app.py

from transformers import AutoTokenizer, AutoModelForCausalLM,pipeline
import gradio as gr


tokenizer = AutoTokenizer.from_pretrained("distilgpt2")
model = AutoModelForCausalLM.from_pretrained("distilgpt2")


gen_pipeline = pipeline(task = "text-generation", model=model, tokenizer=tokenizer)
get_generated_text = lambda x: gen_pipeline(x,max_length = 200)[0]['generated_text']


demo = gr.Interface(
    fn   = get_generated_text ,
    inputs = gr.Textbox(label = 'Enter A series of Text and Generate more',lines = 2, max_lines = 5),
    outputs = 'text',
)


demo.launch()