app.py

import gradio as gr
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline

# tokenizer = AutoTokenizer.from_pretrained("human-centered-summarization/financial-summarization-pegasus")
# model = AutoModelForSeq2SeqLM.from_pretrained("human-centered-summarization/financial-summarization-pegasus")
# pipe = pipeline(task="summarization", 
#                 model=model,
#                 tokenizer=tokenizer,)

pipe = pipeline(task="text2text-generation", model = "human-centered-summarization/financial-summarization-pegasus")

with open('text1.txt') as f:
    text1 = f.read()

with open('text2.txt') as f:
    text2 = f.read()

with open('text3.txt') as f:
    text3 = f.read()

gr.Interface.from_pipeline(pipe, 
                    title="Financial Summarization",
                    description="Financial Summarization using Pegasus. Model can be found at https://huggingface.co/human-centered-summarization/financial-summarization-pegasus",
                    examples=[text1,text2]
                    ).launch()