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--- |
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pipeline_tag: text-classification |
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tags: |
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- cross-encoder |
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- sentence-similarity |
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- transformers |
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--- |
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# Cross-Encoder |
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This model was trained using [SentenceTransformers](https://sbert.net) [Cross-Encoder](https://www.sbert.net/examples/applications/cross-encoder/README.html) class. |
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## Training Data |
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This model was trained on [stsb](https://huggingface.co./datasets/mteb/stsbenchmark-sts). The model will predict a score between 0 and 1 for how semantically similarity two sentences are. |
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## Usage and Performance |
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```python |
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from sentence_transformers import CrossEncoder |
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model = CrossEncoder('tomaarsen/distilroberta-base-stsb-cross-encoder') |
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scores = model.predict([('Sentence 1', 'Sentence 2'), ('Sentence 3', 'Sentence 4')]) |
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``` |
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The model will predict scores for the pairs `('Sentence 1', 'Sentence 2')` and `('Sentence 3', 'Sentence 4')`. |
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## Model Card Author |
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I adapted this model card from [https://huggingface.co./efederici/cross-encoder-bert-base-stsb](efederici/cross-encoder-bert-base-stsb) by @efederici. |
