louisbrulenaudet
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<img src="assets/thumbnail.webp">
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#
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This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [intfloat/multilingual-e5-large](https://huggingface.co/intfloat/multilingual-e5-large). It maps sentences & paragraphs to a 1024-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
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publisher = "Association for Computational Linguistics",
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url = "https://arxiv.org/abs/1908.10084",
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```
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<img src="assets/thumbnail.webp">
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# Lemone-Embed: A Series of Fine-Tuned Embedding Models for French Taxation
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This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [intfloat/multilingual-e5-large](https://huggingface.co/intfloat/multilingual-e5-large). It maps sentences & paragraphs to a 1024-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
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publisher = "Association for Computational Linguistics",
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url = "https://arxiv.org/abs/1908.10084",
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}
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```
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If you use this code in your research, please use the following BibTeX entry.
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```BibTeX
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@misc{louisbrulenaudet2024,
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author = {Louis Brulé Naudet},
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title = {Lemone-Embed: A Series of Fine-Tuned Embedding Models for French Taxation},
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year = {2024}
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howpublished = {\url{https://huggingface.co/datasets/louisbrulenaudet/lemone-embed-l-boost}},
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}
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```
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## Feedback
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If you have any feedback, please reach out at [[email protected]](mailto:[email protected]).
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