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  ---
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  pipeline_tag: sentence-similarity
 
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  tags:
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  - sentence-transformers
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  - feature-extraction
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  - sentence-similarity
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  - transformers
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- - transformers
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- - transformers
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- - transformers
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- - transformers
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- - transformers
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- - transformers
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- - transformers
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  ---
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  # sentence-transformers/facebook-dpr-question_encoder-single-nq-base
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- This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
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  ## Citing & Authors
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- This model was trained by [sentence-transformers](https://www.sbert.net/).
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-
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- If you find this model helpful, feel free to cite our publication [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://arxiv.org/abs/1908.10084):
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- ```bibtex
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- @inproceedings{reimers-2019-sentence-bert,
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- title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
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- author = "Reimers, Nils and Gurevych, Iryna",
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- booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
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- month = "11",
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- year = "2019",
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- publisher = "Association for Computational Linguistics",
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- url = "http://arxiv.org/abs/1908.10084",
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- }
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- ```
 
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  ---
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  pipeline_tag: sentence-similarity
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+ license: apache-2.0
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  tags:
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  - sentence-transformers
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  - feature-extraction
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  - sentence-similarity
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  - transformers
 
 
 
 
 
 
 
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  ---
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  # sentence-transformers/facebook-dpr-question_encoder-single-nq-base
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+ This is a port of the [DPR Model](https://github.com/facebookresearch/DPR) to [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
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  ## Citing & Authors
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+ Have a look at: [DPR Model](https://github.com/facebookresearch/DPR)