Update app.py

app.py

@@ -353,11 +353,11 @@ with gr.Blocks() as demo:
         0.9]</i></b> and <b><i>y</i></b> in range <b><i>[0.25, 0.7]</i></b>, since the training dataset labels are in 
         given ranges.)</p>""")
     gr.Markdown(
-        """<p>( <b>Point-E Demo Note</b>: THis demo only shows the point cloud results instead of meshes due to 
-        hardware limitation. For mesh results, check out our code.)</p>""")
+        """<p>( <b>Point-E Note</b>: This demo only shows the point cloud results instead of meshes due to 
+        hardware limitation. For mesh results, check out our code to render them on your local machine!)</p>""")
     gr.Markdown(
-        """<p>( <b>Stable Diffusion Note</b>: Stable Diffusion has filter enabled, so it sometimes generates all black 
-        results for possibly improper images.)</p>""")
+        """<p>( <b>Stable Diffusion Note</b>: Stable Diffusion has a filter enabled, so it sometimes generates all black 
+        results for possibly inappropriate images.)</p>""")
     with gr.Row():
         with gr.Column():
             gr.Markdown(
@@ -390,7 +390,7 @@ with gr.Blocks() as demo:
             with gr.Row():
                 asset_model = gr.Radio(['Point-E'], type="value", label='Text to 3D model', value='Point-E')
             # asset_output = gr.Image(label='GIF')
-            asset_output = gr.Plot(label='Plot')
+            asset_output = gr.Plot(label='Plot')Screenshot from 2023-01-18 10-32-20
             asset_button = gr.Button("Generate")
             asset_examples = gr.Examples(examples=pointe_examples, inputs=[asset_input, asset_weights, asset_model])