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from difflib import Differ |
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import gradio as gr |
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from transformers import pipeline |
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pipe = pipeline("summarization", "dominguesm/positive-reframing-en") |
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def predict(text, operation): |
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try: |
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res = pipe(f"[{operation}]: {text}", max_length=124) |
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except Exception as e: |
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return e |
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d = Differ() |
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return ( |
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res[0]["summary_text"], |
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[ |
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(token[2:], token[0] if token[0] != " " else None) |
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for token in d.compare(text, res[0]["summary_text"]) |
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], |
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) |
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iface = gr.Interface( |
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title="Positive Reframing EN", |
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description="This model is a T5 adjusted to the sentiment transfer task, where the objective is to reverse the sentiment polarity of a text without contradicting the original meaning. Positive reframing induces a complementary positive viewpoint (e.g. glass-half-full) escaping negative patterns. More info [here](https://huggingface.co/dominguesm/positive-reframing-en).", |
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fn=predict, |
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inputs=[ |
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gr.Textbox( |
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lines=1, |
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placeholder=( |
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f"Pensar no meu futuro me faz querer viver numa ilha sozinha para sempre" |
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), |
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), |
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gr.Radio( |
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[ |
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"growth", |
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"impermanence", |
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"neutralizing", |
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"optimism", |
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"self_affirmation", |
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"thankfulness", |
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] |
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), |
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], |
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outputs=[ |
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gr.Textbox(label="Generated Text"), |
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gr.HighlightedText( |
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label="Diff", |
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combine_adjacent=True, |
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).style(color_map={"+": "green", "-": "red"}), |
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], |
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examples=[ |
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[ |
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"You know I really don't care about the power struggle between the papacy and secular authority in the medieval ages. stupid", |
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"growth", |
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], |
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[ |
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"thinking about my future makes me want to go live on a island alone forever. annoyed", |
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"optimism", |
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], |
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[ |
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"Who would have ever guessed that it would be so freaking hard to get three different grades from two different schools together.", |
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"thankfulness", |
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], |
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], |
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) |
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iface.launch() |
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