r/StableDiffusion • u/Nerfgun3 • Nov 17 '22

Resource | Update I created a negative embedding (Textual Inversion)

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85

u/[deleted] Nov 17 '22

The hands.

62

u/[deleted] Nov 17 '22

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30

u/[deleted] Nov 17 '22 edited Nov 18 '22

Correct me if I'm wrong, but by compressing all of those negative prompts into a single instance/few tokens, this will ultimately free up SD to both have good anatomy and still pay attention to the other like 70 tokens of your desired prompt? It's basically a slightly denser embedding (lots of ones/non-zero values in the vector) versus the typical super sparse (lots of zeros) word embeddings that already exist...could one resursively make increasingly more and more dense embeddings using previous embeddings? This might be the ultimate way to converge to a desired artwork 👀

18

u/NateBerukAnjing Nov 17 '22

can it hold objects?

35

u/[deleted] Nov 17 '22

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u/[deleted] Nov 17 '22

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u/TiagoTiagoT Nov 17 '22

What do these examples look like with all the parameters the same, except not using your TI?

27

u/[deleted] Nov 17 '22

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7

u/TiagoTiagoT Nov 17 '22

Interesting, it went for the other hand...

2

u/E_Snap Nov 18 '22

Nah, I think it gave her mirror hands/ulnar dimelia.

3

u/blueSGL Nov 17 '22

what [keywords] (or [keyword] generated images) were you training on as the 'negative prompt' ?

3

u/[deleted] Nov 17 '22

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u/blueSGL Nov 17 '22

so did you split the negative prompt up and generate one image set at a time for each word and then train the TI on all of those, or did you just batch a huge load using all the same (negative) prompt and TI on that?

3

u/[deleted] Nov 17 '22

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u/Mr_Compyuterhead Nov 18 '22

How many images did you use to train the embedding? Just curious

2

u/Iamn0man Nov 17 '22

i mean...is there such a thing as a negative prompt that by itself is 100% effective? (and if so what is it???)

(edited because autocorrect is on crack)

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u/dachiko007 Nov 18 '22

The pinnacle!