app.py

from transformers import pipeline, set_seed
import gradio as grad

gpt2_pipe = pipeline('text-generation', model = 'distilgpt2')
set_seed(42)

def generate(starting_text):
    response = gpt2_pipe(starting_text, max_length = 20, num_return_sequences = 5)

    return response

txt = grad.Textbox(lines = 1, label = 'English', placeholder = 'English Text Here')
out = grad.Textbox(lines = 1, label = 'Generated Text')
grad.Interface(
    generate,
    inputs = txt,
    outputs = out
).launch()