Update app.py

app.py

@@ -79,32 +79,41 @@ def predict(music_prompt, melody, duration):
 
 
 with gr.Blocks() as demo:
+    gr.Markdown(
+        """
+        # Split Audio to MusicGen
+        <br/>
+        <a href="https://huggingface.co/spaces/fffiloni/SplitTrack2MusicGen?duplicate=true" style="display: inline-block;margin-top: .5em;margin-right: .25em;" target="_blank">
+        <img style="margin-bottom: 0em;display: inline;margin-top: -.25em;" src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>
+        for longer sequences, more control and no queue.</p>
+        """
+    )
+    with gr.Row():
+        
+        with gr.Row():
+            uploaded_sound = gr.Audio(type="numpy", label="Input", source="upload")
+            chosen_track = gr.Radio(["vocals", "bass", "drums", "other"], label="Track", info="Which track from your audio do you want to mashup ?", value="vocals")
+            load_sound_btn = gr.Button('Load your sound')
+            #split_vocals = gr.Audio(type="filepath", label="Vocals")
+            #split_bass = gr.Audio(type="filepath", label="Bass")
+            #split_drums = gr.Audio(type="filepath", label="Drums")
+            #split_others = gr.Audio(type="filepath", label="Other")
+        with gr.Row():
+            music_prompt = gr.Textbox(label="Musical Prompt", info="Describe what kind music you wish for", interactive=True)
+            melody = gr.Audio(source="upload", type="numpy", label="Melody Condition (optional)", interactive=False)
     with gr.Row():
-        with gr.Column():
-            with gr.Row():
-                uploaded_sound = gr.Audio(type="numpy", label="Input", source="upload")
-                chosen_track = gr.Radio(["vocals", "bass", "drums", "other"], label="Track", info="Which track from your audio do you want to mashup ?", value="vocals")
-                load_sound_btn = gr.Button('Load your sound')
-                #split_vocals = gr.Audio(type="filepath", label="Vocals")
-                #split_bass = gr.Audio(type="filepath", label="Bass")
-                #split_drums = gr.Audio(type="filepath", label="Drums")
-                #split_others = gr.Audio(type="filepath", label="Other")
-            with gr.Row():
-                music_prompt = gr.Textbox(label="Musical Prompt", info="Describe what kind music you wish for", interactive=True)
-                melody = gr.Audio(source="upload", type="numpy", label="Melody Condition (optional)", interactive=False)
-            with gr.Row():
-                submit = gr.Button("Submit")
-            #with gr.Row():
-            #   model = gr.Radio(["melody", "medium", "small", "large"], label="Model", value="melody", interactive=True)
-            with gr.Row():
-                duration = gr.Slider(minimum=1, maximum=30, value=10, step=1, label="Duration", interactive=True)
-            #with gr.Row():
-            #   topk = gr.Number(label="Top-k", value=250, interactive=True)
-            #   topp = gr.Number(label="Top-p", value=0, interactive=True)
-            #   temperature = gr.Number(label="Temperature", value=1.0, interactive=True)
-            #   cfg_coef = gr.Number(label="Classifier Free Guidance", value=3.0, interactive=True)
-        with gr.Column():
-            output = gr.Audio(label="Generated Music")
+        submit = gr.Button("Submit")
+    #with gr.Row():
+    #   model = gr.Radio(["melody", "medium", "small", "large"], label="Model", value="melody", interactive=True)
+    with gr.Row():
+        duration = gr.Slider(minimum=1, maximum=30, value=10, step=1, label="Duration", interactive=True)
+    #with gr.Row():
+    #   topk = gr.Number(label="Top-k", value=250, interactive=True)
+    #   topp = gr.Number(label="Top-p", value=0, interactive=True)
+    #   temperature = gr.Number(label="Temperature", value=1.0, interactive=True)
+    #   cfg_coef = gr.Number(label="Classifier Free Guidance", value=3.0, interactive=True)
+    
+    output = gr.Audio(label="Generated Music")
     load_sound_btn.click(split_process, inputs=[uploaded_sound, chosen_track], outputs=[melody])
     submit.click(predict, inputs=[music_prompt, melody, duration], outputs=[output])