From 60f5a643f13ec3b3148ff509d0d51414348fd252 Mon Sep 17 00:00:00 2001 From: Patrick von Platen Date: Tue, 7 Jun 2022 17:04:32 +0200 Subject: [PATCH] Update README.md --- README.md | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 80a8b9b9..2b1fe904 100644 --- a/README.md +++ b/README.md @@ -20,9 +20,9 @@ ## 1. `diffusers` as a central modular diffusion and sampler library -`diffusers` should be more modularized than `transformers` so that parts of it can be easily used in other libraries. -It could become a central place for all kinds of models, schedulers, training utils and processors required when using diffusion models in audio, vision, ... -One should be able to save both models and samplers as well as load them from the Hub. +`diffusers` is more modularized than `transformers`. The idea is that researchers and engineers can use only parts of the library easily for the own use cases. +It could become a central place for all kinds of models, schedulers, training utils and processors that one can mix and match for one's own use case. +Both models and scredulers should be load- and saveable from the Hub. Example: @@ -78,8 +78,8 @@ image_pil = PIL.Image.fromarray(image_processed[0]) image_pil.save("test.png") ``` -## 2. `diffusers` as a collection of most import Diffusion models (GLIDE, Dalle, ...) -`models` directory in repository hosts complete diffusion training code & pipelines. Easily load & saveable from the Hub. Will be possible to use just from pip `diffusers` version: +## 2. `diffusers` as a collection of most important Diffusion systems (GLIDE, Dalle, ...) +`models` directory in repository hosts the complete code necessary for running a diffusion system as well as to train it. A `DiffusionPipeline` class allows to easily run the diffusion model in inference: Example: