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  ### Trained Using Sentence-Transformers
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  #### Usage
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- ```
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- sentence = "During its monthly call, the National Oceanic and Atmospheric Administration warned of increased temperatures and low precipitation"
 
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  labels = ["Computer", "Climate Change", "Tablet", "Football", "Artificial Intelligence", "Global Warming"]
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  scores = model.predict([[sentence, l] for l in labels])
 
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  ### Trained Using Sentence-Transformers
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  #### Usage
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+ ```python
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+ sentence = "During its monthly call, the National Oceanic and Atmospheric Administration warned of \
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+ increased temperatures and low precipitation"
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  labels = ["Computer", "Climate Change", "Tablet", "Football", "Artificial Intelligence", "Global Warming"]
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  scores = model.predict([[sentence, l] for l in labels])