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license: mit |
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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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scores = model.predict([[sentence, l] for l in labels]) |
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print(scores) |
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#array([0.04118565, 0.2435827 , 0.03941465, 0.00203637, 0.00501176, 0.1423797], dtype=float32) |
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``` |
