Update README.md

README.md

@@ -14,7 +14,7 @@ license: mit
 
 [FastGAN model](https://arxiv.org/abs/2101.04775) is a Generative Adversarial Networks (GAN) training on a small amount of high-fidelity images with minimum computing cost. Using a skip-layer channel-wise excitation module and a self-supervised discriminator trained as a feature-encoder, the model was able to converge after some hours of training for either 100 high-quality images or 1000 images datasets.
 
-This model was trained on a dataset of 1000 high-quality images of Shells.
+This model was trained on a dataset of 1000 high-quality images of art paintings.
 
 
 #### How to use