deep-floyd/IF

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

7804 stars · 523 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

DeepFloyd IF is an open-source text-to-image model library implementing a cascaded pixel diffusion architecture with a frozen T5 text encoder and two super-resolution stages, producing photorealistic images up to 1024x1024 px. It ships as a Python package with notebooks and integrations for running the base and upscaler modules.

Use cases

• generate photorealistic images from text prompts
• run a cascaded diffusion text-to-image pipeline locally
• upscale 64x64 generated images to 256px and 1024px
• research large UNet diffusion models with strong language understanding
• benchmark text-to-image models on COCO zero-shot FID

When to choose

• you need high photorealism and strong text rendering in generated images
• you have 16-24GB of GPU VRAM available
• you want an open-source research-grade text-to-image model in Python

When to avoid

• you lack a high-VRAM GPU
• you need actively maintained tooling or the latest model features
• you want a lightweight or CPU-only image generator

Facets

library · maturity maintenance

machine-learning image-processing deep-learning artificial-intelligence image-processing deep-learning python text-to-image diffusion-models image-generation super-resolution t5-encoder gpu linux

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markdown · JSON · MCP: product_card(name="deep-floyd/IF")