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Stable Diffusion 2-1 - a Hugging Face Space by stabilityai. Spaces. stabilityai. /. stable-diffusion. like. 10.6k. Running on CPU Upgrade. Discover amazing ML apps made by the community.
Since its public release the community has done an incredible job at working together to make the stable diffusion checkpoints faster, more memory efficient, and more performant. 🧨 Diffusers offers a simple API to run stable diffusion with all memory, computing, and quality improvements.
Jun 12, 2024 · Stable Diffusion 3 Medium Model Stable Diffusion 3 Medium is a Multimodal Diffusion Transformer (MMDiT) text-to-image model that features greatly improved performance in image quality, typography, complex prompt understanding, and resource-efficiency. For more technical details, please refer to the Research paper.
This stable-diffusion-2 model is resumed from stable-diffusion-2-base (512-base-ema.ckpt) and trained for 150k steps using a v-objective on the same dataset. Resumed for another 140k steps on 768x768 images.
This stable-diffusion-2-1 model is fine-tuned from stable-diffusion-2 (768-v-ema.ckpt) with an additional 55k steps on the same dataset (with punsafe=0.1), and then fine-tuned for another 155k extra steps with punsafe=0.98.
Stable Diffusion is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input. This model card gives an overview of all available model checkpoints. For more in-detail model cards, please have a look at the model repositories listed under Model Access.
The Stable-Diffusion-v1-4 checkpoint was initialized with the weights of the Stable-Diffusion-v1-2 checkpoint and subsequently fine-tuned on 225k steps at resolution 512x512 on "laion-aesthetics v2 5+" and 10% dropping of the text-conditioning to improve classifier-free guidance sampling.
Aug 22, 2022 · LAION-5B is the largest, freely accessible multi-modal dataset that currently exists. In this post, we want to show how to use Stable Diffusion with the 🧨 Diffusers library, explain how the model works and finally dive a bit deeper into how diffusers allows one to customize the image generation pipeline.
Tiny AutoEncoder for Stable Diffusion 3. Tiny AutoEncoder for Stable Diffusion (TAESD3) is a tiny distilled version of Stable Diffusion 3’s VAE by Ollin Boer Bohan that can decode StableDiffusion3Pipeline latents almost instantly. To use with Stable Diffusion 3:
Dec 1, 2022 · Models. We’re on a journey to advance and democratize artificial intelligence through open source and open science.
