mlt-tokyo-2 / app.py
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Create app.py
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import gradio as gr
from transformers import pipeline
pipe = pipeline("text-classification", model="lewtun/xlm-roberta-base-finetuned-marc-en")
label2emoji = {"terrible": "๐Ÿ’ฉ", "poor": "๐Ÿ˜พ", "ok": "๐Ÿฑ", "good": "๐Ÿ˜บ", "great": "๐Ÿ˜ป"}
def predict(text):
preds = pipe(text)[0]
return label2emoji[preds["label"]], round(preds["score"], 5)
gradio_ui = gr.Interface(
fn=predict,
title="Predicting review scores from customer reviews",
description="Enter some review text about an Amazon product and check what the model predicts for it's star rating.",
inputs=[
gr.inputs.Textbox(lines=5, label="Paste some text here"),
],
outputs=[
gr.outputs.Textbox(label="Label"),
gr.outputs.Textbox(label="Score"),
],
examples=[
["My favourite book is Cryptonomicon!"], ["็งใฎๅฅฝใใชๆœฌใฏใ€Œใ‚ฏใƒชใƒ—ใƒˆใƒŽใƒŸใ‚ณใƒณใ€ใงใ™"]
],
)
gradio_ui.launch(debug=True)