Create app.py

app.py

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+import gradio as gr
+
+from transformers import GPT2Tokenizer, TFGPT2LMHeadModel, pipeline
+tokenizer = GPT2Tokenizer.from_pretrained('gpt2')
+model = TFGPT2LMHeadModel.from_pretrained('gpt2')
+
+pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+
+def predict(x):
+    output = pipe(text_inputs=x, max_length=50)
+    return output[0]['generated_text']
+
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Generate some text with this demo ! ")
+    input = gr.Textbox(label="Input Text")
+    output = gr.Textbox(label="Output Text")
+    generate_btn = gr.Button("Generate")
+    generate_btn.click(fn=predict, inputs=input, outputs=output)
+    gr.Markdown("## Examples")
+    gr.Examples(examples=["My name is James and i like", "I go every day at the "],
+                cache_examples=True,
+                inputs=input,
+                outputs=output,
+                fn=predict)
+
+
+demo.launch(server_name="0.0.0.0")