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import gradio as gr |
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from transformers import pipeline |
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pipe = pipeline("text-classification", model="lewtun/xlm-roberta-base-finetuned-marc-en") |
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label2emoji = {"terrible": "๐ฉ", "poor": "๐พ", "ok": "๐ฑ", "good": "๐บ", "great": "๐ป"} |
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def predict(text): |
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preds = pipe(text)[0] |
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return label2emoji[preds["label"]], round(preds["score"], 5) |
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gradio_ui = gr.Interface( |
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fn=predict, |
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title="Predicting review scores from customer reviews", |
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description="Enter some review text about an Amazon product and check what the model predicts for it's star rating.", |
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inputs=[ |
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gr.inputs.Textbox(lines=5, label="Paste some text here"), |
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], |
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outputs=[ |
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gr.outputs.Textbox(label="Label"), |
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gr.outputs.Textbox(label="Score"), |
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], |
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examples=[ |
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["My favourite book is Cryptonomicon!"], ["็งใฎๅฅฝใใชๆฌใฏใใฏใชใใใใใณใณใใงใ"] |
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], |
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) |
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gradio_ui.launch() |