import gradio as gr

title = "ALBERT"

description = "Gradio Demo for ALBERT. To use it, simply add your text, or click one of the examples to load them. Read more at the links below."

article = "<p style='text-align: center'><a href='https://arxiv.org/abs/1909.11942' target='_blank'>ALBERT: A Lite BERT for Self-supervised Learning of Language Representations</a></p>"

examples = [
    ['Paris is the [MASK] of France.','albert-base-v1']
]


io1 = gr.Interface.load("huggingface/albert-base-v1")

io2 = gr.Interface.load("huggingface/albert-base-v2")


def inference(inputtext, model):
    if model == "albert-base-v1":
        outlabel = io1(inputtext)
    else:
        outlabel = io2(inputtext)
    return outlabel
     

gr.Interface(
    inference, 
    [gr.inputs.Textbox(label="Context",lines=10),gr.inputs.Dropdown(choices=["albert-base-v1","albert-base-v2"], type="value", default="albert-base-v1", label="model")], 
    [gr.outputs.Label(label="Output")],
    examples=examples,
    article=article,
    title=title,
    description=description).launch(enable_queue=True,cache_examples=True)