Update app.py

app.py

@@ -6,8 +6,29 @@ description = "Gradio Demo for ELECTRA. To use it, simply add your text, or clic
 
 article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2003.10555' target='_blank'>ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators</a></p>"
 
+
 examples = [
-    ["My name is Sarah and I live in London","Where do I live?"]
+    ["My name is Sarah and I live in London","electra_large_discriminator_squad2_512","Where do I live?"]
 ]
 
-gr.Interface.load("huggingface/ahotrod/electra_large_discriminator_squad2_512",title=title,description=description,article=article, examples=examples).launch(enable_queue=True)
+io1 = gr.Interface.load("huggingface/ahotrod/electra_large_discriminator_squad2_512")
+
+io2 = gr.Interface.load("huggingface/deepset/electra-base-squad2")
+
+def inference(context, model,question):
+    if model == "electra_large_discriminator_squad2_512":
+        outlabel = io1(context,question)
+    else:
+        outlabel = io2(context,question)
+    return outlabel
+     
+
+gr.Interface(
+    inference, 
+    [gr.inputs.Textbox(label="Context",lines=10),gr.inputs.Dropdown(choices=["electra_large_discriminator_squad2_512","electra-base-squad2"], type="value", default="electra_large_discriminator_squad2_512", label="model"),gr.inputs.Textbox(label="Question Answering")], 
+    [gr.outputs.Textbox(label="Output")],
+    examples=examples,
+    article=article,
+    title=title,
+    description=description).launch(enable_queue=True, cache_examples=True)
+