According to their paper ([2307.01952] SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis), it’s just that instead of using 1 big encoder, they use 2 and concatenate the embedding vector. (CLIP ViT-L & OpenCLIP ViT-bigG)
Specifically,
we use OpenCLIP ViT-bigG [19] in combination with CLIP ViT-L [34], where we concatenate the
penultimate text encoder outputs along the channel-axis
It’s not clear if the training was done using different prompts for each encoder, but the HF docs says that even if the default usage is to use the same prompt for both encoders, you can use two different prompts.
I suppose a natural intuition would be use one text encoder for the semantic information, and the other encoder for all the style information, but I have no idea if one encoder is more specialized on style than the other or vice verse, or even if it’s a good idea to have two different prompts.
Did someone made some tests on what to expect on these double encoder use variations ?