Update app.py

app.py

@@ -7,6 +7,8 @@ import streamlit as st
 
 # Each dataset is unique, and depending on the task, some datasets may require additional steps to prepare it for training. But you can always use datasets tools to load and process a dataset. The fastest and easiest way to get started is by loading an existing dataset from the [Hugging Face Hub](https://huggingface.co/datasets). There are thousands of datasets to choose from, spanning many tasks. Choose the type of dataset you want to work with, and let's get started!
 
+st.html = """
+
 <div class="mt-4">
    <div class="w-full flex flex-col space-y-4 md:space-y-0 md:grid md:grid-cols-3 md:gap-y-4 md:gap-x-5">
       <a class="!no-underline border dark:border-gray-700 p-5 rounded-lg shadow hover:shadow-lg" href="#audio"
@@ -29,7 +31,7 @@ import streamlit as st
 # Check out [Chapter 5](https://huggingface.co/course/chapter5/1?fw=pt) of the Hugging Face course to learn more about other important topics such as loading remote or local datasets, tools for cleaning up a dataset, and creating your own dataset.
 
 </Tip>
-
+""", unsafe_allow_html=True)
 
 from datasets import load_dataset, Audio