Update app.py

app.py

@@ -19,10 +19,10 @@ learn = load_learner('drawingstyle.pkl')
 labels = learn.dls.vocab
 
 title = "What's your drawing style?"
-description = "An artistic style classifier trained on the <a href='https://www.kaggle.com/datasets/ikarus777/best-artworks-of-all-time'>best-artworks-of-all-time</a> dataset with fastai. Created as homework for lesson 2 of the course <a href='https://course.fast.ai/Lessons/lesson2.html'>Pratical Deep Learning for Coders</a>."
+description = "An artistic style classifier trained on the <a href='https://www.kaggle.com/datasets/ikarus777/best-artworks-of-all-time'>best-artworks-of-all-time</a> dataset with fastai. Created as homework for lesson 2 of the course <a href='https://course.fast.ai/Lessons/lesson2.html'>Pratical Deep Learning for Coders</a>.<br>Do you feel like something is off? Check the <a href='https://www.kaggle.com/code/nerusskyhigh/artisticdrawingstyle' target='_blank'>Kaggle Notebook</a>! ;)"
 
 
-article="<p style='text-align: center'>Do you feel like something is off? Check the <a href='https://www.kaggle.com/code/nerusskyhigh/artisticdrawingstyle' target='_blank'>Kaggle Notebook</a>!</br>You can find more test images in the original dataset. Only the first 100 images per artist were used to train the neural network. As the other images were discarded, you can use them to test the network.</p>"
+article="<p style='text-align: center'><a href='https://github.com/NerusSkyhigh/practicaldeeplearning' target='_blank'>Check the repository!</a></br>You can find more test images in the original dataset. Only the first 100 images per artist were used to train the neural network. As the other images were discarded, you can use them to test the network.</p>"
 
 examples = ['Leonardo_da_Vinci_121.jpg', 'Pablo_Picasso_164.jpg', 'Vincent_van_Gogh_154.jpg']