Update app.py

app.py

@@ -54,8 +54,7 @@ def predict(img) -> Tuple[Dict, float]:
 
 example_list = [["examples/" + example] for example in os.listdir("examples")]
 title = "Computer Vision for Food Processing"
-description = "An [EfficientNetB2](https://pytorch.org/vision/main/models/generated/torchvision.models.efficientnet_b2.html?highlight=efficientnet_b2#torchvision.models.efficientnet_b2) feature extractor computer vision model to classify images of 101 foods (taken from PyTorch's [Food101](https://pytorch.org/vision/main/generated/torchvision.datasets.Food101.html) dataset).
-View the foods that this model can classify [here](https://github.com/alpapado/food-101/blob/master/data/meta/classes.txt)."
+description = "An [EfficientNetB2](https://pytorch.org/vision/main/models/generated/torchvision.models.efficientnet_b2.html?highlight=efficientnet_b2#torchvision.models.efficientnet_b2) feature extractor computer vision model to classify images of 101 foods (taken from PyTorch's [Food101](https://pytorch.org/vision/main/generated/torchvision.datasets.Food101.html) dataset). View the foods that this model can classify [here](https://github.com/alpapado/food-101/blob/master/data/meta/classes.txt)."
 
 demo = gr.Interface(fn=predict,
                     inputs=gr.Image(type="pil"),