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README.md
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license: apache-2.0
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# Cross-Encoder for
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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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## Usage and Performance
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Pre-trained models can be used like this:
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```
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from sentence_transformers import CrossEncoder
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scores = model.predict([('Sentence 1', 'Sentence 2'), ('Sentence 3', 'Sentence 4')])
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```
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license: apache-2.0
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# Cross-Encoder for Semantic Textual Similarity
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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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## Usage and Performance
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Pre-trained models can be used like this:
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```python
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from sentence_transformers import CrossEncoder
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model = CrossEncoder('cross-encoder/stsb-roberta-base')
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scores = model.predict([('Sentence 1', 'Sentence 2'), ('Sentence 3', 'Sentence 4')])
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```
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