import gradio as gr

title = "ConvBERT"

description = "Gradio Demo for ConvBERT. 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/2008.02496' target='_blank'>ConvBERT: Improving BERT with Span-based Dynamic Convolution</a></p>"

examples = [
    ['My name is Wolfgang and I live in Berlin',"conv-bert-base"]
]


io1 = gr.Interface.load("huggingface/YituTech/conv-bert-base")

io2 = gr.Interface.load("huggingface/YituTech/conv-bert-medium-small")

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

gr.Interface(
    inference, 
    [gr.inputs.Textbox(label="Context",lines=10),gr.inputs.Dropdown(choices=["conv-bert-base","conv-bert-medium-small"], type="value", default="conv-bert-base", label="model")], 
    [gr.outputs.Dataframe(type="pandas",label="Output",max_rows=2000000)],
    examples=examples,
    article=article,
    title=title,
    description=description).launch(enable_queue=True)