add better description

app.py

@@ -164,13 +164,7 @@ See an [example dataset](https://huggingface.co/datasets/davanstrien/MOH-Bethnal
 
 The resulting text chunks are stored in a dataset that can be previewed and uploaded to the Hugging Face Hub for easy sharing and access by the community.
 The chunking is done using `Llama-index`'s [`SentenceSplitter`](https://docs.llamaindex.ai/en/stable/module_guides/loading/node_parsers/modules/?h=sentencesplitter#sentencesplitter) classes. 
-
-### Usage:
-1. Upload Files: Use the upload button to load file(s) for processing. A preview will be automatically generated using default settings.
-2. Adjust Parameters (Optional): Customize the chunk size, overlap, and sentence splitting option according to your requirements.
-3. Update Preview (Optional): Click the 'Update Preview' button to view the updated dataset based on your parameter changes.
-4. Login: When ready to upload, log in to your Hugging Face account using the provided login button.
-5. Upload to Hub: Specify the Hub ID, choose whether to make the dataset private, and click 'Upload to Hub'."""
+"""
 
 with gr.Blocks() as demo:
     state = gr.State({})
@@ -180,7 +174,9 @@ with gr.Blocks() as demo:
         <center><i> &#128193; From random files to a Hugging Face dataset in a few steps &#128193; </i></center>"""
     )
     gr.Markdown(description)
-
+    gr.Markdown(
+        "### 1. Upload Files\nClick 'Upload Files' to select text file(s). A preview will generate automatically"
+    )
     with gr.Row():
         upload_button = gr.File(
             file_types=["text"],
@@ -189,7 +185,10 @@ with gr.Blocks() as demo:
             interactive=True,
             label="Upload Files",
         )
-
+    gr.Markdown("""
+    ### 2. Adjust Parameters for Chunking Text (Optional)
+    Customize the chunk size, overlap, and sentence splitting option according to your requirements.
+    """)
     with gr.Row():
         split_sentences = gr.Checkbox(True, label="Split sentences?")
         chunk_size = gr.Number(
@@ -206,17 +205,19 @@ with gr.Blocks() as demo:
             maximum=4096,
             step=1,
         )
-
+    gr.Markdown(
+        "### 3. Update Preview\nClick 'Update Preview' to see changes based on new parameters."
+    )
     update_preview_button = gr.Button("Update Preview")
+
     corpus_preview_df = gr.DataFrame(label="Dataset Preview")
     preview_summary = gr.Markdown()
-
+    gr.Markdown("""### 4. Upload to Hub
+    After adjusting parameters and previewing the dataset, you can upload it to the Hugging Face Hub. Make sure to sign in to your Hugging Face account. Specify the Hub ID and choose whether to make the dataset private. Click 'Upload to Hub' to complete the process.
+    """)
     with gr.Row():
         gr.LoginButton()
         with gr.Column():
-            gr.Markdown(
-                "To upload to the Hub, add an ID for where you want to push the dataset"
-            )
             hub_id = gr.Textbox(value=None, label="Hub ID")
             private = gr.Checkbox(False, label="Upload dataset to a private repo?")