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It seems to be empty: https://github.com/lucidrains/DALLE2-pytorch/blob/main/dalle...
If this were a complete project what kind of compute resources would one need to run DALL-E 2? (In inference or train)
Google Cloud TPUs would be a good start.
hm.. I wonder which clip model they'll use. A big part of what makes DALLE-2 so good is the unreleased huge clip model. To train the diffusion prior they may need to first replicate this clip model.
I hope they find latent diffusion works for this, without it this will probably be too expensive for private parties to train on big collections.
Isn't the VQ-VAE/dVAE generator approach in the DALL-E models quite a bit cheaper computationally than latent diffusion models?
My understanding was that diffusion models were quite a bit more expensive, but yielded richer latent distributions and better images (for some definition of better).
My understanding was that diffusion models were quite a bit more expensive, but yielded richer latent distributions and better images (for some definition of better).