Add usage

frontends/gradio/main.py

@@ -536,6 +536,10 @@ def launch():
                     outputs=[plot],
                 )
 
+            with gr.Tab("Usage"):
+                with open(root_dir / "usage.md", "r") as f:
+                    gr.Markdown(f.read())
+
     demo.launch()
 
 

usage.md

@@ -2,9 +2,9 @@
 In this visualizer you can train an MLP to fit the data points.
 
 ### Dataset - Generate or upload a dataset to train on.
-If generating, enter a function and the visualizer will sample points uniformly in the domain based on the settings. If uploading, make sure to upload a csv file with two columns with x being the first column and y being the second.
+If generating, enter a function and the visualizer will sample points uniformly in the domain based on the settings. If uploading, make sure to upload a csv file with at least two columns.
 
-### Architecture - Specify MLP architecture
+### Model - Specify MLP architecture
 You can choose one of the presets or use a custom one by editing the text. Each layer must be in square brackets and the last layer must always be `[output_units: 1]`. Supported activation functions are: `{relu, sigmoid, tanh, leaky_relu, elu, gelu, identity}`. 
 
 ### Train - Train the MLP on the dataset