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Stable Cascade

Developed by stabilityai
An efficient text-to-image generation model based on Würstchen architecture, achieving fast inference and low-cost training through a 42x compression factor
Downloads 24.96k
Release Time : 2/6/2024

Model Overview

Stable Cascade is a three-stage text-to-image generation model that significantly reduces computational costs through a highly compressed latent space while maintaining high-quality image generation capabilities

Model Features

Efficient Compression Architecture
Employs a 42x compression factor (1024x1024→24x24), significantly improving efficiency compared to Stable Diffusion's 8x compression
Low Training Cost
Early versions reduce training costs by 16x compared to Stable Diffusion 1.5
Compatible Extensions
Supports extensions like LoRA, ControlNet, IP-Adapter, LCM
Multiple Version Options
Offers model versions with different parameter scales (1B/3.6B parameters, etc.) to meet diverse needs

Model Capabilities

Text-to-image generation
High-resolution image generation (1024x1024)
Fast inference
Image reconstruction

Use Cases

Art Creation
Concept Art Generation
Generate creative concept art images from text descriptions
High-quality artworks
Design Applications
Product Prototype Design
Quickly generate product design prototype images
Accelerate design workflow
Education & Research
Generative Model Research
Study the architecture and performance of efficient generative models
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