lmao

Yep basically, maybe even one step more abstract.

e.g. this picture i can imagine instances where i might want to search for works with similar:
- oil painting/moody style
- ethereal/cosmic/angelic dreams style
- mixed media mashups

How to select/change embedding to reflect those aspects in query

By that i mean, in the same image there can be different aspects of it that draws me in or that i want to find more instances of/commission. For most embedding and searching its always the same embedding no matter the intent/aspect of focus.

guess thats why text input exists, to be able to steer

I would. I really like the idea of being able to find artists based on a vibe i want/mood board. A lot of times i give up bc there is no good way to express what i want.

The crux i think would be, can this let me change how it queries the embedding space on what features/vibes of the images i want

agreed

my reason for the small model route is, it takes care of any json oddities as well, without constraining the output diversity/quality of the big model while also getting parseable json more reliably than just having the model freestyle it

1) plan like usual with big intelligent model
2) format it into json format with guided generation on a small 1B model finetuned to put outputs into JSON, so not (nearly as)much reasoning required

Same, just got here, hopping following lists to build back my old network. surprisingly more that i thought already here

I did change pfp and overall vibes though 🤐