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app.py

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+import gradio as gr
+from gradio import mix
+
+title = "GPT2"
+description = "Gradio Demo for OpenAI GPT2. 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://d4mucfpksywv.cloudfront.net/better-language-models/language_models_are_unsupervised_multitask_learners.pdf' target='_blank'>Language Models are Unsupervised Multitask Learners</a></p>"
+
+examples = [
+    ['Paris is the capital of',"gpt2-medium"]
+]
+
+io1 = gr.Interface.load("huggingface/distilgpt2")
+
+io2 = gr.Interface.load("huggingface/gpt2-large")
+
+io3 = gr.Interface.load("huggingface/gpt2-medium")
+
+io4 = gr.Interface.load("huggingface/gpt2-xl")
+
+def inference(text, model):
+    if model == "gpt2-large":
+        outtext = io2(text)
+    elif model == "gpt2-medium":
+        outtext = io3(text)
+    elif model == "gpt2-xl":
+        outtext = io4(text)
+    else:
+        outtext = io1(text)
+    return outtext   
+    
+     
+
+gr.Interface(
+    inference, 
+    [gr.inputs.Textbox(label="Input"),gr.inputs.Dropdown(choices=["distilgpt2","gpt2-medium","gpt2-large","gpt2-xl"], type="value", default="gpt2-medium", label="model")
+], 
+    gr.outputs.Textbox(label="Output"),
+    examples=examples,
+    article=article,
+    title=title,
+    description=description).launch(enable_queue=True, cache_examples=True)