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Positive Perspectives with Portuguese Text Reframing

Model description

This model is a PTT5 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. Based on the article arXiv:2204.02952.

How to use

The model uses one or more sentiment strategies concatenated with a sentence and will generate a sentence with the applied sentiment output. The maximum string length is 1024 tokens. Entries must be organized in the following format:

"['thankfulness', 'optimism']: Tenho tanta coisa para fazer antes de sair da cidade por uma semana no domingo."

Available sentiment strategies:

growth: viewing a challenging event as an opportunity for the author to specifically grow or improve himself.

impermanence: Saying that bad things don't last forever, will get better soon, and/or that other people have had similar difficulties.

neutralizing: Replacing a negative word with a neutral word. For example, “This was a terrible day” becomes “This was a long day”.

optimism: Focusing on things about the situation itself, at that moment, that are good (not just predicting a better future).

self_affirmation: Talking about what strengths the author already has, or values he admires, such as love, courage, perseverance, etc.

thankfulness: Expressing gratitude or gratitude with keywords like appreciate, happy for it, grateful for, good thing, etc.


from transformers import pipeline

pipe = pipeline('summarization', "dominguesm/positive-reframing-ptbr")

text = "['thankfulness', 'optimism']: Tenho tanta coisa para fazer antes de sair da cidade por uma semana no domingo."

pipe(text, max_length=1024)
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