diff --git a/docs/_posts/ahmet-mesut/2024-04-04-mpnet_embeddings_biolord_2023_c_en.md b/docs/_posts/ahmet-mesut/2024-04-04-mpnet_embeddings_biolord_2023_c_en.md new file mode 100644 index 00000000000000..c4ce7a4be31dd5 --- /dev/null +++ b/docs/_posts/ahmet-mesut/2024-04-04-mpnet_embeddings_biolord_2023_c_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English BioLORD-2023-C MPNetEmbeddings from FremyCompany +author: John Snow Labs +name: mpnet_embeddings_biolord_2023_c +date: 2024-04-04 +tags: [en, mpnet, embeddings, biolord, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.3.1 +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_c` is a English model originally trained by `FremyCompany`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_embeddings_biolord_2023_c_en_5.3.1_3.0_1712265672474.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_embeddings_biolord_2023_c_en_5.3.1_3.0_1712265672474.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} + +```python +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("documents") + +embeddings =MPNetEmbeddings.pretrained("mpnet_embeddings_biolord_2023_c","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_c", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mpnet_embeddings_biolord_2023_c| +|Compatibility:|Spark NLP 5.3.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[MPNet]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/FremyCompany/BioLORD-2023-C