latent-diffusion

There are a lot but the one implemented as LDSR in most stable guis is this one. https://github.com/CompVis/latent-diffusion upscale wiki is really the place to explore everything image scaling: https://upscale.wiki/

The model was initially released in August 22, 2022, and everything from the GitHub organization that hosted the code, to the actual licenses being around and all the communication made it very clear that there was a bunch of groups involved with the model; Runway, CompVis, and Stability AI Then Stability AI raised money from investors in October 2022. Are you really telling me these investors didn't even do any sort of due diligence (not even "barely any" but literally any at all), didn't realized that Stable Diffusion was the work of many, and checked the license of the model and code? That's a bit far fetched, to be honest. Supposedly, this "leaked pitch deck" is supposed to show us that they lied to investors, but where is the pitch deck itself? Seemingly, only one of the slides is in the article, how could anyone reach any sort of co

The "retrieval based model" refers to https://github.com/CompVis/latent-diffusion#retrieval-augmen..., which uses ScaNN to train a knn embedding searcher.

The latent-diffusion[1] I've got running at home frequently generates stock image watermarks (e.g. "The London Skyline at night in the style of Carboni"[2], images 1, 2, and 6) [1] https://github.com/CompVis/latent-diffusion [2] https://imgur.com/a/8tOI9QU

FYI if you only have a limited amount of compute, latent diffusion models will converge much faster. https://github.com/CompVis/latent-diffusion

I don't have any of the DALL-Es but I do have a couple from github [1], [2] which gave these outputs[3] [1] https://github.com/nerdyrodent/VQGAN-CLIP [2] https://github.com/CompVis/latent-diffusion [3] https://imgur.com/a/DjQYLUz

Don't have access to Dall-E 2 or Imagen but I do have [1] and [2] locally and they produced [3] with that prompt. [1] https://github.com/nerdyrodent/VQGAN-CLIP.git [2] https://github.com/CompVis/latent-diffusion.git [3] https://imgur.com/a/dCPt35K

The latent-diffusion[1] one I've been playing with is not terrible at drawing legible text but generally awful at actually drawing the text you want (cf. [2]) (or drawing text when you don't want any.) [1] https://github.com/CompVis/latent-diffusion.git [2] https://imgur.com/a/Sl8YVD5

latent diffusion model trained on LAION-400M https://github.com/CompVis/latent-diffusion

An older, but similar and still impressive alternative is available here: https://github.com/CompVis/latent-diffusion If you have a decent amount of VRAM, you can use it to start generating images with their pre-trained models. They're nowhere near as impressive as DALL-E 2, but they're still pretty damn cool. I don't know what the exact memory requirements are, but I've gotten it to run on a 1080 TI with 11gb. EDIT: I also tried a 980 with 4GB of RAM a while back, but that failed...so you probably need more than that.

Hi, I'm the author of this post. I hope you all enjoy it! I researched and wrote this back in January, and although the main ideas are still relevant, the landscape of AI art generation has changed quite a bit in just three months. Here are some important new developments: - DALL-E 2: https://openai.com/dall-e-2/ - Midjourney: https://twitter.com/midjourney - Laion 5B dataset: https://laion.ai/laion-5b-a-new-era-of-open-large-scale-mult... - Compvis latent diffusion: https://github.com/CompVis/latent-diffusion Since the field is moving so quickly, this newsletter is a good way to try to stay on top of things: https://multimodal.art/news Also I went on Yannic Kilcher's podcast to talk about this! https://www.youtube.com/watch?v=DdkenV-ZdJU&ab_channel=Yanni...

latent difussion models (see: https://github.com/CompVis/latent-diffusion). we also use our own open-source library https://github.com/thegeniverse/geniverse

This isn’t true, the quality of images generated by DALL-E are really good, but they are an incremental improvement and based on a long chain of prior work. See e.g. https://github.com/CompVis/latent-diffusion