Update app.py

app.py

@@ -49,17 +49,17 @@ with gr.Blocks(title=title) as demo:
     gr.Markdown(f"# {title}")
     gr.Markdown(
         """
-        ### This demo shows the precision-recall curves on the Iris dataset \
+        This demo shows the precision-recall curves on the Iris dataset \
         using a Linear SVM classifier + StandardScaler. \
         Noise is added to the dataset to make the problem more challenging. \
         The dataset is split into train and test sets. \
         The model is trained on the train set and evaluated on the test set. \
         Two separate problems are solved: 
         
-        ### Binary classification: class 0 vs class 1
-        ### Multi-label classification: class 0 vs class 1 vs class 2
+        - Binary classification: class 0 vs class 1
+        - Multi-label classification: class 0 vs class 1 vs class 2
 
-        [Original Example](https://scikit-learn.org/stable/auto_examples/model_selection/plot_precision_recall.html#sphx-glr-auto-examples-model-selection-plot-precision-recall-py)
+        See the scikit-learn example [here](https://scikit-learn.org/stable/auto_examples/model_selection/plot_precision_recall.html#sphx-glr-auto-examples-model-selection-plot-precision-recall-py).
         """
     )