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--- |
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license: apache-2.0 |
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datasets: |
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- sentence-transformers/quora-duplicates |
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language: |
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- en |
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base_model: |
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- FacebookAI/roberta-base |
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pipeline_tag: text-ranking |
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library_name: sentence-transformers |
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tags: |
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- transformers |
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--- |
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# Cross-Encoder for Quora Duplicate Questions Detection |
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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 the [Quora Duplicate Questions](https://www.quora.com/q/quoradata/First-Quora-Dataset-Release-Question-Pairs) dataset. The model will predict a score between 0 and 1 how likely the two given questions are duplicates. |
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Note: The model is not suitable to estimate the similarity of questions, e.g. the two questions "How to learn Java" and "How to learn Python" will result in a rather low score, as these are not duplicates. |
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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/quora-roberta-base') |
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scores = model.predict([('Question 1', 'Question 2'), ('Question 3', 'Question 4')]) |
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``` |
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You can use this model also without sentence_transformers and by just using Transformers ``AutoModel`` class |
