from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
import gradio as gr

model_name = "deep-learning-analytics/wikihow-t5-small"
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
text2text_tokenizer = AutoTokenizer.from_pretrained(model_name)

def text2text(paragraph):
    text = paragraph.strip().replace("\n", "")
    token_text = text2text_tokenizer.encode(text, return_tensors="pt")
    token_ids = model.generate(token_text, max_length=250, num_beams=5, repetition_penality=2.5, early_stopping=True)
    response = text2text_tokenizer.decode(token_ids[0], skip_special_tokens=True) 
    return response

in_para = gr.Textbox(lines=10, label="Paragraph", placeholder="Copy paragraph")
out = gr.Textbox(lines=1, label="Summary")
gr.Interface(text2text, inputs=in_para, outputs=out)