app.py

import gradio
from os import system

system("pip3 install torch")
system("pip3 install transformers")

from transformers import AutoTokenizer,OpenAIGPTLMHeadModel

tokenizer = AutoTokenizer.from_pretrained("openai-community/openai-gpt")
model = OpenAIGPTLMHeadModel.from_pretrained("openai-community/openai-gpt")

def work(inp_text):
    out = tokenizer.encode(inp_text,return_tensors="pt")

    out = model.generate(
        out,
        max_new_tokens=20,
        do_sample=True,
        temperature=0.3,
    )

    out = tokenizer.decode(out[0])

    return str(out)

demo = gradio.Interface(
    fn=work,
    inputs=["text"],
    outputs=["text"],
)

demo.launch()