Added instructions, et. al.

app.py

@@ -4,8 +4,8 @@ import huggingface_hub
 model_path_configs = {
         "Humpback Whales":      ("Intelligent-Instruments-Lab/rave-models", "humpbacks_pondbrain_b2048_r48000_z20.ts"), 
         "Magnets":              ("Intelligent-Instruments-Lab/rave-models", "magnets_b2048_r48000_z8.ts"), 
-        "Big Ensemble":          ("Intelligent-Instruments-Lab/rave-models", "crozzoli_bigensemblesmusic_18d.ts"),
-        "Bird Dawn Chorus":       ("Intelligent-Instruments-Lab/rave-models", "birds_dawnchorus_b2048_r48000_z8.ts"), 
+        "Big Ensemble":         ("Intelligent-Instruments-Lab/rave-models", "crozzoli_bigensemblesmusic_18d.ts"),
+        "Bird Dawn Chorus":     ("Intelligent-Instruments-Lab/rave-models", "birds_dawnchorus_b2048_r48000_z8.ts"), 
         "Speaking & Singing":   ("Intelligent-Instruments-Lab/rave-models", "voice-multi-b2048-r48000-z11.ts"), 
         "Resonator Piano":      ("Intelligent-Instruments-Lab/rave-models", "mrp_strengjavera_b2048_r44100_z16.ts"),
         "Multimbral Guitar":    ("Intelligent-Instruments-Lab/rave-models", "guitar_iil_b2048_r48000_z16.ts"),
@@ -248,12 +248,24 @@ def GenerateRaveEncDecAudio(model_name_a, model_name_b, audio_file_name, audio_f
         
 import gradio as gr
 
+column_widths=['35%', '20%', '20%', '25%']
 waveform_options = gr.WaveformOptions(waveform_color="#01C6FF", 
                                                      waveform_progress_color="#0066B4",
                                                      skip_length=2,)
-column_widths=['35%', '20%', '20%', '25%']
 
-AverageModels = gr.Interface(title="Process Audio Through Averaged Models.",
+description = "<p>This app attempts to average tewo RAVE models and then encode and decode an audio file through the averaged model.</p>" \
+"<ul><li>Select the two models from the list of pre-trained RAVE models (put credits).</li>" \
+"<li>Select an audio file from the ones available in the dropdown, or upload an audio file of up to 60 seconds.</li>" \
+"<li>Select a sample rate multiple for the averaged model. When there is a useful result, it sometimes sounds better at double the sample rate.</li>" \
+"<li>Select a bias towards one of the models. A bias of 0 will average the two models equally. A positive bias will favor Model A, and a negative bias will favor Model B.</li></ul>" \
+"<p>The app will display the original audio, the audio processed through each individual model, and the audio processed through the averaged model.</p>" \
+"<p>Note that in most cases not all parameters can be averaged. They may not exist in both models, or they may not have the same shape.</br>" \
+"These will be reported in the output dataframes and can be copied into a spreadsheet to be analyzed.</p>" \
+
+
+
+
+AverageModels = gr.Interface(title="Process Audio Through the Average of Two Rave Models", description=description,
     fn=GenerateRaveEncDecAudio,
     inputs=[
         gr.Radio(model_path_config_keys, label="Select Model A", value="Multimbral Guitar", container=True),
@@ -271,7 +283,7 @@ AverageModels = gr.Interface(title="Process Audio Through Averaged Models.",
         gr.Audio(label="Encoded/Decoded through Model A", sources=None, waveform_options=waveform_options,),
         gr.Audio(label="Encoded/Decoded through Model B", sources=None, waveform_options=waveform_options,),
         gr.Audio(label="Encoded/Decoded through averaged model", sources=None, waveform_options=waveform_options,),
-        gr.Textbox(label="Stats"),
+        gr.Textbox(label="Info:"),
         gr.Dataframe(label="Params Averaged", show_copy_button="True", scale=100, column_widths=column_widths, headers=['Param Name', 'Model A Shape', 'Model B Shape', 'Errors']),
         gr.Dataframe(label="Params Not Averaged", show_copy_button="True", scale=100, column_widths=column_widths, headers=['Param Name', 'Model A Shape', 'Model B Shape', 'Errors'])
         ]