app.py

import gradio as gr
from transformers import pipeline
pipe = pipeline("text2text-generation", model="csebuetnlp/banglat5")

def generate_text(input_text):
    output = pipe(input_text)
    return output[0]['generated_text']

iface = gr.Interface(
    fn=generate_text,
    inputs=gr.inputs.Textbox(label="Input Text"),
    outputs=gr.outputs.Textbox(label="Generated Text"),
    title="Bangla Text Generation",
    description="Generate text based on the input using the Bangla T5 model."
)
if __name__ == "__main__":
    iface.launch()