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Stable Diffusion 1.5

Developed by Jiali
A latent diffusion model for text-to-image generation that can create realistic images from arbitrary text inputs
Downloads 17.12k
Release Time : 8/30/2024

Model Overview

Stable Diffusion is a latent text-to-image diffusion model that utilizes a latent diffusion model architecture and CLIP ViT-L/14 text encoder, supporting high-quality image generation through text prompts.

Model Features

High-Quality Image Generation
Capable of generating high-resolution (512x512) realistic images based on text prompts
Classifier-Free Guidance Sampling
Optimized with 10% text condition dropout to enhance generation quality
Commercial-Friendly License
Allows commercial use or redistribution of model weights as a service
Multi-Framework Support
Supports usage through Diffusers library or original GitHub repository

Model Capabilities

Text-to-Image Generation
Artistic Creation
Design Assistance
Educational Tool Development

Use Cases

Artistic Creation
Concept Art Generation
Quickly generate concept art images based on textual descriptions
Can be used for pre-visualization in industries like gaming and film
Education & Research
Generative Model Research
Study the limitations and biases of generative models
Helps understand the characteristics of AI-generated content
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