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license: mit
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### Trained Using Sentence-Transformers
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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"]
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