Skip to content

GLIDE: a diffusion-based text-conditional image synthesis model

License

Notifications You must be signed in to change notification settings

tannervoas742/Glide-Text-2-Image

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

14 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

GLIDE

This is the official codebase for running the small, filtered-data GLIDE model from GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models.

For details on the pre-trained models in this repository, see the Model Card.

Usage

To install this package, clone this repository and then run:

pip install -e .

For detailed usage examples, see the notebooks directory.

  • The text2im notebook shows how to use GLIDE (filtered) with classifier-free guidance to produce images conditioned on text prompts.
  • The inpaint notebook shows how to use GLIDE (filtered) to fill in a masked region of an image, conditioned on a text prompt.
  • The clip_guided notebook shows how to use GLIDE (filtered) + a filtered noise-aware CLIP model to produce images conditioned on text prompts.

About

GLIDE: a diffusion-based text-conditional image synthesis model

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 82.1%
  • Jupyter Notebook 17.9%