import gradio as gr
title = "T0"
description = "Gradio Demo for T0: T0* is a series of encoder-decoder models trained on a large set of different tasks specified in natural language prompts. Can use the models to perform inference on tasks by specifying your query in natural language, and the models will generate a prediction. Read more at the links below."
article = "<p style='text-align: center'><a href='https://huggingface.co/bigscience/T0' target='_blank'>Hugging face model page</a></p>"
examples = [
    ['Is this review positive or negative? Review: this is the best cast iron skillet you will ever buy'],
    ['Reorder the words in this sentence: justin and name bieber years is my am I 27 old.']
]
gr.Interface.load("huggingface/bigscience/T0", inputs=gr.inputs.Textbox(lines=5, label="Input Text"),title=title,description=description,article=article, examples=examples,enable_queue=True).launch()