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  ## PEARL-small
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  [Learning High-Quality and General-Purpose Phrase Representations](https://arxiv.org/pdf/2401.10407.pdf). <br>
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  [Lihu Chen](https://chenlihu.com), [Gaël Varoquaux](https://gael-varoquaux.info/), [Fabian M. Suchanek](https://suchanek.name/).
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- <br> Accepted by EACL Findings 2024 <br>
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- PEARL-small is a variant of [E5-small](https://huggingface.co/intfloat/e5-small-v2) finetuned on our constructed context-free [dataset](https://zenodo.org/records/10676475) to yield better representations
 
 
 
 
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  for phrases and strings. <br>
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- If you require semantic similarity computation for strings, our PEARL model might be a helpful tool.<br>
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- It offers powerful embeddings suitable for tasks like string matching, entity retrieval, entity clustering, and fuzzy join.
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  🤗 [PEARL-small](https://huggingface.co/Lihuchen/pearl_small) 🤗 [PEARL-base](https://huggingface.co/Lihuchen/pearl_base)
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  <br>
 
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  ## PEARL-small
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  [Learning High-Quality and General-Purpose Phrase Representations](https://arxiv.org/pdf/2401.10407.pdf). <br>
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  [Lihu Chen](https://chenlihu.com), [Gaël Varoquaux](https://gael-varoquaux.info/), [Fabian M. Suchanek](https://suchanek.name/).
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+ Accepted by EACL Findings 2024 <br>
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+ PEARL-small is a lightweight string embedding model. It is the tool of choice for semantic similarity computation for strings,
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+ creating excellent embeddings for string matching, entity retrieval, entity clustering, fuzzy join...
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+ <br>
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+ It differents from typically sentence embedders because it adds a character-level representation giving a good support for open vocabulary.
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+ The model is a variant of [E5-small](https://huggingface.co/intfloat/e5-small-v2) finetuned on our constructed context-free [dataset](https://zenodo.org/records/10676475) to yield better representations
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  for phrases and strings. <br>
 
 
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  🤗 [PEARL-small](https://huggingface.co/Lihuchen/pearl_small) 🤗 [PEARL-base](https://huggingface.co/Lihuchen/pearl_base)
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  <br>