app.py

import gradio as gr

# Simulated responses to show effects of fine-tuning
techniques = {
    "Full Fine-Tuning": {
        "description": "Retrain the entire model on your specific data. Best for when you have a lot of data and compute.",
        "example_input": "Translate 'How are you?' into Kannada.",
        "output": "ನೀವು ಹೇಗಿದ್ದೀರಾ?"
    },
    "Feature Extraction (Freeze Layers)": {
        "description": "Use the model’s existing features and only train the final layers on your data.",
        "example_input": "Classify: 'This movie was thrilling and well-acted.'",
        "output": "Positive sentiment"
    },
    "Adapter Layers": {
        "description": "Insert small trainable blocks inside a frozen model. Very efficient.",
        "example_input": "Generate a reply to: 'I want to cancel my flight.'",
        "output": "Sure, I can help you cancel your flight. Can I know the booking ID?"
    },
    "LoRA (Low-Rank Adaptation)": {
        "description": "Train only low-rank matrices while keeping the original weights frozen. Saves a lot of memory.",
        "example_input": "Explain: 'Photosynthesis' to a 5-year-old.",
        "output": "Plants make their food using sunlight and air, like magic!"
    },
    "Prompt Tuning": {
        "description": "Only tune how the prompt is phrased. Model weights stay unchanged.",
        "example_input": "Summarize: 'Today was a rainy day and we stayed indoors.'",
        "output": "Summary: It rained and we stayed inside."
    }
}

def show_details(selected_technique):
    data = techniques[selected_technique]
    return data["description"], data["example_input"], data["output"]

with gr.Blocks() as demo:
    gr.Markdown("## 🧠 Model Fine-Tuning Techniques (Simulated Examples)")
    gr.Markdown("Select a technique to learn how it works and what it can do:")

    technique_dropdown = gr.Dropdown(choices=list(techniques.keys()), label="Choose a Fine-Tuning Technique")
    desc = gr.Textbox(label="Description", lines=3)
    example = gr.Textbox(label="Example Input")
    output = gr.Textbox(label="Simulated Output")

    technique_dropdown.change(fn=show_details, inputs=technique_dropdown, outputs=[desc, example, output])

demo.launch()