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ruDALL-E finetuned on Damien Hirst vitrinespic.twitter.com/qXg6PqnyBR
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ruDALL-E finetuned on Modigliani portraitspic.twitter.com/bLONrWZlIO
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Some more Hoppers, this time upscaled with https://github.com/CompVis/latent-diffusion …pic.twitter.com/F48XGalENd
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Oh god so many new text-to-image models but so little time
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Michael Friesen Retweeted
My 602M parameter CLIP conditioned diffusion model trained on Conceptual 12M is out at https://github.com/crowsonkb/v-diffusion-pytorch …! It can generate images matching the prompt quickly using its CLIP conditioning, but still requires CLIP guidance for best results.pic.twitter.com/bQjfTBuIO3
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ruDALL-E finetuned on abstract paintingspic.twitter.com/lGraPZcVsr
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ruDALL-E finetuned on Francisco Goya's Black Paintingspic.twitter.com/IWEJZ5hMGl
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ruDALL-E finetuned on a single image; the cover of In the Aeroplane Over the Sea (center)pic.twitter.com/JptQb5Ph8H
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ruDALL-E finetuned on Wikihow illustrationspic.twitter.com/1VTaNBuE80
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If you want to finetune your own very cool and sexy ruDALL-E, check out this here Kaggle notebook for an example of how to do so:https://www.kaggle.com/shonenkov/emojich-rudall-e …
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