I

IF II L V1.0

Developed by DeepFloyd
DeepFloyd-IF is a pixel-based three-stage cascaded diffusion model capable of generating images with exceptional realism and language understanding, achieving a zero-shot FID-30K score of 6.66.
Downloads 33.76k
Release Time : 3/21/2023

Model Overview

A pixel-level text-to-image cascaded diffusion model composed of a frozen text module and three-stage pixel diffusion modules, progressively increasing resolution (64x64→256x256→1024x1024), utilizing a T5 encoder to extract text embeddings and input them into a UNet architecture.

Model Features

High-Realism Image Generation
Zero-shot FID-30K score of 6.66 (COCO dataset), with exceptional detail representation
Three-Stage Cascaded Architecture
Progressively enhances resolution through 64x64→256x256→1024x1024 three-stage process, optimizing generation quality
Deep Language Understanding
Utilizes T5 text encoder for precise text-image semantic alignment
Memory-Optimized Design
Supports CPU offloading technology, requiring as little as 14GB VRAM to run

Model Capabilities

Text-to-Image Generation
High-Resolution Image Upscaling
Multilingual Prompt Understanding
Artistic Style Creation

Use Cases

Artistic Creation
Concept Design
Quickly generate creative concept images for clothing, scenes, etc.
Example: Precise generation of 'a kangaroo wearing an orange hoodie and blue sunglasses standing in front of the Eiffel Tower'
Educational Research
Generative Model Safety Research
Analyze biases and safety limitations of diffusion models
Built-in restrictions for prohibited scenarios such as military/surveillance
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