Modified::Added some text to the app

app.py

@@ -92,6 +92,15 @@ def multilabel_classification(n_samples:int, n_classes: int, n_labels: int, allo
 
 with gr.Blocks() as demo:
 
+    gr.Markdown(""" 
+    
+    # Multilabel Classification
+
+    This space is an implementation of the scikit-learn document [Multilabel Classification](https://scikit-learn.org/stable/auto_examples/miscellaneous/plot_multilabel.html#sphx-glr-auto-examples-miscellaneous-plot-multilabel-py).
+    The objective of this space is to simulate a multi-label document classification problem, where the data is generated randomly. 
+    
+    """)
+
     n_samples = gr.Slider(100, 10_000, label="n_samples", info="the number of samples")
     n_classes = gr.Slider(2, 10, label="n_classes", info="the number of classes that data should have.", step=1)
     n_labels = gr.Slider(1, 10, label="n_labels", info="the average number of labels per instance", step=1)