init

app.py

@@ -1,9 +1,35 @@
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!"
+title = "BERT"
 
-demo = gr.Interface(fn=greet, inputs="textbox", outputs="textbox")
-    
-if __name__ == "__main__":
-    demo.launch()
+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
+
+inputs = gr.Textbox(label="Context", lines=10)
+model_choice = gr.Dropdown(choices=["bert-base-cased", "bert-base-uncased"], label="Model", default="bert-base-cased")
+outputs = gr.Textbox(label="Output")
+
+gr.Interface(
+    fn=inference,
+    inputs=[inputs, model_choice],
+    outputs=outputs,
+    examples=examples,
+    article=article,
+    title=title,
+    description=description
+).launch(enable_queue=True)