app.py

# URL: https://huggingface.co/spaces/gradio/text_generation
# imports
import gradio as gr
from transformers import GPT2Tokenizer, GPT2Model
import torch

# loading the model
tokenizer = GPT2Tokenizer.from_pretrained('gpt2')
model = GPT2Model.from_pretrained('gpt2')

# defining the core function
def generate(text):
    generation_pipeline = pipeline("text-generation", model=model, tokenizer=tokenizer)
    result = generation_pipeline(text)
    return result[0]["generated_text"]


# defining title and examples
title = "Text Generation with GPT-2"
examples = [
    ["The Moon's orbit around Earth has"],
    ["The smooth Borealis basin in the Northern Hemisphere covers 40%"],
]

# defining the interface
demo = gr.Interface(
    fn=generate,
    inputs=gr.inputs.Textbox(lines=5, label="Input Text"),
    outputs=gr.outputs.Textbox(label="Generated Text"),
    title=title,
    examples=examples
)

# launching
demo.launch()