app.py

import gradio as gr

from transformers import pipeline
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

#hub_model_id = "huggingface-course/mt5-small-finetuned-amazon-en-es"
model_id = "philschmid/bart-large-cnn-samsum"
#model_id = "t5-base"

summarizer = pipeline("summarization", model=model_id)

def summarize(text):
    #return "Summary: " + text
    out = summarizer_bart(text, max_length=70, min_length = 35)
    return "Summary: " + str(out)

iface = gr.Interface(fn=summarize, inputs="text", outputs="text")
iface.launch()