2024-02-11-bge_m3_xx (#14170)

* Add model 2024-02-11-bge_m3_xx

* Update 2024-02-11-bge_m3_xx.md

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Co-authored-by: ahmedlone127 <ahmedlone127@gmail.com>
Co-authored-by: Maziyar Panahi <maziyar.panahi@iscpif.fr>

docs/_posts/ahmedlone127/2024-02-11-bge_m3_xx.md

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+---
+layout: model
+title: Multilingual bge_m3 XlmRoBertaSentenceEmbeddings from BAII
+author: John Snow Labs
+name: bge_m3
+date: 2024-02-11
+tags: [xx, open_source, onnx]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.2.3
+spark_version: 3.4
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.bge_m3 is a Multilingual model originally trained by BAII.
+
+## 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/bge_m3_xx_5.2.3_3.4_1707668886363.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_m3_xx_5.2.3_3.4_1707668886363.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")
+
+sentencerDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")\ 
+    .setInputCols(["document"])\ 
+    .setOutputCol("sentence")
+
+embeddings =XlmRoBertaSentenceEmbeddings.pretrained("bge_m3 ","xx") \
+            .setInputCols(["sentence"]) \
+            .setOutputCol("embeddings")
+
+pipeline = Pipeline().setStages([document_assembler, sentencerDL, embeddings])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("documents")
+
+val sentencerDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+    .setInputCols(["document"])
+    .setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings 
+    .pretrained("bge_m3 ", "xx")
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, sentencerDL, embeddings))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_m3|
+|Compatibility:|Spark NLP 5.2.3+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[sentence_embeddings]|
+|Language:|xx|
+|Size:|410.8 MB|
+|Max sentence length:|32|
+
+## References
+
+https://huggingface.co/BAAI/bge-m3