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  license: mit
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  ---
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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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  license: mit
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  ---
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+ ### Usage
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+ First, install [Sentence-Transformers](https://www.sbert.net/)
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+ Then,
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  ```python
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+ from sentence_transformers import CrossEncoder
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+ model_name="ragarwal/deberta-v3-base-nli-mixer"
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+ model = CrossEncoder(model_name, max_length=256)
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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"]