fix typos

Author: Thomas Capelle

README.md

@@ -4,8 +4,7 @@
 
 # Cloud Diffusion Experiment
 
-This codebase contains an implementation of a deep diffusion model applied to cloud images. It was developed as part of a research project exploring the potential of diffusion models
-for image generation and forecasting.
+This codebase contains an implementation of a deep diffusion model applied to cloud images. It was developed as part of a research project exploring the potential of diffusion models for image generation and forecasting.
 
 ## Setup
 
@@ -18,6 +17,7 @@ for image generation and forecasting.
 To train the model, run `python train.py`. You can play with the parameters on top of the file to change the model architecture, training parameters, etc.
 
 You can also override the configuration parameters by passing them as command-line arguments, e.g.
+
 ```bash
 > python train.py --epochs=10 --batch_size=32
 ```
@@ -27,7 +27,6 @@ You can also override the configuration parameters by passing them as command-li
 This training is based on a Transformer based Unet (UViT), you can train the default model by running:
 
 ```bash
-
 > python train_uvit.py
 ```