arpm01/financial-summarization

1import gradio as gr2from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline3 4tokenizer = AutoTokenizer.from_pretrained("human-centered-summarization/financial-summarization-pegasus")5model = AutoModelForSeq2SeqLM.from_pretrained("human-centered-summarization/financial-summarization-pegasus")6 7pipe = pipeline(task="text2text-generation", model=model, tokenizer=tokenizer)8 9with open('text1.txt') as f:10    text1 = f.read()11 12with open('text2.txt') as f:13    text2 = f.read()14 15with open('text3.txt') as f:16    text3 = f.read()17 18gr.Interface.from_pipeline(pipe, 19                    title="Financial Summarization",20                    description="Financial Summarization using google/pegasus-xsum fine-tuned on financial news dataset. Model can be found at https://huggingface.co/human-centered-summarization/financial-summarization-pegasus. Examples are news articles from business.inquirer.net.",21                    examples=[text1,text2,text3]22                    ).launch()