app.py

import gradio as gr
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

model_name = "cointegrated/rut5-base"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)

def generate(text):
    inputs = tokenizer(text, return_tensors="pt")
    outputs = model.generate(**inputs, max_length=100)
    return tokenizer.decode(outputs[0], skip_special_tokens=True)

demo = gr.Interface(fn=generate, inputs="text", outputs="text", title="RuT5 Demo")
demo.launch()