| 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,cache_examples=True) |