Latent text-to-image diffusion model
https://github.com/CompVis/stable-diffusion
Stable Diffusion is a latent text-to-image diffusion model. Thanks to a generous compute donation from Stability AI and support from LAION, we were able to train a Latent Diffusion Model on 512x512 images from a subset of the LAION-5B database. Similar to Google's Imagen, this model uses a frozen CLIP ViT-L/14 text encoder to condition the model on text prompts. With its 860M UNet and 123M text encoder, the model is relatively lightweight and runs on a GPU with at least 10GB VRAM. See this section below and the model card.
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Source Files
Filename | Size | Changed |
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_service | 0000000576 576 Bytes | |
_servicedata | 0000000245 245 Bytes | |
python-stable-diffusion.changes | 0000000396 396 Bytes | |
python-stable-diffusion.spec | 0000001996 1.95 KB | |
stable-diffusion-0.0.1+git.20221116.obscpio | 0050539533 48.2 MB | |
stable-diffusion.obsinfo | 0000000118 118 Bytes |
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