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  ---
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- # {CLFE(ConMath)}
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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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  <!--- Describe your model here -->
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- ## Usage (Sentence-Transformers)
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- Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed:
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-
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- ```
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- pip install -U sentence-transformers
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- ```
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-
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- Then you can use the model like this:
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  ```python
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  embedding_latex = model.encode([{'latex': latex}])
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  ## Citing & Authors
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  <!--- Describe where people can find more information -->
 
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  @inproceedings{wang2023math,
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  title={Math Information Retrieval with Contrastive Learning of Formula Embeddings},
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  author={Wang, Jingyi and Tian, Xuedong},
 
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  ---
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+ # CLFE(ConMath)
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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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  <!--- Describe your model here -->
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+ ## Usage
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  ```python
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  embedding_latex = model.encode([{'latex': latex}])
 
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  ## Citing & Authors
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  <!--- Describe where people can find more information -->
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+
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  @inproceedings{wang2023math,
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  title={Math Information Retrieval with Contrastive Learning of Formula Embeddings},
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  author={Wang, Jingyi and Tian, Xuedong},