Search results
Discover amazing ML apps made by the community. stable-diffusion. like 10.5k
- Hugging Face – The AI community building the future.
Explore the amazing text-to-image generation with Stable...
- stabilityai/stable-diffusion-3-medium · Hugging Face
Stable Diffusion 3 Medium is a Multimodal Diffusion...
- stabilityai/stable-diffusion-2 · Hugging Face
This stable-diffusion-2 model is resumed from...
- The Stable Diffusion Guide - Hugging Face
Since its public release the community has done an...
- stabilityai/stable-diffusion-xl-base-1.0 · Hugging Face
Developed by: Stability AI; Model type: Diffusion-based...
- Introduction to Stable Diffusion - Hugging Face
This chapter introduces the building blocks of Stable...
- Hugging Face – The AI community building the future.
12 iun. 2024 · 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.
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.
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.
New stable diffusion model (Stable Diffusion 2.1-v, Hugging Face) at 768x768 resolution and (Stable Diffusion 2.1-base, HuggingFace) at 512x512 resolution, both based on the same number of parameters and architecture as 2.0 and fine-tuned on 2.0, on a less restrictive NSFW filtering of the LAION-5B dataset.
Developed by: Stability AI; Model type: Diffusion-based text-to-image generative model; License: CreativeML Open RAIL++-M License; Model Description: This is a model that can be used to generate and modify images based on text prompts. It is a Latent Diffusion Model that uses two fixed, pretrained text encoders (OpenCLIP-ViT/G and CLIP-ViT/L).
This chapter introduces the building blocks of Stable Diffusion which is a generative artificial intelligence (generative AI) model that produces unique photorealistic images from text and image prompts.
