Huh, I'm trying it now and the results seem so weak compared to any other model I've seen since dall-e.

Hmm that’s true for me too. Not sure if it is due to resource constraint. I had a picture of a car in indoor parking lot with walls and pillars. When I prompted “Color the car blue” the whole image was drenched in a tint of blue. Similarly when prompted “make a hummingbird hover” … the hummingbirds were a patch of shiny colors with an shape that sort of looked like an hummingbird but not like a real one.

Try "turn the car blue"

Does dalle do prompt based photo edits now?

But yeah sometimes it doesn't follow directions well. I haven't noticed a pattern yet for why that is.

How would I upgrade to 2.1 if running locally?

If you're wanting to use Stable Diffusion 2.1 with imaginairy you just specify the model with `--model SD-2.1` when running the `aimg imagine` command.

Sorry for the offtopicness but could you please email me at [email protected]? (I have an idea/possibility for you. Nothing that couldn't be posted here in principle but I'd rather not take the thread off topic.)

This was an uncanny comment, somehow.

Hope ya'll brainstorming session is fruitful.

Sorry for the uncanning! My thought was simply to connect the OP with a YC partner in case they wanted to explore doing this as a startup.

I send such emails all the time but on semi-rare occasions have to resort to offtopic pleas like the GP.

I hope that helps clear things up!

It does, thank you!

EDIT - it's free of charge: https://research.google.com/colaboratory/faq.html

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First time I've used "colab" - looks great. Out of interest, who pays for the compute used by this?

Is it freely offerred by Google? Or is it charged to my Google API account when I use it? Or your account? It wasn't clear in the UI.

Freely offered by Google. They offer a subscription model if you want to run your collab notebooks on a beefier machine.

I could not get the first cell to run.

ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts. tensorflow 2.9.2 requires protobuf<3.20,>=3.9.2, but you have protobuf 3.20.3 which is incompatible. tensorboard 2.9.1 requires protobuf<3.20,>=3.9.2, but you have protobuf 3.20.3 which is incompatible.

I believe you can just ignore that error. The cell ran.