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import gradio as gr
title = "BERT"
description = "Gradio Demo for BERT. 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/1810.04805' target='_blank'>BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding</a></p>"
examples = [
['Paris is the [MASK] of France.','bert-base-cased']
]
io1 = gr.Interface.load("huggingface/bert-base-cased")
io2 = gr.Interface.load("huggingface/bert-base-uncased")
def inference(inputtext, model):
if model == "bert-base-cased":
outlabel = io1(inputtext)
else:
outlabel = io2(inputtext)
return outlabel
gr.Interface(
inference,
[gr.inputs.Textbox(label="Context",lines=10),gr.inputs.Dropdown(choices=["bert-base-cased","bert-base-uncased"], type="value", default="bert-base-cased", label="model")],
[gr.outputs.Label(label="Output")],
examples=examples,
article=article,
title=title,
description=description).launch(enable_queue=True) |