app.py

import gradio as gr
from transformers import GPT2LMHeadModel, GPT2Tokenizer

tokenizer = GPT2Tokenizer.from_pretrained('gpt2-large')
model = GPT2LMHeadModel.from_pretrained('gpt2-large', pad_token_id = tokenizer.eos_token_id)

def generator(text):
    input_ids = tokenizer.encode(text, return_tensors = 'pt')
    output = model.generate(input_ids, max_length = 500, num_beams = 5, no_repeat_ngram_size = 2, early_stopping = True)
    post = tokenizer.decode(output[0], skip_special_tokens = True)
    return post

interface = gr.Interface(
    fn=generator,
    inputs=gr.inputs.Textbox(lines=5, label="Input Text"),
    outputs=gr.outputs.Textbox(label="Generated Post"),
)

interface.launch()