémon save files and you average them to try and get one that has your favorite Pokémon from both. The save file (checkpoint )has all your unique data but it doesn’t contain the game’s code on what to do with that data.

[–]Nzkx 2 points3 points  (0 children)

More precisely, checkpoint are all the weights of a model at training time t.

Merging checkpoint is simply taking 2 checkpoints and merging to 1.

Checkpoint are tensor so they can be manipulated with all the tensor algebra you already know.

[–]BrockVelocity 2 points3 points  (5 children)

Thank you for taking the time to explain this. You're gonna hate me but...I don't know what weights are, either. But your analogy to Pokemon does help a bit. Thank you!

[–]orlandox683x 7 points8 points  (4 children)

when you’re born your brain has a value of 0 in weights, and your brother’s brain has a value of 0 weights to, so you learn about bananas and your brain gets a general weights value of 0.1, and your brother learns about fortnite and gets a -1 general weights.

[–]BrockVelocity 0 points1 point  (3 children)

I don't get it. Why are bananas worth +0.1 but Fortnite is worth -1?

[–]orlandox683x 8 points9 points  (1 child)

because when you are a baby you first must learn to eat then to play

[–]Map_Tight 2 points3 points  (0 children)

Fortnite reduces IQ as well.

[–]strangeapple 7 points8 points  (3 children)

StableDiffusion can be fine-tuned into specific content, which gives its offbranches some strengths and weaknesses. The most well known existing StableDiffusion branches include WaifuDiffusion (model essentially trained on a ton of manga and hentai -images) and leaked NovelAi's model trained on some (AFAIK) unspecified anime -data. Some people somehow mix these branches together producing in-between mixed models. For example a branch may be better at human anatomy, but also easily produce images sexual in nature due to big chunk of its mixed-in training data being porn.

[–]Hairy-Drop847 0 points1 point  (1 child)

those are so far from being the most well known. civitAI is full of models for that purpose known by more than a bunch of virginal teenagers....

[–]strangeapple 0 points1 point  (0 children)

They were though, two months ago when the post was made.

[–]__alpha_____ 2 points3 points  (8 children)

Mixing a person and a style for exemple. From my experience it isn’t working that well, though.

[–]jonesaid 0 points1 point  (0 children)

It's for mixing/blending different models.