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+---
+layout: model
+title: English BioLORD-2023 MPNetEmbeddings from FremyCompany
+author: John Snow Labs
+name: mpnet_embeddings_biolord_2023
+date: 2024-04-22
+tags: [en, mpnet, embeddings, biolord, open_source, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.3.4
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP `mpnet_embeddings_biolord_2023` is a English model originally trained by `FremyCompany`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_embeddings_biolord_2023_en_5.3.4_3.0_1713812521034.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_embeddings_biolord_2023_en_5.3.4_3.0_1713812521034.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler()\
+    .setInputCol("text")\
+    .setOutputCol("documents")
+    
+embeddings =MPNetEmbeddings.pretrained("mpnet_embeddings_biolord_2023","en")\
+    .setInputCols(["documents"])\
+    .setOutputCol("mpnet_embeddings")
+
+pipeline = Pipeline().setStages([document_assembler, embeddings])
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("documents")
+    
+val embeddings = MPNetEmbeddings 
+    .pretrained("mpnet_embeddings_biolord_2023", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("mpnet_embeddings") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings))
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnet_embeddings_biolord_2023|
+|Compatibility:|Spark NLP 5.3.4+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[MPNet]|
+|Language:|en|
+|Size:|407.0 MB|
+
+## References
+
+https://huggingface.co/FremyCompany/BioLORD-2023
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