Update app.py

app.py

@@ -44,25 +44,41 @@ def update_interface(dataset_input):
         outputs=output
     ).launch()
 
-# Select Model
-model_name = gr.Dropdown(label="Model", choices=conf['model']['choices'], value="gpt2")
-# Prompt template
-prompt_template = gr.Textbox(label="Prompt Template", value="Instruction: {0}\nOutput: {1}")
-# Prompt Input
-name_input = gr.Textbox(label="Your Name")
-# Dataset choice
-dataset_choice = gr.Radio(label="Choose Dataset", choices=["Predefined Dataset", "Upload Your Own"], value="Predefined Dataset")
-
-# Initial interface setup
-initial_choice = dataset_choice.value
-initial_interface = build_interface(initial_choice)
-
-# Output textbox
-output = gr.Textbox(label="Output")
-
-# Setup button
-tune_btn = gr.Button("Start Fine Tuning")
-tune_btn.click(on_choice_change, inputs=[dataset_choice])
-
-# Launch the initial interface
-update_interface(initial_interface)
+##################################### Gradio Blocks #######################################
+with gr.Blocks() as demo:
+
+    ##### Title Block #####
+    gr.Markdown("# Instruction Tuning with Unsloth")
+
+    ##### Model Inputs #####
+
+    # Select Model
+    model_name = gr.Dropdown(label="Model", choices=conf['model']['choices'], value="gpt2")
+    # Prompt template
+    prompt_template = gr.Textbox(label="Prompt Template", value="Instruction: {0}\nOutput: {1}")
+    # Prompt Input
+    name_input = gr.Textbox(label="Your Name")
+    # Dataset choice
+    dataset_choice = gr.Radio(label="Choose Dataset", choices=["Predefined Dataset", "Upload Your Own"], value="Predefined Dataset")
+
+    # Initial interface setup
+    initial_choice = dataset_choice.value
+    initial_interface = build_interface(initial_choice)
+
+    # Output textbox
+    output = gr.Textbox(label="Output")
+
+    # Setup button
+    tune_btn = gr.Button("Start Fine Tuning")
+    tune_btn.click(on_choice_change, inputs=[dataset_choice])
+
+    # Launch the initial interface
+    update_interface(initial_interface)
+
+    # Update visibility based on user choice
+    dataset_choice.change(on_choice_change, inputs=[dataset_choice])
+
+##################################### Launch #######################################
+
+if __name__ == "__main__":
+    demo.launch()