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Developed by gligen
Stable Diffusion is a latent text-to-image diffusion model capable of generating realistic images from arbitrary text inputs.
Downloads 130
Release Time : 3/11/2023

Model Overview

A diffusion-based text-to-image generation model utilizing latent diffusion model architecture, supporting high-quality image generation from text descriptions.

Model Features

High-Quality Image Generation
Capable of generating high-resolution (512x512) realistic images from text inputs
Classifier-Free Guidance Sampling
Utilizes 10% text condition dropout optimization to enhance generation quality
Memory Optimization
Supports attention slicing technology, can run on GPUs with less than 4GB VRAM
Multi-Platform Support
Supports PyTorch and JAX/Flax frameworks, can run on GPU/TPU

Model Capabilities

Text-to-Image Generation
Art Creation
Design Assistance
Creative Visualization

Use Cases

Art Creation
Concept Art Generation
Quickly generate concept art images from text descriptions
Can be used for pre-production concept design in games, films, etc.
Stylized Image Creation
Generate unique images by combining different artistic style prompts
Such as Disney style, cyberpunk style, etc.
Education & Research
Generative Model Research
Explore the limitations and possibilities of generative models
For academic research and experiments
Creative Tool Development
Develop creative assistance tools based on the model
Such as design assistance applications, art creation tools, etc.
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