From 2e9910bdb703da3ebeb295d06651648dc100eaa1 Mon Sep 17 00:00:00 2001 From: Patrick von Platen Date: Sun, 12 Jun 2022 00:24:20 +0200 Subject: [PATCH] Update README.md --- README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 941428b0..6c9a2d50 100644 --- a/README.md +++ b/README.md @@ -31,7 +31,7 @@ cd diffusers && pip install -e . 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 schedulers should be load- and saveable from the Hub. -**Example for [DDPM](https://arxiv.org/abs/2006.11239):** +#### **Example for [DDPM](https://arxiv.org/abs/2006.11239):** ```python import torch @@ -79,7 +79,7 @@ image_pil = PIL.Image.fromarray(image_processed[0]) image_pil.save("test.png") ``` -**Example for [DDIM](https://arxiv.org/abs/2010.02502):** +#### **Example for [DDIM](https://arxiv.org/abs/2010.02502):** ```python import torch @@ -133,7 +133,7 @@ image_pil.save("test.png") ### 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 image generation with DDPM** +#### **Example image generation with DDPM** ```python from diffusers import DiffusionPipeline