app.py

import gradio as gr
from transformers import AutoConfig

# Predefined list of models
model_list = ["bert-base-uncased", "gpt2", "distilbert-base-uncased"]

def update_model_list(new_model):
    if new_model not in model_list:
        model_list.append(new_model)
    return model_list

def create_config(model_name, num_labels, use_cache):
    config = AutoConfig.from_pretrained(model_name, num_labels=num_labels, use_cache=use_cache)
    return str(config)

with gr.Blocks() as demo:
    gr.Markdown("## Config Class - Transformers")
    with gr.Row():
        model_dropdown = gr.Dropdown(label="Select a Model", choices=model_list)
        add_model_box = gr.Textbox(label="Add a New Model")
        add_model_button = gr.Button("Add Model")
    num_labels = gr.Number(label="Number of Labels", default=2)
    use_cache = gr.Checkbox(label="Use Cache", default=True)
    output = gr.Textbox(label="Config Output", readonly=True)
    submit_button = gr.Button("Create Config")

    # Logic to add a new model to the dropdown
    add_model_button.click(fn=update_model_list, inputs=add_model_box, outputs=model_dropdown)

    # Logic to create a config
    submit_button.click(fn=create_config, inputs=[model_dropdown, num_labels, use_cache], outputs=output)

demo.launch()