Update app.py

app.py

@@ -7,7 +7,7 @@ labels = sorted(list(authors_df.name))
 
 model = tf.keras.models.load_model('efficientnetb0.h5')
 
-description = 'This is a DEMO that attempts to recognize the inspirations used by the AI art generator. After uploading a picture of an image, the application displays the predicted artist along with the probability of predicting the top three authors.The DEMO uses EfficientNetB0 convolutional neural network as a base model whose classifier was modified and trained the 8,000+ paintings from [Kaggle](https://www.kaggle.com/datasets/ikarus777/best-artworks-of-all-time) dataset. Given the dataset limitations, the model only recognizes paintings of [50 artists](https://huggingface.co/spaces/osydorchuk/painting_authors/blob/main/authors.csv).'
+description = 'This is a DEMO that attempts to recognize the inspirations used by the AI art generator. After uploading a picture of an image, the application displays the predicted artist along with the probability of predicting the top three authors.The DEMO uses EfficientNetB0 convolutional neural network as a base model whose classifier was modified and trained the 8,000+ paintings from [Kaggle](https://www.kaggle.com/datasets/ikarus777/best-artworks-of-all-time) dataset. Model trained by osydorchuk89. Given the dataset limitations, the model only recognizes paintings of [50 artists](https://huggingface.co/spaces/osydorchuk/painting_authors/blob/main/authors.csv).'
 
 def predict_author(input):
     if input is None: